default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDWilliam W. Cohen
2020 – today
- 2024
[c230]Hexiang Hu, Kelvin C. K. Chan, Yu-Chuan Su, Wenhu Chen, Yandong Li, Kihyuk Sohn, Yang Zhao, Xue Ben, Boqing Gong, William W. Cohen, Ming-Wei Chang, Xuhui Jia:
Instruct-Imagen: Image Generation with Multi-modal Instruction. CVPR 2024: 4754-4763- [c229]Yury Zemlyanskiy, Michiel de Jong, Luke Vilnis, Santiago Ontañón, William W. Cohen, Sumit Sanghai, Joshua Ainslie:
MEMORY-VQ: Compression for Tractable Internet-Scale Memory. NAACL (Short Papers) 2024: 737-744 - [c228]Tal Schuster, Ádám D. Lelkes, Haitian Sun, Jai Gupta, Jonathan Berant, William W. Cohen, Donald Metzler:
SEMQA: Semi-Extractive Multi-Source Question Answering. NAACL-HLT 2024: 1363-1381 - [c227]Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson, William W. Cohen:
Stratified Prediction-Powered Inference for Effective Hybrid Evaluation of Language Models. NeurIPS 2024 - [c226]Gabriel Sarch, Lawrence Jang, Michael J. Tarr, William W. Cohen, Kenneth Marino, Katerina Fragkiadaki:
VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought. NeurIPS 2024 - [i91]Hexiang Hu, Kelvin C. K. Chan, Yu-Chuan Su, Wenhu Chen, Yandong Li, Kihyuk Sohn, Yang Zhao, Xue Ben, Boqing Gong, William W. Cohen, Ming-Wei Chang, Xuhui Jia:
Instruct-Imagen: Image Generation with Multi-modal Instruction. CoRR abs/2401.01952 (2024) - [i90]R. Alex Hofer, Joshua Maynez, Bhuwan Dhingra, Adam Fisch, Amir Globerson, William W. Cohen:
Bayesian Prediction-Powered Inference. CoRR abs/2405.06034 (2024) - [i89]Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson, William W. Cohen:
Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation. CoRR abs/2406.04291 (2024) - [i88]Gabriel Sarch, Lawrence Jang, Michael J. Tarr, William W. Cohen, Kenneth Marino, Katerina Fragkiadaki:
ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights. CoRR abs/2406.14596 (2024) - [i87]Cassandra A. Cohen, William W. Cohen:
Watch Your Steps: Observable and Modular Chains of Thought. CoRR abs/2409.15359 (2024) - 2023
- [j48]Wenhu Chen, Xueguang Ma, Xinyi Wang, William W. Cohen:
Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks. Trans. Mach. Learn. Res. 2023 (2023) - [c225]William W. Cohen, Wenhu Chen, Michiel de Jong, Nitish Gupta, Alessandro Presta, Pat Verga, John Wieting:
QA Is the New KR: Question-Answer Pairs as Knowledge Bases. AAAI 2023: 15385-15392 - [c224]Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen:
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. ACL (Findings) 2023: 11534-11547 - [c223]John Wieting, Jonathan H. Clark, William W. Cohen, Graham Neubig, Taylor Berg-Kirkpatrick:
Beyond Contrastive Learning: A Variational Generative Model for Multilingual Retrieval. ACL (1) 2023: 12044-12066 - [c222]Julian Martin Eisenschlos, Jeremy R. Cole, Fangyu Liu, William W. Cohen:
WinoDict: Probing language models for in-context word acquisition. EACL 2023: 94-102 - [c221]Wenhu Chen, Pat Verga, Michiel de Jong, John Wieting, William W. Cohen:
Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering. EACL 2023: 1589-1602 - [c220]Wenhu Chen, Hexiang Hu, Chitwan Saharia, William W. Cohen:
Re-Imagen: Retrieval-Augmented Text-to-Image Generator. ICLR 2023 - [c219]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
Scenario-based Question Answering with Interacting Contextual Properties. ICLR 2023 - [c218]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen:
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. ICML 2023: 7329-7342 - [c217]Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Ruiz, Xuhui Jia, Ming-Wei Chang, William W. Cohen:
Subject-driven Text-to-Image Generation via Apprenticeship Learning. NeurIPS 2023 - [i86]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William W. Cohen:
Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. CoRR abs/2301.10448 (2023) - [i85]Wenhu Chen, Hexiang Hu
, Yandong Li, Nataniel Ruiz, Xuhui Jia, Ming-Wei Chang, William W. Cohen:
Subject-driven Text-to-Image Generation via Apprenticeship Learning. CoRR abs/2304.00186 (2023) - [i84]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Sumit Sanghai, William W. Cohen, Joshua Ainslie:
GLIMMER: generalized late-interaction memory reranker. CoRR abs/2306.10231 (2023) - [i83]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
Answering Ambiguous Questions with a Database of Questions, Answers, and Revisions. CoRR abs/2308.08661 (2023) - [i82]Yury Zemlyanskiy, Michiel de Jong, Luke Vilnis, Santiago Ontañón, William W. Cohen, Sumit Sanghai, Joshua Ainslie:
MEMORY-VQ: Compression for Tractable Internet-Scale Memory. CoRR abs/2308.14903 (2023) - [i81]Tal Schuster, Ádám D. Lelkes, Haitian Sun, Jai Gupta, Jonathan Berant, William W. Cohen, Donald Metzler:
SEMQA: Semi-Extractive Multi-Source Question Answering. CoRR abs/2311.04886 (2023) - [i80]Vasilisa Bashlovkina, Zhaobin Kuang, Riley Matthews, Edward Clifford, Yennie Jun, William W. Cohen, Simon Baumgartner:
Trusted Source Alignment in Large Language Models. CoRR abs/2311.06697 (2023) - [i79]Chung-Ching Chang, William W. Cohen, Yun-Hsuan Sung:
Characterizing Tradeoffs in Language Model Decoding with Informational Interpretations. CoRR abs/2311.10083 (2023) - 2022
- [j47]Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, Daniel Gillick, Jacob Eisenstein, William W. Cohen:
Time-Aware Language Models as Temporal Knowledge Bases. Trans. Assoc. Comput. Linguistics 10: 257-273 (2022) - [j46]Danish Pruthi, Rachit Bansal, Bhuwan Dhingra, Livio Baldini Soares, Michael Collins, Zachary C. Lipton, Graham Neubig, William W. Cohen:
Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students? Trans. Assoc. Comput. Linguistics 10: 359-375 (2022) - [c216]Siddhant Arora, Danish Pruthi, Norman M. Sadeh, William W. Cohen, Zachary C. Lipton, Graham Neubig:
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations. AAAI 2022: 5277-5285 - [c215]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. ACL (1) 2022: 3627-3637 - [c214]Wenhu Chen, Hexiang Hu, Xi Chen, Pat Verga, William W. Cohen:
MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text. EMNLP 2022: 5558-5570 - [c213]Vidhisha Balachandran, Hannaneh Hajishirzi, William W. Cohen, Yulia Tsvetkov:
Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling. EMNLP 2022: 9818-9830 - [c212]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen:
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. ICLR 2022 - [c211]Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Prakash Gupta, Tal Schuster, William W. Cohen, Donald Metzler:
Transformer Memory as a Differentiable Search Index. NeurIPS 2022 - [i78]Yi Tay, Vinh Q. Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Prakash Gupta, Tal Schuster, William W. Cohen, Donald Metzler:
Transformer Memory as a Differentiable Search Index. CoRR abs/2202.06991 (2022) - [i77]Wenhu Chen, Pat Verga, Michiel de Jong, John Wieting, William W. Cohen:
Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering. CoRR abs/2204.04581 (2022) - [i76]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
Reasoning over Logically Interacted Conditions for Question Answering. CoRR abs/2205.12898 (2022) - [i75]Wenhu Chen, William W. Cohen, Michiel de Jong, Nitish Gupta, Alessandro Presta, Pat Verga, John Wieting:
QA Is the New KR: Question-Answer Pairs as Knowledge Bases. CoRR abs/2207.00630 (2022) - [i74]Julian Martin Eisenschlos, Jeremy R. Cole, Fangyu Liu, William W. Cohen:
