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ORCIDTushar Khot
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- affiliation: AI2, Allen Institute for Artificial Intelligence, Seattle, US
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2020 – today
- 2023
[c57]Nikil Roashan Selvam, Sunipa Dev, Daniel Khashabi, Tushar Khot, Kai-Wei Chang:
The Tail Wagging the Dog: Dataset Construction Biases of Social Bias Benchmarks. ACL (2) 2023: 1373-1386- [c56]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions. ACL (1) 2023: 10014-10037 - [c55]Yao Fu, Hao Peng, Ashish Sabharwal, Peter Clark, Tushar Khot:
Complexity-Based Prompting for Multi-step Reasoning. ICLR 2023 - [c54]Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal:
Decomposed Prompting: A Modular Approach for Solving Complex Tasks. ICLR 2023 - [c53]Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, Tushar Khot:
Specializing Smaller Language Models towards Multi-Step Reasoning. ICML 2023: 10421-10430 - [i44]Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, Tushar Khot:
Specializing Smaller Language Models towards Multi-Step Reasoning. CoRR abs/2301.12726 (2023) - [i43]Yao Fu, Hao Peng, Tushar Khot, Mirella Lapata:
Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback. CoRR abs/2305.10142 (2023) - [i42]Yao Fu, Litu Ou, Mingyu Chen, Yuhao Wan, Hao Peng, Tushar Khot:
Chain-of-Thought Hub: A Continuous Effort to Measure Large Language Models' Reasoning Performance. CoRR abs/2305.17306 (2023) - [i41]Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Raghavi Chandu, David Wadden, Kelsey MacMillan, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi:
How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources. CoRR abs/2306.04751 (2023) - [i40]Carl Edwards, Aakanksha Naik, Tushar Khot, Martin Burke, Heng Ji, Tom Hope:
SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design. CoRR abs/2307.11694 (2023) - [i39]Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande, Ashwin Kalyan, Peter Clark, Ashish Sabharwal, Tushar Khot:
Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs. CoRR abs/2311.04892 (2023) - [i38]Archiki Prasad, Alexander Koller, Mareike Hartmann, Peter Clark, Ashish Sabharwal, Mohit Bansal, Tushar Khot:
ADaPT: As-Needed Decomposition and Planning with Language Models. CoRR abs/2311.05772 (2023) - 2022
- [j8]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
♫ MuSiQue: Multihop Questions via Single-hop Question Composition. Trans. Assoc. Comput. Linguistics 10: 539-554 (2022) - [c52]Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal:
Hey AI, Can You Solve Complex Tasks by Talking to Agents? ACL (Findings) 2022: 1808-1823 - [c51]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts. EMNLP 2022: 6541-6566 - [c50]Daniel Khashabi, Xinxi Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Sameer Singh, Yejin Choi:
Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts. NAACL-HLT 2022: 3631-3643 - [i37]Zhengzhong Liang, Tushar Khot, Steven Bethard, Mihai Surdeanu, Ashish Sabharwal:
Better Retrieval May Not Lead to Better Question Answering. CoRR abs/2205.03685 (2022) - [i36]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Teaching Broad Reasoning Skills via Decomposition-Guided Contexts. CoRR abs/2205.12496 (2022) - [i35]Yao Fu, Hao Peng, Ashish Sabharwal, Peter Clark, Tushar Khot:
Complexity-Based Prompting for Multi-Step Reasoning. CoRR abs/2210.00720 (2022) - [i34]Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal:
Decomposed Prompting: A Modular Approach for Solving Complex Tasks. CoRR abs/2210.02406 (2022) - [i33]Nikil Roashan Selvam, Sunipa Dev, Daniel Khashabi, Tushar Khot, Kai-Wei Chang:
The Tail Wagging the Dog: Dataset Construction Biases of Social Bias Benchmarks. CoRR abs/2210.10040 (2022) - [i32]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions. CoRR abs/2212.10509 (2022) - 2021