WinoDict: Probing language models for in-context word acquisition. CoRR abs/2209.12153 (2022) - [i73]Wenhu Chen, Hexiang Hu, Chitwan Saharia, William W. Cohen:
Re-Imagen: Retrieval-Augmented Text-to-Image Generator. CoRR abs/2209.14491 (2022) - [i72]Wenhu Chen, Hexiang Hu, Xi Chen, Pat Verga, William W. Cohen:
MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text. CoRR abs/2210.02928 (2022) - [i71]Vidhisha Balachandran, Hannaneh Hajishirzi, William W. Cohen, Yulia Tsvetkov:
Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling. CoRR abs/2210.12378 (2022) - [i70]Wenhu Chen, Xueguang Ma, Xinyi Wang, William W. Cohen:
Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks. CoRR abs/2211.12588 (2022) - [i69]Bernd Bohnet, Vinh Q. Tran, Pat Verga, Roee Aharoni, Daniel Andor, Livio Baldini Soares, Jacob Eisenstein, Kuzman Ganchev, Jonathan Herzig, Kai Hui, Tom Kwiatkowski, Ji Ma, Jianmo Ni, Tal Schuster, William W. Cohen, Michael Collins, Dipanjan Das, Donald Metzler, Slav Petrov, Kellie Webster:
Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models. CoRR abs/2212.08037 (2022) - [i68]Michiel de Jong, Yury Zemlyanskiy, Joshua Ainslie, Nicholas FitzGerald, Sumit Sanghai, Fei Sha, William W. Cohen:
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. CoRR abs/2212.08153 (2022) - [i67]John Wieting, Jonathan H. Clark, William W. Cohen, Graham Neubig, Taylor Berg-Kirkpatrick:
Beyond Contrastive Learning: A Variational Generative Model for Multilingual Retrieval. CoRR abs/2212.10726 (2022) - 2021
- [c210]Avishai Zagoury, Einat Minkov, Idan Szpektor, William W. Cohen:
What's the Best Place for an AI Conference, Vancouver or _______: Why Completing Comparative Questions is Difficult. AAAI 2021: 14292-14300 - [c209]Vidhisha Balachandran, Bhuwan Dhingra, Haitian Sun, Michael Collins, William W. Cohen:
Investigating the Effect of Background Knowledge on Natural Questions. DeeLIO@NAACL-HLT 2021: 25-30 - [c208]Keshav Kolluru, Martin Rezk, Pat Verga, William W. Cohen, Partha P. Talukdar:
Multilingual Fact Linking. AKBC 2021 - [c207]Julian Martin Eisenschlos, Maharshi Gor, Thomas Müller, William W. Cohen:
MATE: Multi-view Attention for Table Transformer Efficiency. EMNLP (1) 2021: 7606-7619 - [c206]Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, William W. Cohen:
Open Question Answering over Tables and Text. ICLR 2021 - [c205]Haitian Sun, Patrick Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W. Cohen:
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations. ICML 2021: 9966-9977 - [c204]Pat Verga, Haitian Sun, Livio Baldini Soares, William W. Cohen:
Adaptable and Interpretable Neural MemoryOver Symbolic Knowledge. NAACL-HLT 2021: 3678-3691 - [c203]Bill Yuchen Lin, Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Xiang Ren, William W. Cohen:
Differentiable Open-Ended Commonsense Reasoning. NAACL-HLT 2021: 4611-4625 - [p2]Haitian Sun, Pat Verga, William W. Cohen:
Answering Natural-Language Questions with Neuro-Symbolic Knowledge Bases. Neuro-Symbolic Artificial Intelligence 2021: 126-145 - [i66]Haitian Sun, Pat Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W. Cohen:
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations. CoRR abs/2102.07043 (2021) - [i65]Avishai Zagoury, Einat Minkov, Idan Szpektor, William W. Cohen:
What's the best place for an AI conference, Vancouver or ______: Why completing comparative questions is difficult. CoRR abs/2104.01940 (2021) - [i64]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents. CoRR abs/2106.00200 (2021) - [i63]Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, Daniel Gillick, Jacob Eisenstein, William W. Cohen:
Time-Aware Language Models as Temporal Knowledge Bases. CoRR abs/2106.15110 (2021) - [i62]Julian Martin Eisenschlos, Maharshi Gor, Thomas Müller, William W. Cohen:
MATE: Multi-view Attention for Table Transformer Efficiency. CoRR abs/2109.04312 (2021) - [i61]Keshav Kolluru, Martin Rezk, Pat Verga, William W. Cohen, Partha P. Talukdar:
Multilingual Fact Linking. CoRR abs/2109.14364 (2021) - [i60]Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen:
Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. CoRR abs/2110.06176 (2021) - [i59]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. CoRR abs/2110.06884 (2021) - [i58]Siddhant Arora, Danish Pruthi, Norman M. Sadeh, William W. Cohen, Zachary C. Lipton, Graham Neubig:
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations. CoRR abs/2112.09669 (2021) - 2020
- [j45]William W. Cohen, Fan Yang, Kathryn Mazaitis:
TensorLog: A Probabilistic Database Implemented Using Deep-Learning Infrastructure. J. Artif. Intell. Res. 67: 285-325 (2020) - [c202]William W. Cohen, Haitian Sun, R. Alex Hofer, Matthew Siegler:
Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base. ICLR 2020 - [c201]Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen:
Differentiable Reasoning over a Virtual Knowledge Base. ICLR 2020 - [c200]Haitian Sun, Andrew O. Arnold, Tania Bedrax-Weiss, Fernando Pereira, William W. Cohen:
Faithful Embeddings for Knowledge Base Queries. NeurIPS 2020 - [c199]Yifeng Tao, Chunhui Cai, William W. Cohen, Xinghua Lu:
From Genome to Phenome: Predicting Multiple Cancer Phenotypes Based on Somatic GenomicAlterations via the Genomic Impact Transformer. PSB 2020: 79-90 - [i57]William W. Cohen, Haitian Sun, R. Alex Hofer, Matthew Siegler:
Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base. CoRR abs/2002.06115 (2020) - [i56]Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen:
Differentiable Reasoning over a Virtual Knowledge Base. CoRR abs/2002.10640 (2020) - [i55]Haitian Sun, Andrew O. Arnold, Tania Bedrax-Weiss, Fernando Pereira, William W. Cohen:
Guessing What's Plausible But Remembering What's True: Accurate Neural Reasoning for Question-Answering. CoRR abs/2004.03658 (2020) - [i54]Pat Verga, Haitian Sun, Livio Baldini Soares, William W. Cohen:
Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge. CoRR abs/2007.00849 (2020) - [i53]Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, William W. Cohen:
Open Question Answering over Tables and Text. CoRR abs/2010.10439 (2020) - [i52]Bill Yuchen Lin, Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Xiang Ren, William W. Cohen:
Differentiable Open-Ended Commonsense Reasoning. CoRR abs/2010.14439 (2020) - [i51]Danish Pruthi, Bhuwan Dhingra, Livio Baldini Soares, Michael Collins, Zachary C. Lipton, Graham Neubig, William W. Cohen:
Evaluating Explanations: How much do explanations from the teacher aid students? CoRR abs/2012.00893 (2020)
2010 – 2019
- 2019
- [c198]Bhuwan Dhingra, Manaal Faruqui, Ankur P. Parikh, Ming-Wei Chang, Dipanjan Das, William W. Cohen:
Handling Divergent Reference Texts when Evaluating Table-to-Text Generation. ACL (1) 2019: 4884-4895 - [c197]Haitian Sun, Tania Bedrax-Weiss, William W. Cohen:
PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text. EMNLP/IJCNLP (1) 2019: 2380-2390 - [c196]Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W. Cohen, Xinghua Lu:
PubMedQA: A Dataset for Biomedical Research Question Answering. EMNLP/IJCNLP (1) 2019: 2567-2577 - [c195]Fan Yang, Liu Leqi, Yifan Wu, Zachary Chase Lipton, Pradeep Ravikumar, Tom M. Mitchell, William W. Cohen:
Game Design for Eliciting Distinguishable Behavior. NeurIPS 2019: 4686-4695 - [c194]Haohan Wang, Xiang Liu, Yifeng Tao, Wenting Ye, Qiao Jin, William W. Cohen, Eric P. Xing:
Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning. PSB 2019: 112-123 - [i50]Samira Abnar, Tania Bedrax-Weiss, Tom Kwiatkowski, William W. Cohen:
Incremental Reading for Question Answering. CoRR abs/1901.04936 (2019) - [i49]Qiao Jin, Bhuwan Dhingra, William W. Cohen, Xinghua Lu:
Probing Biomedical Embeddings from Language Models. CoRR abs/1904.02181 (2019) - [i48]Haitian Sun, Tania Bedrax-Weiss, William W. Cohen:
PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text. CoRR abs/1904.09537 (2019) - [i47]William W. Cohen, Matthew Siegler, R. Alex Hofer:
Neural Query Language: A Knowledge Base Query Language for Tensorflow. CoRR abs/1905.06209 (2019) - [i46]William W. Cohen, Haitian Sun, R. Alex Hofer, Matthew Siegler:
Differentiable Representations For Multihop Inference Rules. CoRR abs/1905.10417 (2019) - [i45]Bhuwan Dhingra, Manaal Faruqui, Ankur P. Parikh, Ming-Wei Chang, Dipanjan Das, William W. Cohen:
Handling Divergent Reference Texts when Evaluating Table-to-Text Generation. CoRR abs/1906.01081 (2019) - [i44]Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William W. Cohen, Xinghua Lu:
PubMedQA: A Dataset for Biomedical Research Question Answering. CoRR abs/1909.06146 (2019) - [i43]Andrew O. Arnold, William W. Cohen:
Instance-based Transfer Learning for Multilingual Deep Retrieval. CoRR abs/1911.06111 (2019) - [i42]Fan Yang, Liu Leqi, Yifan Wu, Zachary C. Lipton, Pradeep Ravikumar, William W. Cohen, Tom M. Mitchell:
Game Design for Eliciting Distinguishable Behavior. CoRR abs/1912.06074 (2019) - 2018
- [j44]Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha P. Talukdar, Bo Yang, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matt Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling:
Never-ending learning. Commun. ACM 61(5): 103-115 (2018) - [c193]Vidhisha Balachandran, Dheeraj Rajagopal, Rose Catherine Kanjirathinkal, William W. Cohen:
Learning to Define Terms in the Software Domain. NUT@EMNLP 2018: 164-172 - [c192]Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, Christopher D. Manning:
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. EMNLP 2018: 2369-2380 - [c191]Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, William W. Cohen:
Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text. EMNLP 2018: 4231-4242 - [c190]Rose Catherine, William W. Cohen:
TransNets for Review Generation. ICLR (Workshop) 2018 - [c189]Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen:
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. ICLR 2018 - [c188]Fan Yang, Jiazhong Nie, William W. Cohen, Ni Lao:
Learning to Organize Knowledge with N-Gram Machines. ICLR (Workshop) 2018 - [c187]Bhuwan Dhingra, Qiao Jin, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Neural Models for Reasoning over Multiple Mentions Using Coreference. NAACL-HLT (2) 2018: 42-48 - [c186]Haitian Sun, William W. Cohen, Lidong Bing:
Semi-Supervised Learning with Declaratively Specified Entropy Constraints. NeurIPS 2018: 4430-4440 - [c185]Zhilin Yang, Junbo Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun:
GLoMo: Unsupervised Learning of Transferable Relational Graphs. NeurIPS 2018: 8964-8975 - [i41]Bhuwan Dhingra, Qiao Jin, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Neural Models for Reasoning over Multiple Mentions using Coreference. CoRR abs/1804.05922 (2018) - [i40]Haitian Sun, William W. Cohen, Lidong Bing:
Semi-Supervised Learning with Declaratively Specified Entropy Constraints. CoRR abs/1804.09238 (2018) - [i39]Zhilin Yang, Junbo Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun:
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations. CoRR abs/1806.05662 (2018) - [i38]Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, William W. Cohen:
Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text. CoRR abs/1809.00782 (2018) - [i37]Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, Christopher D. Manning:
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. CoRR abs/1809.09600 (2018) - 2017
- [j43]Lidong Bing, Zhiming Zhang, Wai Lam, William W. Cohen:
Towards a language-independent solution: Knowledge base completion by searching the Web and deriving language pattern. Knowl. Based Syst. 115: 80-86 (2017) - [c184]Lidong Bing, Bhuwan Dhingra, Kathryn Mazaitis, Jong Hyuk Park, William W. Cohen:
Bootstrapping Distantly Supervised IE Using Joint Learning and Small Well-Structured Corpora. AAAI 2017: 3408-3414 - [c183]Zhilin Yang, Junjie Hu, Ruslan Salakhutdinov, William W. Cohen:
Semi-Supervised QA with Generative Domain-Adaptive Nets. ACL (1) 2017: 1040-1050 - [c182]Bhuwan Dhingra, Hanxiao Liu, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Gated-Attention Readers for Text Comprehension. ACL (1) 2017: 1832-1846 - [c181]Fan Yang, William W. Cohen, Jiazhong Nie, Ni Lao:
Learning to Organize Knowledge with N-Gram Machines. AKBC@NIPS 2017 - [c180]Wen-Haw Chong, Ee-Peng Lim, William W. Cohen:
Collective Entity Linking in Tweets Over Space and Time. ECIR 2017: 82-94 - [c179]Zhilin Yang, Bhuwan Dhingra, Ye Yuan, Junjie Hu, William W. Cohen, Ruslan Salakhutdinov:
Words or Characters? Fine-grained Gating for Reading Comprehension. ICLR (Poster) 2017 - [c178]Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen:
Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks. ICLR (Poster) 2017 - [c177]Lidong Bing, William W. Cohen, Bhuwan Dhingra:
Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning. IJCAI 2017: 1454-1460 - [c176]Fan Yang, Zhilin Yang, William W. Cohen:
Differentiable Learning of Logical Rules for Knowledge Base Reasoning. NIPS 2017: 2319-2328 - [c175]Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov:
Good Semi-supervised Learning That Requires a Bad GAN. NIPS 2017: 6510-6520 - [c174]Rose Catherine, William W. Cohen:
TransNets: Learning to Transform for Recommendation. RecSys 2017: 288-296 - [c173]Rose Catherine, Kathryn Mazaitis, Maxine Eskénazi, William W. Cohen:
Explainable Entity-based Recommendations with Knowledge Graphs. RecSys Posters 2017 - [i36]Zhilin Yang, Junjie Hu, Ruslan Salakhutdinov, William W. Cohen:
Semi-Supervised QA with Generative Domain-Adaptive Nets. CoRR abs/1702.02206 (2017) - [i35]Fan Yang, Zhilin Yang, William W. Cohen:
Differentiable Learning of Logical Rules for Knowledge Base Completion. CoRR abs/1702.08367 (2017) - [i34]Bhuwan Dhingra, Hanxiao Liu, Ruslan Salakhutdinov, William W. Cohen:
A Comparative Study of Word Embeddings for Reading Comprehension. CoRR abs/1703.00993 (2017) - [i33]Lidong Bing, William W. Cohen, Bhuwan Dhingra:
Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning. CoRR abs/1703.01557 (2017) - [i32]Bhuwan Dhingra, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Linguistic Knowledge as Memory for Recurrent Neural Networks. CoRR abs/1703.02620 (2017) - [i31]Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen:
Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks. CoRR abs/1703.06345 (2017) - [i30]Rose Catherine, William W. Cohen:
TransNets: Learning to Transform for Recommendation. CoRR abs/1704.02298 (2017) - [i29]Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov:
Good Semi-supervised Learning that Requires a Bad GAN. CoRR abs/1705.09783 (2017) - [i28]Bhuwan Dhingra, Kathryn Mazaitis, William W. Cohen:
Quasar: Datasets for Question Answering by Search and Reading. CoRR abs/1707.03904 (2017) - [i27]Rose Catherine, Kathryn Mazaitis, Maxine Eskénazi, William W. Cohen:
Explainable Entity-based Recommendations with Knowledge Graphs. CoRR abs/1707.05254 (2017) - [i26]William W. Cohen, Fan Yang, Kathryn Mazaitis:
TensorLog: Deep Learning Meets Probabilistic DBs. CoRR abs/1707.05390 (2017) - [i25]Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen:
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. CoRR abs/1711.03953 (2017) - [i24]Fan Yang, Jiazhong Nie, William W. Cohen, Ni Lao:
Learning to Organize Knowledge with N-Gram Machines. CoRR abs/1711.06744 (2017) - 2016
- [c172]Lidong Bing, Mingyang Ling, Richard C. Wang, William W. Cohen:
Distant IE by Bootstrapping Using Lists and Document Structure. AAAI 2016: 2899-2905 - [c171]Bhuwan Dhingra, Zhong Zhou, Dylan J. Fitzpatrick, Michael Muehl, William W. Cohen:
Tweet2Vec: Character-Based Distributed Representations for Social Media. ACL (2) 2016 - [c170]Lidong Bing, William W. Cohen, Bhuwan Dhingra, Richard C. Wang:
Using Graphs of Classifiers to Impose Constraints on Semi-supervised Relation Extraction. AKBC@NAACL-HLT 2016: 1-6 - [c169]Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Revisiting Semi-Supervised Learning with Graph Embeddings. ICML 2016: 40-48 - [c168]William Yang Wang, William W. Cohen:
Learning First-Order Logic Embeddings via Matrix Factorization. IJCAI 2016: 2132-2138 - [c167]Zhilin Yang, Jie Tang, William W. Cohen:
Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs. IJCAI 2016: 2287-2293 - [c166]William Yang Wang, William W. Cohen:
Scalable Statistical Relational Learning for NLP. HLT-NAACL Tutorials 2016: 14-16 - [c165]Zhilin Yang, Ye Yuan, Yuexin Wu, William W. Cohen, Ruslan Salakhutdinov:
Review Networks for Caption Generation. NIPS 2016: 2361-2369 - [c164]Rose Catherine, William W. Cohen:
Personalized Recommendations using Knowledge Graphs: A Probabilistic Logic Programming Approach. RecSys 2016: 325-332 - [c163]Bhavana Dalvi, Aditya Kumar Mishra, William W. Cohen:
Hierarchical Semi-supervised Classification with Incomplete Class Hierarchies. WSDM 2016: 193-202 - [i23]Lidong Bing, Mingyang Ling, Richard C. Wang, William W. Cohen:
Distant IE by Bootstrapping Using Lists and Document Structure. CoRR abs/1601.00620 (2016) - [i22]Abhinav Maurya, Kenton Murray, Yandong Liu, Chris Dyer, William W. Cohen, Daniel B. Neill:
Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams. CoRR abs/1602.04393 (2016) - [i21]Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen:
Multi-Task Cross-Lingual Sequence Tagging from Scratch. CoRR abs/1603.06270 (2016) - [i20]Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Revisiting Semi-Supervised Learning with Graph Embeddings. CoRR abs/1603.08861 (2016) - [i19]Bhuwan Dhingra, Zhong Zhou, Dylan J. Fitzpatrick, Michael Muehl, William W. Cohen:
Tweet2Vec: Character-Based Distributed Representations for Social Media. CoRR abs/1605.03481 (2016) - [i18]William W. Cohen:
TensorLog: A Differentiable Deductive Database. CoRR abs/1605.06523 (2016) - [i17]Zhilin Yang, Ye Yuan, Yuexin Wu, Ruslan Salakhutdinov, William W. Cohen:
Encode, Review, and Decode: Reviewer Module for Caption Generation. CoRR abs/1605.07912 (2016) - [i16]Bhuwan Dhingra, Hanxiao Liu, William W. Cohen, Ruslan Salakhutdinov:
Gated-Attention Readers for Text Comprehension. CoRR abs/1606.01549 (2016) - [i15]Lidong Bing, Bhuwan Dhingra, Kathryn Mazaitis, Jong Hyuk Park, William W. Cohen:
Bootstrapping Distantly Supervised IE using Joint Learning and Small Well-structured Corpora. CoRR abs/1606.03398 (2016) - [i14]Zhilin Yang, Bhuwan Dhingra, Ye Yuan, Junjie Hu, William W. Cohen, Ruslan Salakhutdinov:
Words or Characters? Fine-grained Gating for Reading Comprehension. CoRR abs/1611.01724 (2016) - 2015
- [j42]Nan Li, Noboru Matsuda, William W. Cohen, Kenneth R. Koedinger:
Integrating representation learning and skill learning in a human-like intelligent agent. Artif. Intell. 219: 67-91 (2015) - [j41]Noboru Matsuda, William W. Cohen, Kenneth R. Koedinger:
Teaching the Teacher: Tutoring SimStudent Leads to More Effective Cognitive Tutor Authoring. Int. J. Artif. Intell. Educ. 25(1): 1-34 (2015) - [j40]Jay Pujara, Hui Miao, Lise Getoor, William W. Cohen:
Using Semantics and Statistics to Turn Data into Knowledge. AI Mag. 36(1): 65-74 (2015) - [j39]William Yang Wang, Kathryn Mazaitis, Ni Lao, William W. Cohen:
Efficient inference and learning in a large knowledge base - Reasoning with extracted information using a locally groundable first-order probabilistic logic. Mach. Learn. 100(1): 101-126 (2015) - [j38]ChengXiang Zhai, William W. Cohen, John D. Lafferty:
Beyond Independent Relevance: Methods and Evaluation Metrics for Subtopic Retrieval. SIGIR Forum 49(1): 2-9 (2015) - [c162]Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha Pratim Talukdar, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matthew Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling:
Never-Ending Learning. AAAI 2015: 2302-2310 - [c161]William Yang Wang, William W. Cohen:
Joint Information Extraction and Reasoning: A Scalable Statistical Relational Learning Approach. ACL (1) 2015: 355-364 - [c160]Ni Lao, Einat Minkov, William W. Cohen:
Learning Relational Features with Backward Random Walks. ACL (1) 2015: 666-675 - [c159]Dana Movshovitz-Attias, William W. Cohen:
KB-LDA: Jointly Learning a Knowledge Base of Hierarchy, Relations, and Facts. ACL (1) 2015: 1449-1459 - [c158]Lidong Bing, Sneha Chaudhari, Richard C. Wang, William W. Cohen:
Improving Distant Supervision for Information Extraction Using Label Propagation Through Lists. EMNLP 2015: 524-529 - [c157]Evgenia Wasserman Pritsker, William W. Cohen, Einat Minkov:
Learning to Identify the Best Contexts for Knowledge-based WSD. EMNLP 2015: 1662-1667 - [c156]William Yang Wang, Kathryn Mazaitis, William W. Cohen:
A Soft Version of Predicate Invention Based on Structured Sparsity. IJCAI 2015: 3918-3924 - [c155]Bhavana Bharat Dalvi, Einat Minkov, Partha Pratim Talukdar, William W. Cohen:
Automatic Gloss Finding for a Knowledge Base using Ontological Constraints. WSDM 2015: 369-378 - [i13]Dana Movshovitz-Attias, William W. Cohen:
Grounded Discovery of Coordinate Term Relationships between Software Entities. CoRR abs/1505.00277 (2015) - [i12]William W. Cohen, Charles Sutton, Martin T. Vechev:
Programming with "Big Code" (Dagstuhl Seminar 15472). Dagstuhl Reports 5(11): 90-102 (2015) - 2014
- [j37]Einat Minkov, William W. Cohen:
Adaptive graph walk-based similarity measures for parsed text. Nat. Lang. Eng. 20(3): 361-397 (2014) - [c154]William Yang Wang, Kathryn Mazaitis, William W. Cohen:
ProPPR: Efficient First-Order Probabilistic Logic Programming for Structure Discovery, Parameter Learning, and Scalable Inference. StarAI@AAAI 2014 - [c153]Partha Pratim Talukdar, William W. Cohen:
Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch. AISTATS 2014: 940-947 - [c152]William Yang Wang, Kathryn Mazaitis, William W. Cohen:
Structure Learning via Parameter Learning. CIKM 2014: 1199-1208 - [c151]William Yang Wang, Lingpeng Kong, Kathryn Mazaitis, William W. Cohen:
Dependency Parsing for Weibo: An Efficient Probabilistic Logic Programming Approach. EMNLP 2014: 1152-1158 - [c150]Noboru Matsuda, Cassondra L. Griger, Nikolaos Barbalios, Gabriel Stylianides, William W. Cohen, Kenneth R. Koedinger:
Investigating the Effect of Meta-cognitive Scaffolding for Learning by Teaching. Intelligent Tutoring Systems 2014: 104-113 - [c149]Tuan-Anh Hoang, William W. Cohen, Ee-Peng Lim:
On Modeling Community Behaviors and Sentiments in Microblogging. SDM 2014: 479-487 - [r1]Ramnath Balasubramanyan, William W. Cohen:
Block-LDA: Jointly Modeling Entity-Annotated Text and Entity-Entity Links. Handbook of Mixed Membership Models and Their Applications 2014: 255-273 - [i11]William Yang Wang, Kathryn Mazaitis, Ni Lao, Tom M. Mitchell, William W. Cohen:
Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic. CoRR abs/1404.3301 (2014) - 2013
- [j36]Nan Li, William W. Cohen, Kenneth R. Koedinger:
Problem Order Implications for Learning. Int. J. Artif. Intell. Educ. 23(1-4): 71-93 (2013) - [c148]Jay Pujara, Hui Miao, Lise Getoor, William W. Cohen:
Large-Scale Knowledge Graph Identification Using PSL. AAAI Fall Symposia 2013 - [c147]Dana Movshovitz-Attias, William W. Cohen:
Natural Language Models for Predicting Programming Comments. ACL (2) 2013: 35-40 - [c146]Nan Li, Yuandong Tian, William W. Cohen, Kenneth R. Koedinger:
Integrating Perceptual Learning with External World Knowledge in a Simulated Student. AIED 2013: 400-410 - [c145]Tuan-Anh Hoang, William W. Cohen, Ee-Peng Lim, Douglas Pierce, David P. Redlawsk:
Politics, sharing and emotion in microblogs. ASONAM 2013: 282-289 - [c144]Jay Pujara, Hui Miao, Lise Getoor, William W. Cohen:
Ontology-aware partitioning for knowledge graph identification. AKBC@CIKM 2013: 19-24 - [c143]Bhavana Dalvi, William W. Cohen, Jamie Callan:
Classifying entities into an incomplete ontology. AKBC@CIKM 2013: 31-36 - [c142]William Yang Wang, Kathryn Mazaitis, William W. Cohen:
Programming with personalized pagerank: a locally groundable first-order probabilistic logic. CIKM 2013: 2129-2138 - [c141]Nan Li, Eliane Stampfer, William W. Cohen, Kenneth R. Koedinger:
General and Efficient Cognitive Model Discovery Using a Simulated Student. CogSci 2013 - [c140]Nan Li, William W. Cohen, Kenneth R. Koedinger:
Discovering Student Models with a Clustering Algorithm Using Problem Content. EDM 2013: 98-105 - [c139]Mahesh Joshi, Mark Dredze, William W. Cohen, Carolyn P. Rosé:
What's in a Domain? Multi-Domain Learning for Multi-Attribute Data. HLT-NAACL 2013: 685-690 - [c138]Bhavana Bharat Dalvi, William W. Cohen, Jamie Callan:
Exploratory Learning. ECML/PKDD (3) 2013: 128-143 - [c137]Ramnath Balasubramanyan, Bhavana Bharat Dalvi, William W. Cohen:
From Topic Models to Semi-supervised Learning: Biasing Mixed-Membership Models to Exploit Topic-Indicative Features in Entity Clustering. ECML/PKDD (2) 2013: 628-642 - [c136]Ramnath Balasubramanyan, William W. Cohen:
Regularization of Latent Variable Models to Obtain Sparsity. SDM 2013: 414-422 - [c135]William W. Cohen, Bhavana Bharat Dalvi:
Very Fast Similarity Queries on Semi-Structured Data from the Web. SDM 2013: 512-520 - [c134]Jay Pujara, Hui Miao, Lise Getoor, William W. Cohen:
Knowledge Graph Identification. ISWC (1) 2013: 542-557 - [c133]Nan Li, Apoorv Khandelwal, Tung Phan, David S. Touretzky, William W. Cohen, Kenneth R. Koedinger:
Creating an educational robot by embedding a learning agent in the physical world (abstract only). SIGCSE 2013: 759-760 - [i10]William Yang Wang, Kathryn Mazaitis, William W. Cohen:
Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic. CoRR abs/1305.2254 (2013) - [i9]William W. Cohen, David P. Redlawsk, Douglas Pierce:
The Effect of Biased Communications On Both Trusting and Suspicious Voters. CoRR abs/1306.2558 (2013) - [i8]Bhavana Bharat Dalvi, William W. Cohen, Jamie Callan:
Exploratory Learning. CoRR abs/1307.0253 (2013) - [i7]Bhavana Bharat Dalvi, William W. Cohen, Jamie Callan:
WebSets: Extracting Sets of Entities from the Web Using Unsupervised Information Extraction. CoRR abs/1307.0261 (2013) - [i6]Partha Pratim Talukdar, William W. Cohen:
Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch. CoRR abs/1310.2959 (2013) - 2012
- [c132]Timothy W. Clark, William W. Cohen, Lawrence Hunter, Chris J. Lintott, Jude W. Shavlik:
Invited Talks. AAAI Fall Symposium: Discovery Informatics 2012 - [c131]Partha P. Talukdar, William W. Cohen:
Crowdsourced Comprehension: Predicting Prerequisite Structure in Wikipedia. BEA@NAACL-HLT 2012: 307-315 - [c130]Dana Movshovitz-Attias, William W. Cohen:
Bootstrapping Biomedical Ontologies for Scientific Text using NELL. BioNLP@HLT-NAACL 2012: 11-19 - [c129]Dana Movshovitz-Attias, William W. Cohen:
Alignment-HMM-based Extraction of Abbreviations from Biomedical Text. BioNLP@HLT-NAACL 2012: 47-55 - [c128]Ramnath Balasubramanyan, Kathryn Rivard, William W. Cohen, Jelena Jakovljevic, John L. Woolford:
Evaluating Joint Modeling of Yeast Biology Literature and Protein-Protein Interaction Networks. BioNLP@HLT-NAACL 2012: 155-162 - [c127]William W. Cohen:
Learning similarity measures based on random walks. CIKM 2012: 3 - [c126]Freddy Chong Tat Chua, William W. Cohen, Justin Betteridge, Ee-Peng Lim:
Community-based classification of noun phrases in twitter. CIKM 2012: 1702-1706 - [c125]Noboru Matsuda, Evelyn Yarzebinski, Victoria Keiser, Rohan Raizada, William W. Cohen, Gabriel Stylianides, Kenneth R. Koedinger:
Shallow learning as a pathway for successful learning both for tutors and tutees. CogSci 2012 - [c124]Noboru Matsuda, William W. Cohen, Kenneth R. Koedinger, Victoria Keiser, Rohan Raizada, Evelyn Yarzebinski, Shayna P. Watson, Gabriel Stylianides:
Studying the Effect of Tutor Learning Using a Teachable Agent that Asks the Student Tutor for Explanations. DIGITEL 2012: 25-32 - [c123]Nan Li, Abraham Schreiber, William W. Cohen, Kenneth R. Koedinger:
Creating Features from a Learned Grammar in a Simulated Student. ECAI 2012: 534-539 - [c122]Ni Lao, Amarnag Subramanya, Fernando C. N. Pereira, William W. Cohen:
Reading The Web with Learned Syntactic-Semantic Inference Rules. EMNLP-CoNLL 2012: 1017-1026 - [c121]Mahesh Joshi, Mark Dredze, William W. Cohen, Carolyn P. Rosé:
Multi-Domain Learning: When Do Domains Matter? EMNLP-CoNLL 2012: 1302-1312 - [c120]Nan Li, William W. Cohen, Kenneth R. Koedinger:
Integrating perceptual representation learning and skill learning in a simulated student. ICDL-EPIROB 2012: 1-2 - [c119]Frank Lin, William W. Cohen:
A General and Scalable Approach to Mixed Membership Clustering. ICDM 2012: 429-438 - [c118]Ramnath Balasubramanyan, William W. Cohen, Douglas Pierce, David P. Redlawsk:
Modeling Polarizing Topics: When Do Different Political Communities Respond Differently to the Same News? ICWSM 2012 - [c117]Nan Li, William W. Cohen, Kenneth R. Koedinger:
Problem Order Implications for Learning Transfer. ITS 2012: 185-194 - [c116]Nan Li, William W. Cohen, Kenneth R. Koedinger:
Efficient Cross-Domain Learning of Complex Skills. ITS 2012: 493-498 - [c115]Bhavana Dalvi, William W. Cohen, Jamie Callan:
Collectively Representing Semi-Structured Data from the Web. AKBC-WEKEX@NAACL-HLT 2012: 7-12 - [c114]Nan Li, William W. Cohen, Kenneth R. Koedinger:
Learning to Perceive Two-Dimensional Displays Using Probabilistic Grammars. ECML/PKDD (2) 2012: 773-788 - [c113]Einat Minkov, William W. Cohen:
Graph Based Similarity Measures for Synonym Extraction from Parsed Text. TextGraphs@ACL 2012: 20-24 - [c112]Bhavana Bharat Dalvi, William W. Cohen, Jamie Callan:
WebSets: extracting sets of entities from the web using unsupervised information extraction. WSDM 2012: 243-252 - [i5]Pradeep Ravikumar, William W. Cohen:
A Hierarchical Graphical Model for Record Linkage. CoRR abs/1207.4180 (2012) - 2011
- [c111]Noboru Matsuda, Evelyn Yarzebinski, Victoria Keiser, Rohan Raizada, Gabriel Stylianides, William W. Cohen, Kenneth R. Koedinger:
Learning by Teaching SimStudent - An Initial Classroom Baseline Study Comparing with Cognitive Tutor. AIED 2011: 213-221 - [c110]Noboru Matsuda, Victoria Keiser, Rohan Raizada, Gabriel Stylianides, William W. Cohen, Kenneth R. Koedinger:
Learning by Teaching SimStudent - Interactive Event. AIED 2011: 623 - [c109]Nan Li, William W. Cohen, Kenneth R. Koedinger, Noboru Matsuda:
A Machine Learning Approach for Automatic Student Model Discovery. EDM 2011: 31-40 - [c108]Jacob Eisenstein, Tae Yano, William W. Cohen, Noah A. Smith, Eric P. Xing:
Structured Databases of Named Entities from Bayesian Nonparametrics. ULNLP@EMNLP 2011: 2-12 - [c107]Ni Lao, Tom M. Mitchell, William W. Cohen:
Random Walk Inference and Learning in A Large Scale Knowledge Base. EMNLP 2011: 529-539 - [c106]Ramnath Balasubramanyan, William W. Cohen:
Block-LDA: Jointly modeling entity-annotated text and entity-entity links. SDM 2011: 450-461 - [i4]William W. Cohen, Robert E. Schapire, Yoram Singer:
Learning to Order Things. CoRR abs/1105.5464 (2011) - [i3]Chumki Basu, William W. Cohen, Haym Hirsh, Craig G. Nevill-Manning:
Technical Paper Recommendation: A Study in Combining Multiple Information Sources. CoRR abs/1106.0248 (2011) - 2010
- [j35]Ni Lao, William W. Cohen:
Relational retrieval using a combination of path-constrained random walks. Mach. Learn. 81(1): 53-67 (2010) - [j34]Einat Minkov, William W. Cohen:
Improving graph-walk-based similarity with reranking: Case studies for personal information management. ACM Trans. Inf. Syst. 29(1): 4:1-4:52 (2010) - [j33]Amr Ahmed, Andrew Arnold, Luís Pedro Coelho, Joshua D. Kangas, Abdul-Saboor Sheikh, Eric P. Xing, William W. Cohen, Robert F. Murphy:
Structured literature image finder: Parsing text and figures in biomedical literature. J. Web Semant. 8(2-3): 151-154 (2010) - [c105]Nan Li, William W. Cohen, Kenneth R. Koedinger:
Integrating Transfer Learning in Synthetic Student. AAAI 2010: 1943-1944 - [c104]Nan Li, Noboru Matsuda, William W. Cohen, Kenneth R. Koedinger:
Towards a Computational Model of Why Some Students Learn Faster than Others. AAAI Fall Symposium: Cognitive and Metacognitive Educational Systems 2010 - [c103]Frank Lin, William W. Cohen:
Semi-Supervised Classification of Network Data Using Very Few Labels. ASONAM 2010: 192-199 - [c102]Frank Lin, William W. Cohen:
A Very Fast Method for Clustering Big Text Datasets. ECAI 2010: 303-308 - [c101]Frank Lin, William W. Cohen:
Power Iteration Clustering. ICML 2010: 655-662 - [c100]Noboru Matsuda, Victoria Keiser, Rohan Raizada, Arthur Tu, Gabriel Stylianides, William W. Cohen, Kenneth R. Koedinger:
Learning by Teaching SimStudent: Technical Accomplishments and an Initial Use with Students. Intelligent Tutoring Systems (1) 2010: 317-326 - [c99]Nan Li, William W. Cohen, Kenneth R. Koedinger:
A Computational Model of Accelerated Future Learning through Feature Recognition. Intelligent Tutoring Systems (2) 2010: 368-370 - [c98]Noboru Matsuda, Victoria Keiser, Rohan Raizada, Gabriel Stylianides, William W. Cohen, Kenneth R. Koedinger:
Learning by Teaching SimStudent. Intelligent Tutoring Systems (2) 2010: 449 - [c97]Ni Lao, William W. Cohen:
Fast query execution for retrieval models based on path-constrained random walks. KDD 2010: 881-888 - [c96]Ni Lao, Jun Zhu, Xinwang Liu, Yandong Liu, William W. Cohen:
Efficient Relational Learning with Hidden Variable Detection. NIPS 2010: 1234-1242 - [c95]Philip Stutz, Abraham Bernstein, William W. Cohen:
Signal/Collect: Graph Algorithms for the (Semantic) Web. ISWC (1) 2010: 764-780 - [c94]Bhavana Bharat Dalvi, Jamie Callan, William W. Cohen:
Entity List Completion Using Set Expansion Techniques. TREC 2010 - [e4]William W. Cohen, Samuel Gosling:
Proceedings of the Fourth International Conference on Weblogs and Social Media, ICWSM 2010, Washington, DC, USA, May 23-26, 2010. The AAAI Press 2010 [contents]
2000 – 2009
- 2009
- [c93]Richard C. Wang, William W. Cohen:
Automatic Set Instance Extraction using the Web. ACL/IJCNLP 2009: 441-449 - [c92]Richard C. Wang, William W. Cohen:
Character-level Analysis of Semi-Structured Documents for Set Expansion. EMNLP 2009: 1503-1512 - [c91]Andrew Arnold, William W. Cohen:
Information Extraction as Link Prediction: Using Curated Citation Networks to Improve Gene Detection. ICWSM 2009 - [c90]Ramnath Balasubramanyan, Frank Lin, William W. Cohen, Matthew Hurst, Noah A. Smith:
From Episodes to Sagas: Understanding the News by Identifying Temporally Related Story Sequences. ICWSM 2009 - [c89]Amr Ahmed, Eric P. Xing, William W. Cohen, Robert F. Murphy:
Structured correspondence topic models for mining captioned figures in biological literature. KDD 2009: 39-48 - [c88]Tae Yano, William W. Cohen, Noah A. Smith:
Predicting Response to Political Blog Posts with Topic Models. HLT-NAACL 2009: 477-485 - [c87]Andrew Arnold, William W. Cohen:
Information Extraction as Link Prediction: Using Curated Citation Networks to Improve Gene Detection. WASA 2009: 541-550 - 2008
- [c86]Andrew O. Arnold, Ramesh Nallapati, William W. Cohen:
Exploiting Feature Hierarchy for Transfer Learning in Named Entity Recognition. ACL 2008: 245-253 - [c85]Einat Minkov, Ramnath Balasubramanyan, William W. Cohen:
Activity-centred Search in Email. CEAS 2008 - [c84]Andrew Arnold, William W. Cohen:
Intra-document structural frequency features for semi-supervised domain adaptation. CIKM 2008: 1291-1300 - [c83]Vitor R. Carvalho, Jonathan L. Elsas, William W. Cohen, Jaime G. Carbonell:
Suppressing outliers in pairwise preference ranking. CIKM 2008: 1487-1488 - [c82]Vitor R. Carvalho, William W. Cohen:
Ranking Users for Intelligent Message Addressing. ECIR 2008: 321-333 - [c81]Einat Minkov, William W. Cohen:
Learning Graph Walk Based Similarity Measures for Parsed Text. EMNLP 2008: 907-916 - [c80]Richard C. Wang, Nico Schlaefer, William W. Cohen, Eric Nyberg:
Automatic Set Expansion for List Question Answering. EMNLP 2008: 947-954 - [c79]Richard C. Wang, William W. Cohen:
Iterative Set Expansion of Named Entities Using the Web. ICDM 2008: 1091-1096 - [c78]Frank Lin, William W. Cohen:
The MultiRank Bootstrap Algorithm: Self-Supervised Political Blog Classification and Ranking Using Semi-Supervised Link Classification. ICWSM 2008 - [c77]Ramesh Nallapati, William W. Cohen:
Link-PLSA-LDA: A New Unsupervised Model for Topics and Influence of Blogs. ICWSM 2008 - [c76]Yi-Chia Wang, Mahesh Joshi, William W. Cohen, Carolyn P. Rosé:
Recovering Implicit Thread Structure in Newsgroup Style Conversations. ICWSM 2008 - [c75]Luís Pedro Coelho, Amr Ahmed, Andrew Arnold, Joshua D. Kangas, Abdul-Saboor Sheikh, Eric P. Xing, William W. Cohen, Robert F. Murphy:
Structured Literature Image Finder: Extracting Information from Text and Images in Biomedical Literature. BioLINK@ISMB/ECCB 2008: 23-32 - [c74]Noboru Matsuda, William W. Cohen, Jonathan Sewall, Gustavo Lacerda, Kenneth R. Koedinger:
Why Tutored Problem Solving May be Better Than Example Study: Theoretical Implications from a Simulated-Student Study. Intelligent Tutoring Systems 2008: 111-121 - [c73]Ramesh Nallapati, Amr Ahmed, Eric P. Xing, William W. Cohen:
Joint latent topic models for text and citations. KDD 2008: 542-550 - [e3]William W. Cohen, Andrew McCallum, Sam T. Roweis:
Machine Learning, Proceedings of the Twenty-Fifth International Conference (ICML 2008), Helsinki, Finland, June 5-9, 2008. ACM International Conference Proceeding Series 307, ACM 2008, ISBN 978-1-60558-205-4 [contents] - 2007
- [j32]Sarah Zelikovitz, William W. Cohen, Haym Hirsh:
Extending WHIRL with background knowledge for improved text classification. Inf. Retr. 10(1): 35-67 (2007) - [c72]Noboru Matsuda, William W. Cohen, Jonathan Sewall, Gustavo Lacerda, Kenneth R. Koedinger:
Predicting Students' Performance with SimStudent: Learning Cognitive Skills from Observation. AIED 2007: 467-476 - [c71]Vitor R. Carvalho, Wen Wu, William W. Cohen:
Discovering Leadership Roles in Email Workgroups. CEAS 2007 - [c70]Andrew O. Arnold, Ramesh Nallapati, William W. Cohen:
A Comparative Study of Methods for Transductive Transfer Learning. ICDM Workshops 2007: 77-82 - [c69]Richard C. Wang, William W. Cohen:
Language-Independent Set Expansion of Named Entities Using the Web. ICDM 2007: 342-350 - [c68]Ramesh Nallapati, Amr Ahmed, William W. Cohen, Eric P. Xing:
Sparse Word Graphs: A Scalable Algorithm for Capturing Word Correlations in Topic Models. ICDM Workshops 2007: 343-348 - [c67]Ramesh Nallapati, William W. Cohen, John D. Lafferty:
Parallelized Variational EM for Latent Dirichlet Allocation: An Experimental Evaluation of Speed and Scalability. ICDM Workshops 2007: 349-354 - [c66]William W. Cohen:
Machine Learning for Information Management: Some Promising Directions. ICMLA 2007 - [c65]Juchang Hua, Orhan N. Ayasli, William W. Cohen, Robert F. Murphy:
Identifying Fluorescence Microscope Images in Online Journal Articles Using Both Image and Text Features. ISBI 2007: 1224-1227 - [c64]Zhenzhen Kou, William W. Cohen, Robert F. Murphy:
A Stacked Graphical Model for Associating Sub-Images with Sub-Captions. Pacific Symposium on Biocomputing 2007: 257-268 - [c63]Vitor R. Carvalho, William W. Cohen:
Preventing Information Leaks in Email. SDM 2007: 68-77 - [c62]Zhenzhen Kou, William W. Cohen:
Stacked Graphical Models for Efficient Inference in Markov Random Fields. SDM 2007: 533-538 - [c61]Noboru Matsuda, William W. Cohen, Jonathan Sewall, Gustavo Lacerda, Kenneth R. Koedinger:
Evaluating a Simulated Student Using Real Students Data for Training and Testing. User Modeling 2007: 107-116 - 2006
- [j31]William W. Cohen, Einat Minkov:
A graph-search framework for associating gene identifiers with documents. BMC Bioinform. 7: 440 (2006) - [c60]Einat Minkov, William W. Cohen:
An Email and Meeting Assistant Using Graph Walks. CEAS 2006 - [c59]Vitor R. Carvalho, William W. Cohen:
Single-pass online learning: performance, voting schemes and online feature selection. KDD 2006: 548-553 - [c58]Einat Minkov, Richard C. Wang, Anthony Tomasic, William W. Cohen:
NER Systems that Suit User's Preferences: Adjusting the Recall-Precision Trade-off for Entity Extraction. HLT-NAACL 2006 - [c57]Einat Minkov, William W. Cohen, Andrew Y. Ng:
Contextual search and name disambiguation in email using graphs. SIGIR 2006: 27-34 - [e2]William W. Cohen, Andrew W. Moore:
Machine Learning, Proceedings of the Twenty-Third International Conference (ICML 2006), Pittsburgh, Pennsylvania, USA, June 25-29, 2006. ACM International Conference Proceeding Series 148, ACM 2006, ISBN 1-59593-383-2 [contents] - 2005
- [c56]Carolyn Penstein Rosé, Pinar Donmez, Gahgene Gweon, Andrea Knight, Brian Junker, William W. Cohen, Kenneth R. Koedinger, Neil T. Heffernan:
Automatic and Semi-Automatic Skill Coding With a View Towards Supporting On-Line Assessment. AIED 2005: 571-578 - [c55]William W. Cohen, Vitor Rocha de Carvalho:
Stacked Sequential Learning. IJCAI 2005: 671-676 - [c54]William W. Cohen, Einat Minkov, Anthony Tomasic:
Learning to Understand Web Site Update Requests. IJCAI 2005: 1028-1033 - [c53]Zhenzhen Kou, William W. Cohen, Robert F. Murphy:
High-recall protein entity recognition using a dictionary. ISMB (Supplement of Bioinformatics) 2005: 266-273 - [c52]Einat Minkov, Richard C. Wang, William W. Cohen:
Extracting Personal Names from Email: Applying Named Entity Recognition to Informal Text. HLT/EMNLP 2005: 443-450 - [c51]Vitor Rocha de Carvalho, William W. Cohen:
On the collective classification of email "speech acts". SIGIR 2005: 345-352 - 2004
- [c50]Vitor Rocha de Carvalho, William W. Cohen:
Learning to Extract Signature and Reply Lines from Email. CEAS 2004 - [c49]Yifen Huang, Dinesh Govindaraju, Tom M. Mitchell, Vitor Rocha de Carvalho, William W. Cohen:
Inferring Ongoing Activities of Workstation Users by Clustering Email. CEAS 2004 - [c48]William W. Cohen, Vitor R. Carvalho, Tom M. Mitchell:
Learning to Classify Email into "Speech Acts". EMNLP 2004: 309-316 - [c47]William W. Cohen, Sunita Sarawagi:
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods. KDD 2004: 89-98 - [c46]Sunita Sarawagi, William W. Cohen:
Semi-Markov Conditional Random Fields for Information Extraction. NIPS 2004: 1185-1192 - [c45]Pradeep Ravikumar, William W. Cohen:
A Hierarchical Graphical Model for Record Linkage. UAI 2004: 454-461 - 2003
- [j30]William W. Cohen:
Learning and Discovering Structure in Web Pages. IEEE Data Eng. Bull. 26(3): 3-10 (2003) - [j29]Mikhail Bilenko, Raymond J. Mooney, William W. Cohen, Pradeep Ravikumar, Stephen E. Fienberg:
Adaptive Name Matching in Information Integration. IEEE Intell. Syst. 18(5): 16-23 (2003) - [c44]William W. Cohen:
Infrastructure Components for Large-Scale Information Extraction Systems. IAAI 2003: 71-78 - [c43]William W. Cohen, Pradeep Ravikumar, Stephen E. Fienberg:
A Comparison of String Distance Metrics for Name-Matching Tasks. IIWeb 2003: 73-78 - [c42]Zhenzhen Kou, William W. Cohen, Robert F. Murphy:
Extracting information from text and images for location proteomics. BIOKDD 2003: 2-9 - [c41]William W. Cohen, Richard C. Wang, Robert F. Murphy:
Understanding captions in biomedical publications. KDD 2003: 499-504 - [c40]ChengXiang Zhai, William W. Cohen, John D. Lafferty:
Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. SIGIR 2003: 10-17 - [p1]William W. Cohen, Matthew Hurst, Lee S. Jensen:
A Wrapper Induction System for Complex Documents, and its Application to Tabular Data on the Web. Web Document Analysis 2003: 155-177 - 2002
- [c39]William W. Cohen, Jacob Richman:
Learning to match and cluster large high-dimensional data sets for data integration. KDD 2002: 475-480 - [c38]William W. Cohen:
Improving a Page Classifier with Anchor Extraction and Link Analysis. NIPS 2002: 1481-1488 - [c37]William W. Cohen, Matthew Hurst, Lee S. Jensen:
A flexible learning system for wrapping tables and lists in HTML documents. WWW 2002: 232-241 - 2001
- [j28]Chumki Basu, Haym Hirsh, William W. Cohen, Craig G. Nevill-Manning:
Technical Paper Recommendation: A Study in Combining Multiple Information Sources. J. Artif. Intell. Res. 14: 231-252 (2001) - [c36]William W. Cohen:
Issues in Extracting Information from the Web. IWPT 2001 - 2000
- [j27]William W. Cohen:
WHIRL: A word-based information representation language. Artif. Intell. 118(1-2): 163-196 (2000) - [j26]William W. Cohen, Wei Fan:
Web-collaborative filtering: recommending music by crawling the Web. Comput. Networks 33(1-6): 685-698 (2000) - [j25]William W. Cohen, Andrew McCallum, Dallan Quass:
Learning to Understand the Web. IEEE Data Eng. Bull. 23(3): 17-24 (2000) - [j24]Jaime G. Carbonell, Yiming Yang, William W. Cohen:
Special Issue of Machine Learning on Information Retrieval - Introduction. Mach. Learn. 39(2/3): 99-101 (2000) - [j23]William W. Cohen:
Data integration using similarity joins and a word-based information representation language. ACM Trans. Inf. Syst. 18(3): 288-321 (2000) - [c35]William W. Cohen:
Extracting Information from the Web for Concept Learning and Collaborative Filtering. ALT 2000: 1-12 - [c34]William W. Cohen:
Automatically Extracting Features for Concept Learning from the Web. ICML 2000: 159-166 - [c33]William W. Cohen, Henry A. Kautz, David A. McAllester:
Hardening soft information sources. KDD 2000: 255-259
1990 – 1999
- 1999
- [j22]William W. Cohen:
Reasoning about Textual Similarity in a Web-Based Information Access System. Auton. Agents Multi Agent Syst. 2(1): 65-86 (1999) - [j21]William W. Cohen, Wei Fan:
Learning Page-Independent Heuristics for Extracting Data from Web Pages. Comput. Networks 31(11-16): 1641-1652 (1999) - [j20]William W. Cohen, Premkumar T. Devanbu:
Automatically Exploring Hypotheses About Fault Prediction: A Comparative Study of Inductive Logic Programming Methods. Int. J. Softw. Eng. Knowl. Eng. 9(5): 519-546 (1999) - [j19]William W. Cohen, Robert E. Schapire, Yoram Singer:
Learning to Order Things. J. Artif. Intell. Res. 10: 243-270 (1999) - [j18]William W. Cohen, Yoram Singer:
Context-Sensitive Learning Methods for Text Categorization. ACM Trans. Inf. Syst. 17(2): 141-173 (1999) - [c32]William W. Cohen:
Recognizing Structure in Web Pages using Similarity Queries. AAAI/IAAI 1999: 59-66 - [c31]William W. Cohen, Yoram Singer:
A Simple, Fast, and Effictive Rule Learner. AAAI/IAAI 1999: 335-342 - [c30]William W. Cohen:
A Demonstration of WHIRL (demonstration abstract). SIGIR 1999: 327 - [c29]William W. Cohen:
Some Practical Observations on Integration of Web Information. WebDB (Informal Proceedings) 1999: 55-60 - 1998
- [j17]Narendar Yalamanchilli, William W. Cohen:
Communication Performance of Java-Based Parallel Virtual Machines. Concurr. Pract. Exp. 10(11-13): 1189-1196 (1998) - [j16]William W. Cohen:
Hardness Results for Learning First-Order Representations and Programming by Demonstration. Mach. Learn. 30(1): 57-87 (1998) - [c28]Chumki Basu, Haym Hirsh, William W. Cohen:
Recommendation as Classification: Using Social and Content-Based Information in Recommendation. AAAI/IAAI 1998: 714-720 - [c27]William W. Cohen:
A Web-Based Information System that Reasons with Structured Collections of Text. Agents 1998: 400-407 - [c26]William W. Cohen, Haym Hirsh:
Joins that Generalize: Text Classification Using WHIRL. KDD 1998: 169-173 - [c25]William W. Cohen:
Integration of Heterogeneous Databases Without Common Domains Using Queries Based on Textual Similarity. SIGMOD Conference 1998: 201-212 - [c24]William W. Cohen:
Providing Database-like Access to the Web Using Queries Based on Textual Similarity. SIGMOD Conference 1998: 558-560 - 1997
- [c23]William W. Cohen, Daniel Kudenko:
Transferring and Retraining Learned Information Filters. AAAI/IAAI 1997: 583-590 - [c22]William W. Cohen, Premkumar T. Devanbu:
A Comparative Study of Inductive Logic Programming Methods for Software Fault Prediction. ICML 1997: 66-74 - [c21]William W. Cohen, Robert E. Schapire, Yoram Singer:
Learning to Order Things. NIPS 1997: 451-457 - 1996
- [j15]William W. Cohen:
Adaptive mapping and navigation by teams of simple robots. Robotics Auton. Syst. 18(4): 411-434 (1996) - [c20]William W. Cohen:
Learning Trees and Rules with Set-Valued Features. AAAI/IAAI, Vol. 1 1996: 709-716 - [c19]William W. Cohen:
The Dual DFA Learning Problem: Hardness Results for Programming by Demonstration and Learning First-Order Representations (Extended Abstract). COLT 1996: 29-40 - [c18]William W. Cohen, Yoram Singer:
Context-sensitive Learning Methods for Text Categorization. SIGIR 1996: 307-315 - 1995
- [j14]William W. Cohen:
Pac-Learning Non-Recursive Prolog Clauses. Artif. Intell. 79(1): 1-38 (1995) - [j13]William W. Cohen:
Inductive Specification Recovery: Understanding Software by Learning from Example Behaviors. Autom. Softw. Eng. 2(2): 107-129 (1995) - [j12]William W. Cohen:
Pac-Learning Recursive Logic Programs: Efficient Algorithms. J. Artif. Intell. Res. 2: 501-539 (1995) - [j11]William W. Cohen:
Pac-learning Recursive Logic Programs: Negative Results. J. Artif. Intell. Res. 2: 541-573 (1995) - [j10]William W. Cohen, C. David Page Jr.:
Polynomial Learnability and Inductive Logic Programming: Methods and Results. New Gener. Comput. 13(3&4): 369-409 (1995) - [c17]William W. Cohen, Haym Hirsh:
Corrigendum for "Learnability of Description Logics". COLT 1995: 463 - [c16]William W. Cohen:
Fast Effective Rule Induction. ICML 1995: 115-123 - [c15]William W. Cohen:
Text Categorization and Relational Learning. ICML 1995: 124-132 - [i2]William W. Cohen:
Pac-Learning Recursive Logic Programs: Efficient Algorithms. CoRR cs.AI/9505104 (1995) - [i1]William W. Cohen:
Pac-learning Recursive Logic Programs: Negative Results. CoRR cs.AI/9505105 (1995) - 1994
- [j9]William W. Cohen:
Grammatically Biased Learning: Learning Logic Programs Using an Explicit Antecedent Description Language. Artif. Intell. 68(2): 303-366 (1994) - [j8]William W. Cohen:
Incremental Abductive EBL. Mach. Learn. 15(1): 5-24 (1994) - [j7]William W. Cohen, Haym Hirsh:
The Learnability of Description Logics with Equality Constraints. Mach. Learn. 17(2-3): 169-199 (1994) - [j6]L. Thorne McCarty, William W. Cohen:
The Case for Explicit Exceptions. Methods Log. Comput. Sci. 1(1): 19-50 (1994) - [c14]William W. Cohen:
Recovering Software Specifications with Inductive Logic Programming. AAAI 1994: 142-148 - [c13]William W. Cohen:
Pac-Learning Nondeterminate Clauses. AAAI 1994: 676-681 - [c12]William W. Cohen, Haym Hirsh:
Learning the Classic Description Logic: Theoretical and Experimental Results. KR 1994: 121-133 - [e1]William W. Cohen, Haym Hirsh:
Machine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994. Morgan Kaufmann 1994, ISBN 1-55860-335-2 [contents] - 1993
- [j5]William W. Cohen:
Creating a Memory of Casual Relationships (Book Review). Mach. Learn. 10: 179-183 (1993) - [c11]William W. Cohen:
Cryptographic Limitations on Learning One-Clause Logic Programs. AAAI 1993: 80-85 - [c10]William W. Cohen:
Pac-Learning a Restricted Class of Recursive Logic Programs. AAAI 1993: 86-92 - [c9]William W. Cohen:
Efficient Pruning Methods for Separate-and-Conquer Rule Learning Systems. IJCAI 1993: 988-994 - 1992
- [j4]William W. Cohen:
Using Distribution-Free Learning Theory to Analyze Solution Path Caching Mechan isms. Comput. Intell. 8: 336-375 (1992) - [j3]William W. Cohen:
Abductive Explanation-Based Learning: A Solution to the Multiple Inconsistent Explanation Problem. Mach. Learn. 8: 167-219 (1992) - [c8]William W. Cohen, Alexander Borgida, Haym Hirsh:
Computing Least Common Subsumers in Description Logics. AAAI 1992: 754-760 - [c7]William W. Cohen:
Desiderata for Generalization-to-N Algorithms. AII 1992: 140-150 - [c6]William W. Cohen, Haym Hirsh:
Learnability of Description Logics. COLT 1992: 116-127 - 1991
- [c5]William W. Cohen:
The Generality of Overgenerality. ML 1991: 490-494 - 1990
- [c4]William W. Cohen:
Learning from Textbook Knowledge: A Case Study. AAAI 1990: 743-748 - [c3]William W. Cohen:
An Analysis of Representation Shift in Concept Learning. ML 1990: 104-112 - [c2]William W. Cohen:
Learning Approximate Control Rules of High Utility. ML 1990: 268-276
1980 – 1989
- 1988
- [c1]William W. Cohen:
Generalizing Number and Learning from Multiple Examples in Explanation Based Learning. ML 1988: 256-269 - 1986
- [j2]Karen A. Bartlett, William W. Cohen, Aart J. de Geus, Gary D. Hachtel:
Synthesis and Optimization of Multilevel Logic under Timing Constraints. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 5(4): 582-596 (1986) - 1985
- [j1]Aart J. de Geus, William W. Cohen:
A Rule-Based System for Optimizing Combinational Logic. IEEE Des. Test 2(4): 22-32 (1985)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
[+][–] Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
[+][–] Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-05-03 01:09 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