- [j7]Nandini Ramanan
, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure learning for relational logistic regression: an ensemble approach. Data Min. Knowl. Discov. 35(5): 2089-2111 (2021) - [j6]Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, Jonathan Berant:
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies. Trans. Assoc. Comput. Linguistics 9: 346-361 (2021) - [c49]Jieyu Zhao, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Kai-Wei Chang:
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? ACL/IJCNLP (Findings) 2021: 4158-4164 - [c48]Shih-Ting Lin, Ashish Sabharwal, Tushar Khot:
ReadOnce Transformers: Reusable Representations of Text for Transformers. ACL/IJCNLP (1) 2021: 7129-7141 - [c47]Daniel Khashabi, Amos Ng, Tushar Khot, Ashish Sabharwal, Hannaneh Hajishirzi, Chris Callison-Burch:
GooAQ: Open Question Answering with Diverse Answer Types. EMNLP (Findings) 2021: 421-433 - [c46]Tushar Khot, Daniel Khashabi, Kyle Richardson, Peter Clark, Ashish Sabharwal:
Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models. NAACL-HLT 2021: 1264-1279 - [c45]Ben Zhou, Kyle Richardson, Qiang Ning, Tushar Khot, Ashish Sabharwal, Dan Roth:
Temporal Reasoning on Implicit Events from Distant Supervision. NAACL-HLT 2021: 1361-1371 - [i31]Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, Jonathan Berant:
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies. CoRR abs/2101.02235 (2021) - [i30]Sumithra Bhakthavatsalam, Daniel Khashabi, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Peter Clark:
Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge. CoRR abs/2102.03315 (2021) - [i29]Daniel Khashabi, Amos Ng, Tushar Khot, Ashish Sabharwal, Hannaneh Hajishirzi, Chris Callison-Burch:
GooAQ: Open Question Answering with Diverse Answer Types. CoRR abs/2104.08727 (2021) - [i28]Jieyu Zhao, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Kai-Wei Chang:
Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? CoRR abs/2106.01465 (2021) - [i27]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
MuSiQue: Multi-hop Questions via Single-hop Question Composition. CoRR abs/2108.00573 (2021) - [i26]Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal:
Learning to Solve Complex Tasks by Talking to Agents. CoRR abs/2110.08542 (2021) - [i25]Daniel Khashabi, Shane Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sameer Singh, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Yejin Choi:
PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts. CoRR abs/2112.08348 (2021) - 2020
- [j5]Peter Clark, Oren Etzioni, Tushar Khot, Daniel Khashabi, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, Sumithra Bhakthavatsalam, Dirk Groeneveld, Michal Guerquin, Michael Schmitz:
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project. AI Mag. 41(4): 39-53 (2020) - [c44]Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, Ashish Sabharwal:
QASC: A Dataset for Question Answering via Sentence Composition. AAAI 2020: 8082-8090 - [c43]Daniel Khashabi, Tushar Khot, Ashish Sabharwal:
More Bang for Your Buck: Natural Perturbation for Robust Question Answering. EMNLP (1) 2020: 163-170 - [c42]James Ferguson, Matt Gardner, Hannaneh Hajishirzi, Tushar Khot, Pradeep Dasigi:
IIRC: A Dataset of Incomplete Information Reading Comprehension Questions. EMNLP (1) 2020: 1137-1147 - [c41]Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, Hannaneh Hajishirzi:
UnifiedQA: Crossing Format Boundaries With a Single QA System. EMNLP (Findings) 2020: 1896-1907 - [c40]Tao Li, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Vivek Srikumar:
UNQOVERing Stereotypical Biases via Underspecified Questions. EMNLP (Findings) 2020: 3475-3489 - [c39]Dirk Groeneveld, Tushar Khot, Mausam, Ashish Sabharwal:
A Simple Yet Strong Pipeline for HotpotQA. EMNLP (1) 2020: 8839-8845 - [c38]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning. EMNLP (1) 2020: 8846-8863 - [i24]Daniel Khashabi, Tushar Khot, Ashish Sabharwal:
Natural Perturbation for Robust Question Answering. CoRR abs/2004.04849 (2020) - [i23]Dirk Groeneveld, Tushar Khot, Mausam, Ashish Sabharwal:
A Simple Yet Strong Pipeline for HotpotQA. CoRR abs/2004.06753 (2020) - [i22]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, Hannaneh Hajishirzi:
UnifiedQA: Crossing Format Boundaries With a Single QA System. CoRR abs/2005.00700 (2020) - [i21]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Measuring and Reducing Non-Multifact Reasoning in Multi-hop Question Answering. CoRR abs/2005.00789 (2020) - [i20]Tushar Khot, Daniel Khashabi, Kyle Richardson, Peter Clark, Ashish Sabharwal:
Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models. CoRR abs/2009.00751 (2020) - [i19]Tao Li, Tushar Khot, Daniel Khashabi, Ashish Sabharwal, Vivek Srikumar:
UnQovering Stereotyping Biases via Underspecified Questions. CoRR abs/2010.02428 (2020) - [i18]Ben Zhou, Kyle Richardson, Qiang Ning, Tushar Khot, Ashish Sabharwal, Dan Roth:
Temporal Reasoning on Implicit Events from Distant Supervision. CoRR abs/2010.12753 (2020) - [i17]Shih-Ting Lin, Ashish Sabharwal, Tushar Khot:
ReadOnce Transformers: Reusable Representations of Text for Transformers. CoRR abs/2010.12854 (2020) - [i16]James Ferguson, Matt Gardner, Hannaneh Hajishirzi, Tushar Khot, Pradeep Dasigi:
IIRC: A Dataset of Incomplete Information Reading Comprehension Questions. CoRR abs/2011.07127 (2020)
2010 – 2019
- 2019
- [c37]Souvik Kundu, Tushar Khot, Ashish Sabharwal, Peter Clark:
Exploiting Explicit Paths for Multi-hop Reading Comprehension. ACL (1) 2019: 2737-2747 - [c36]Tushar Khot, Ashish Sabharwal, Peter Clark:
What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering. EMNLP/IJCNLP (1) 2019: 2814-2828 - [c35]Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, Niranjan Balasubramanian:
Repurposing Entailment for Multi-Hop Question Answering Tasks. NAACL-HLT (1) 2019: 2948-2958 - [i15]Daniel Khashabi, Erfan Sadeqi Azer, Tushar Khot, Ashish Sabharwal, Dan Roth:
On the Capabilities and Limitations of Reasoning for Natural Language Understanding. CoRR abs/1901.02522 (2019) - [i14]Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, Niranjan Balasubramanian:
Repurposing Entailment for Multi-Hop Question Answering Tasks. CoRR abs/1904.09380 (2019) - [i13]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth:
Question Answering as Global Reasoning over Semantic Abstractions. CoRR abs/1906.03672 (2019) - [i12]Peter Clark, Oren Etzioni, Daniel Khashabi, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, Sumithra Bhakthavatsalam, Dirk Groeneveld, Michal Guerquin, Michael Schmitz:
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project. CoRR abs/1909.01958 (2019) - [i11]Tushar Khot, Ashish Sabharwal, Peter Clark:
What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering. CoRR abs/1909.09253 (2019) - [i10]Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, Ashish Sabharwal:
QASC: A Dataset for Question Answering via Sentence Composition. CoRR abs/1910.11473 (2019) - 2018
- [c34]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth:
Question Answering as Global Reasoning Over Semantic Abstractions. AAAI 2018: 1905-1914 - [c33]Tushar Khot, Ashish Sabharwal, Peter Clark:
SciTaiL: A Textual Entailment Dataset from Science Question Answering. AAAI 2018: 5189-5197 - [c32]Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Eduard H. Hovy:
AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples. ACL (1) 2018: 2418-2428 - [c31]Todor Mihaylov, Peter Clark, Tushar Khot, Ashish Sabharwal:
Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering. EMNLP 2018: 2381-2391 - [c30]Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Peter Clark:
Bridging Knowledge Gaps in Neural Entailment via Symbolic Models. EMNLP 2018: 4940-4945 - [c29]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure Learning for Relational Logistic Regression: An Ensemble Approach. KR 2018: 661-662 - [i9]Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord:
Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge. CoRR abs/1803.05457 (2018) - [i8]Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Eduard H. Hovy:
AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples. CoRR abs/1805.04680 (2018) - [i7]Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan:
Structure Learning for Relational Logistic Regression: An Ensemble Approach. CoRR abs/1808.02123 (2018) - [i6]Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Peter Clark:
Bridging Knowledge Gaps in Neural Entailment via Symbolic Models. CoRR abs/1808.09333 (2018) - [i5]Todor Mihaylov, Peter Clark, Tushar Khot, Ashish Sabharwal:
Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering. CoRR abs/1809.02789 (2018) - [i4]Souvik Kundu, Tushar Khot, Ashish Sabharwal:
Exploiting Explicit Paths for Multi-hop Reading Comprehension. CoRR abs/1811.01127 (2018) - 2017
- [j4]Sriraam Natarajan, Vishal Bangera, Tushar Khot, Jose Picado, Anurag Wazalwar, Vítor Santos Costa, David Page, Michael Caldwell:
Markov logic networks for adverse drug event extraction from text. Knowl. Inf. Syst. 51(2): 435-457 (2017) - [c28]Tushar Khot, Ashish Sabharwal, Peter Clark:
Answering Complex Questions Using Open Information Extraction. ACL (2) 2017: 311-316 - [c27]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth:
Learning What is Essential in Questions. CoNLL 2017: 80-89 - [c26]Navdeep Kaur, Gautam Kunapuli, Tushar Khot, Kristian Kersting, William Cohen, Sriraam Natarajan:
Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach. ILP 2017: 94-111 - [i3]Tushar Khot, Ashish Sabharwal, Peter Clark:
Answering Complex Questions Using Open Information Extraction. CoRR abs/1704.05572 (2017) - 2016
- [c25]Shuo Yang, Tushar Khot, Kristian Kersting, Sriraam Natarajan:
Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach. AAAI 2016: 2265-2271 - [c24]Peter Clark, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter D. Turney, Daniel Khashabi:
Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions. AAAI 2016: 2580-2586 - [c23]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, Dan Roth:
Question Answering via Integer Programming over Semi-Structured Knowledge. IJCAI 2016: 1145-1152 - [c22]Marcin Malec, Tushar Khot, James G. Nagy, Erik Blask, Sriraam Natarajan:
Inductive Logic Programming Meets Relational Databases: Efficient Learning of Markov Logic Networks. ILP 2016: 14-26 - [c21]Mayukh Das, Yuqing Wu, Tushar Khot, Kristian Kersting, Sriraam Natarajan:
Scaling Lifted Probabilistic Inference and Learning Via Graph Databases. SDM 2016: 738-746 - [i2]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, Dan Roth:
Question Answering via Integer Programming over Semi-Structured Knowledge. CoRR abs/1604.06076 (2016) - 2015
- [j3]Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik:
Gradient-based boosting for statistical relational learning: the Markov logic network and missing data cases. Mach. Learn. 100(1): 75-100 (2015) - [c20]Phillip Odom, Tushar Khot, Reid B. Porter, Sriraam Natarajan:
Knowledge-Based Probabilistic Logic Learning. AAAI 2015: 3564-3570 - [c19]Phillip Odom, Tushar Khot, Sriraam Natarajan:
Learning Probabilistic Logic Models with Human Advice. AAAI Spring Symposia 2015 - [c18]Phillip Odom, Vishal Bangera, Tushar Khot, David Page, Sriraam Natarajan:
Extracting Adverse Drug Events from Text Using Human Advice. AIME 2015: 195-204 - [c17]Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni:
Exploring Markov Logic Networks for Question Answering. EMNLP 2015: 685-694 - [c16]Raksha Kumaraswamy, Anurag Wazalwar, Tushar Khot, Jude W. Shavlik, Sriraam Natarajan:
Anomaly Detection in Text: The Value of Domain Knowledge. FLAIRS 2015: 225-228 - [i1]Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni:
Markov Logic Networks for Natural Language Question Answering. CoRR abs/1507.03045 (2015) - 2014
- [b1]Sriraam Natarajan, Kristian Kersting, Tushar Khot, Jude W. Shavlik:
Boosted Statistical Relational Learners - From Benchmarks to Data-Driven Medicine. Springer Briefs in Computer Science, Springer 2014, ISBN 978-3-319-13643-1, pp. 1-68 - [j2]Sriraam Natarajan, Baidya Nath Saha, Saket Joshi, Adam Edwards, Tushar Khot, Elizabeth M. Davenport, Kristian Kersting, Christopher T. Whitlow, Joseph A. Maldjian:
Relational learning helps in three-way classification of Alzheimer patients from structural magnetic resonance images of the brain. Int. J. Mach. Learn. Cybern. 5(5): 659-669 (2014) - [c15]Tushar Khot, Sriraam Natarajan, Jude W. Shavlik:
Relational One-Class Classification: A Non-Parametric Approach. AAAI 2014: 2453-2459 - [c14]Tushar Khot, Sriraam Natarajan, Jude W. Shavlik:
Classification from One Class of Examples for Relational Domains. StarAI@AAAI 2014 - [c13]Shuo Yang, Tushar Khot, Kristian Kersting, Gautam Kunapuli, Kris Hauser, Sriraam Natarajan:
Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach. ICDM 2014: 1085-1090 - [c12]Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Ré, Jude W. Shavlik:
Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge. ILP 2014: 92-107 - [c11]Arti Shivram, Tushar Khot, Sriraam Natarajan, Venu Govindaraju:
Statistical Relational Learning for Handwriting Recognition. ILP 2014: 126-138 - 2013
- [c10]Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher Ré, Jude W. Shavlik:
Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text. StarAI@AAAI 2013 - [c9]Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli:
Accelerating Imitation Learning in Relational Domains via Transfer by Initialization. ILP 2013: 64-75 - [c8]Tushar Khot, Ce Zhang, Jude W. Shavlik, Sriraam Natarajan, Christopher Ré:
Bootstrapping Knowledge Base Acceleration. TREC 2013 - 2012
- [j1]Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann, Jude W. Shavlik:
Gradient-based boosting for statistical relational learning: The relational dependency network case. Mach. Learn. 86(1): 25-56 (2012) - [c7]Sriraam Natarajan, Saket Joshi, Baidya Nath Saha, Adam Edwards, Tushar Khot, Elizabeth Moody, Kristian Kersting, Christopher T. Whitlow, Joseph A. Maldjian:
A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain. ICMLA (1) 2012: 203-208 - [c6]Tushar Khot, Siddharth Srivastava, Sriraam Natarajan, Jude W. Shavlik:
Learning Relational Structure for Temporal Relation Extraction. StarAI@UAI 2012 - [c5]Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli:
Accelarating Imitation Learning in Relational Domains via Transfer by Initialization. StarAI@UAI 2012 - 2011
- [c4]Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik:
Learning Markov Logic Networks via Functional Gradient Boosting. ICDM 2011: 320-329 - 2010
- [c3]Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik:
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. StarAI@AAAI 2010 - [c2]Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik:
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. ECML/PKDD (2) 2010: 434-450
2000 – 2009
- 2009
- [c1]Xiaojin Zhu, Andrew B. Goldberg, Tushar Khot:
Some new directions in graph-based semi-supervised learning. ICME 2009: 1504-1507
Coauthor Index