Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDAshish Sabharwal
Person information
- affiliation: AI2, Allen Institute for Artificial Intelligence, Seattle, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2021
[i44]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)- [i43]Jialin Wu, Jiasen Lu, Ashish Sabharwal, Roozbeh Mottaghi:
Multi-Modal Answer Validation for Knowledge-Based VQA. CoRR abs/2103.12248 (2021) - [i42]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) - 2020
- [j16]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) - [j15]Kyle Richardson, Ashish Sabharwal:
What Does My QA Model Know? Devising Controlled Probes using Expert. Trans. Assoc. Comput. Linguistics 8: 572-588 (2020) - [c100]Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, Ashish Sabharwal:
QASC: A Dataset for Question Answering via Sentence Composition. AAAI 2020: 8082-8090 - [c99]Kyle Richardson, Hai Hu, Lawrence S. Moss, Ashish Sabharwal:
Probing Natural Language Inference Models through Semantic Fragments. AAAI 2020: 8713-8721 - [c98]Erfan Sadeqi Azer, Daniel Khashabi, Ashish Sabharwal, Dan Roth:
Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses. ACL 2020: 5715-5725 - [c97]Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue:
Towards Efficient Discrete Integration via Adaptive Quantile Queries. ECAI 2020: 2577-2584 - [c96]Daniel Khashabi, Tushar Khot, Ashish Sabharwal:
More Bang for Your Buck: Natural Perturbation for Robust Question Answering. EMNLP (1) 2020: 163-170 - [c95]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 - [c94]Tao Li, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Vivek Srikumar:
UNQOVERing Stereotypical Biases via Underspecified Questions. EMNLP (Findings) 2020: 3475-3489 - [c93]Dirk Groeneveld, Tushar Khot, Mausam, Ashish Sabharwal:
A Simple Yet Strong Pipeline for HotpotQA. EMNLP (1) 2020: 8839-8845 - [c92]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning. EMNLP (1) 2020: 8846-8863 - [c91]Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi:
Adversarial Filters of Dataset Biases. ICML 2020: 1078-1088 - [c90]Jonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, Stefano Ermon:
Belief Propagation Neural Networks. NeurIPS 2020 - [i41]Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi:
Adversarial Filters of Dataset Biases. CoRR abs/2002.04108 (2020) - [i40]Daniel Khashabi, Tushar Khot, Ashish Sabharwal:
Natural Perturbation for Robust Question Answering. CoRR abs/2004.04849 (2020) - [i39]Dirk Groeneveld, Tushar Khot, Mausam, Ashish Sabharwal:
A Simple Yet Strong Pipeline for HotpotQA. CoRR abs/2004.06753 (2020) - [i38]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) - [i37]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Measuring and Reducing Non-Multifact Reasoning in Multi-hop Question Answering. CoRR abs/2005.00789 (2020) - [i36]Jonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, Stefano Ermon:
Belief Propagation Neural Networks. CoRR abs/2007.00295 (2020) - [i35]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) - [i34]Tao Li, Tushar Khot, Daniel Khashabi, Ashish Sabharwal, Vivek Srikumar:
UnQovering Stereotyping Biases via Underspecified Questions. CoRR abs/2010.02428 (2020) - [i33]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) - [i32]Shih-Ting Lin, Ashish Sabharwal, Tushar Khot:
ReadOnce Transformers: Reusable Representations of Text for Transformers. CoRR abs/2010.12854 (2020)
2010 – 2019
- 2019
- [c89]Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, Ashish Sabharwal:
QUAREL: A Dataset and Models for Answering Questions about Qualitative Relationships. AAAI 2019: 7063-7071 - [c88]Souvik Kundu, Tushar Khot, Ashish Sabharwal, Peter Clark:
Exploiting Explicit Paths for Multi-hop Reading Comprehension. ACL (1) 2019: 2737-2747 - [c87]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 - [c86]Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, Niranjan Balasubramanian:
Repurposing Entailment for Multi-Hop Question Answering Tasks. NAACL-HLT (1) 2019: 2948-2958 - [c85]Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon:
Approximating the Permanent by Sampling from Adaptive Partitions. NeurIPS 2019: 8858-8869 - [c84]Jonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon:
Adaptive Hashing for Model Counting. UAI 2019: 271-280 - [i31]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) - [i30]Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, Niranjan Balasubramanian:
Repurposing Entailment for Multi-Hop Question Answering Tasks. CoRR abs/1904.09380 (2019) - [i29]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth:
Question Answering as Global Reasoning over Semantic Abstractions. CoRR abs/1906.03672 (2019) - [i28]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) - [i27]Kyle Richardson, Hai Hu, Lawrence S. Moss, Ashish Sabharwal:
Probing Natural Language Inference Models through Semantic Fragments. CoRR abs/1909.07521 (2019) - [i26]Tushar Khot, Ashish Sabharwal, Peter Clark:
What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering. CoRR abs/1909.09253 (2019) - [i25]Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue:
AdaWISH: Faster Discrete Integration via Adaptive Quantiles. CoRR abs/1910.05811 (2019) - [i24]Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, Ashish Sabharwal:
QASC: A Dataset for Question Answering via Sentence Composition. CoRR abs/1910.11473 (2019) - [i23]Erfan Sadeqi Azer, Daniel Khashabi, Ashish Sabharwal, Dan Roth:
Not All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses. CoRR abs/1911.03850 (2019) - [i22]Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon:
Approximating the Permanent by Sampling from Adaptive Partitions. CoRR abs/1911.11856 (2019) - [i21]Kyle Richardson, Ashish Sabharwal:
What Does My QA Model Know? Devising Controlled Probes using Expert Knowledge. CoRR abs/1912.13337 (2019) - 2018
- [j14]Hanie Sedghi, Ashish Sabharwal:
Knowledge Completion for Generics Using Guided Tensor Factorization. Trans. Assoc. Comput. Linguistics 6: 197-210 (2018) - [c83]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth:
Question Answering as Global Reasoning Over Semantic Abstractions. AAAI 2018: 1905-1914 - [c82]Tushar Khot, Ashish Sabharwal, Peter Clark:
SciTaiL: A Textual Entailment Dataset from Science Question Answering. AAAI 2018: 5189-5197 - [c81]Jonathan Kuck, Ashish Sabharwal, Stefano Ermon:
Approximate Inference via Weighted Rademacher Complexity. AAAI 2018: 6376-6383 - [c80]Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Eduard H. Hovy:
AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples. ACL (1) 2018: 2418-2428 - [c79]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 - [c78]Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Peter Clark:
Bridging Knowledge Gaps in Neural Entailment via Symbolic Models. EMNLP 2018: 4940-4945 - [c77]Yexiang Xue, Yang Yuan, Zhitian Xu, Ashish Sabharwal:
Expanding Holographic Embeddings for Knowledge Completion. NeurIPS 2018: 4496-4506 - [c76]Ashish Sabharwal, Yexiang Xue:
Adaptive Stratified Sampling for Precision-Recall Estimation. UAI 2018: 825-834 - [i20]Jonathan Kuck, Ashish Sabharwal, Stefano Ermon:
Approximate Inference via Weighted Rademacher Complexity. CoRR abs/1801.09028 (2018) - [i19]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) - [i18]Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Eduard H. Hovy:
AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples. CoRR abs/1805.04680 (2018) - [i17]Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Peter Clark:
Bridging Knowledge Gaps in Neural Entailment via Symbolic Models. CoRR abs/1808.09333 (2018) - [i16]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) - [i15]Souvik Kundu, Tushar Khot, Ashish Sabharwal:
Exploiting Explicit Paths for Multi-hop Reading Comprehension. CoRR abs/1811.01127 (2018) - [i14]Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, Ashish Sabharwal:
QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships. CoRR abs/1811.08048 (2018) - 2017
- [c75]Tushar Khot, Ashish Sabharwal, Peter Clark:
Answering Complex Questions Using Open Information Extraction. ACL (2) 2017: 311-316 - [c74]Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth:
Learning What is Essential in Questions. CoNLL 2017: 80-89 - [c73]Ashish Sabharwal, Hanie Sedghi:
How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets. UAI 2017 - [i13]Tushar Khot, Ashish Sabharwal, Peter Clark:
Answering Complex Questions Using Open Information Extraction. CoRR abs/1704.05572 (2017) - 2016
- [c72]Ashish Sabharwal, Horst Samulowitz, Gerald Tesauro:
Selecting Near-Optimal Learners via Incremental Data Allocation. AAAI 2016: 2007-2015 - [c71]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 - [c70]Carolyn Kim, Ashish Sabharwal, Stefano Ermon:
Exact Sampling with Integer Linear Programs and Random Perturbations. AAAI 2016: 3248-3254 - [c69]Shengjia Zhao, Sorathan Chaturapruek, Ashish Sabharwal, Stefano Ermon:
Closing the Gap Between Short and Long XORs for Model Counting. AAAI 2016: 3322-3329 - [c68]Tudor Achim, Ashish Sabharwal, Stefano Ermon:
Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference. ICML 2016: 2254-2262 - [c67]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 - [c66]Shengjia Zhao, Enze Zhou, Ashish Sabharwal, Stefano Ermon:
Adaptive Concentration Inequalities for Sequential Decision Problems. NIPS 2016: 1343-1351 - [p4]Donald W. Loveland, Ashish Sabharwal, Bart Selman:
DPLL: The Core of Modern Satisfiability Solvers. Martin Davis on Computability, Computational Logic, and Mathematical Foundations 2016: 315-335 - [i12]Ashish Sabharwal, Horst Samulowitz, Gerald Tesauro:
Selecting Near-Optimal Learners via Incremental Data Allocation. CoRR abs/1601.00024 (2016) - [i11]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) - [i10]Hanie Sedghi, Ashish Sabharwal:
Knowledge Completion for Generics using Guided Tensor Factorization. CoRR abs/1612.03871 (2016) - 2015
- [j13]Rik Koncel-Kedziorski, Hannaneh Hajishirzi, Ashish Sabharwal, Oren Etzioni, Siena Dumas Ang:
Parsing Algebraic Word Problems into Equations. Trans. Assoc. Comput. Linguistics 3: 585-597 (2015) - [c65]Brian Kell, Ashish Sabharwal, Willem-Jan van Hoeve:
BDD-Guided Clause Generation. CPAIOR 2015: 215-230 - [c64]Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni:
Exploring Markov Logic Networks for Question Answering. EMNLP 2015: 685-694 - [i9]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) - [i8]Shengjia Zhao, Sorathan Chaturapruek, Ashish Sabharwal, Stefano Ermon:
Closing the Gap Between Short and Long XORs for Model Counting. CoRR abs/1512.08863 (2015) - 2014
- [j12]Bistra Dilkina
, Carla P. Gomes, Ashish Sabharwal:
Tradeoffs in the complexity of backdoors to satisfiability: dynamic sub-solvers and learning during search. Ann. Math. Artif. Intell. 70(4): 399-431 (2014) - [c63]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Designing Fast Absorbing Markov Chains. AAAI 2014: 849-855 - [c62]Paul Beame, Ashish Sabharwal:
Non-Restarting SAT Solvers with Simple Preprocessing Can Efficiently Simulate Resolution. AAAI 2014: 2608-2615 - [c61]Ashish Sabharwal, Horst Samulowitz:
Insights into Parallelism with Intensive Knowledge Sharing. CP 2014: 655-671 - [c60]David Bergman, André A. Ciré, Ashish Sabharwal, Horst Samulowitz, Vijay A. Saraswat, Willem Jan van Hoeve:
Parallel Combinatorial Optimization with Decision Diagrams. CPAIOR 2014: 351-367 - [c59]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Low-density Parity Constraints for Hashing-Based Discrete Integration. ICML 2014: 271-279 - 2013
- [c58]Bistra Dilkina, Katherine J. Lai, Ronan LeBras, Yexiang Xue, Carla P. Gomes, Ashish Sabharwal, Jordan Suter, Kevin S. McKelvey, Michael K. Schwartz, Claire A. Montgomery:
Large Landscape Conservation - Synthetic and Real-World Datasets. AAAI 2013 - [c57]George Katsirelos, Ashish Sabharwal, Horst Samulowitz, Laurent Simon:
Resolution and Parallelizability: Barriers to the Efficient Parallelization of SAT Solvers. AAAI 2013 - [c56]Ashish Sabharwal, Horst Samulowitz, Tom Schrijvers, Peter J. Stuckey, Guido Tack:
Automated Design of Search with Composability. AAAI (Late-Breaking Developments) 2013 - [c55]Tobias Achterberg, Ashish Sabharwal, Horst Samulowitz:
Stronger Inference through Implied Literals from Conflicts and Knapsack Covers. CPAIOR 2013: 1-11 - [c54]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization. ICML (2) 2013: 334-342 - [c53]Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering. IJCAI 2013: 608-614 - [c52]Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Boosting Sequential Solver Portfolios: Knowledge Sharing and Accuracy Prediction. LION 2013: 153-167 - [c51]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Embed and Project: Discrete Sampling with Universal Hashing. NIPS 2013: 2085-2093 - [c50]Horst Samulowitz, Chandra Reddy, Ashish Sabharwal, Meinolf Sellmann:
Snappy: A Simple Algorithm Portfolio. SAT 2013: 422-428 - [c49]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Optimization With Parity Constraints: From Binary Codes to Discrete Integration. UAI 2013 - [i7]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization. CoRR abs/1302.6677 (2013) - [i6]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Optimization With Parity Constraints: From Binary Codes to Discrete Integration. CoRR abs/1309.6827 (2013) - 2012
- [c48]Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Parallel SAT Solver Selection and Scheduling. CP 2012: 512-526 - [c47]Ashish Sabharwal, Horst Samulowitz, Chandra Reddy:
Guiding Combinatorial Optimization with UCT. CPAIOR 2012: 356-361 - [c46]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Density Propagation and Improved Bounds on the Partition Function. NIPS 2012: 2771-2779 - [c45]Bard Bloom, David Grove, Benjamin Herta, Ashish Sabharwal, Horst Samulowitz, Vijay A. Saraswat:
SatX10: A Scalable Plug&Play Parallel SAT Framework - (Tool Presentation). SAT 2012: 463-468 - [c44]Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Learning Back-Clauses in SAT - (Poster Presentation). SAT 2012: 498-499 - [c43]Arie Matsliah, Ashish Sabharwal, Horst Samulowitz:
Augmenting Clause Learning with Implied Literals - (Poster Presentation). SAT 2012: 500-501 - [i5]Daniel Sheldon, Bistra Dilkina, Adam N. Elmachtoub, Ryan Finseth, Ashish Sabharwal, Jon Conrad, Carla P. Gomes, David B. Shmoys, William Allen, Ole Amundsen, William Vaughan:
Maximizing the Spread of Cascades Using Network Design. CoRR abs/1203.3514 (2012) - [i4]Raghuram Ramanujan, Ashish Sabharwal, Bart Selman:
Understanding Sampling Style Adversarial Search Methods. CoRR abs/1203.4011 (2012) - [i3]Lukas Kroc, Ashish Sabharwal, Bart Selman:
Survey Propagation Revisited. CoRR abs/1206.5273 (2012) - 2011
- [j11]Ashish Sabharwal, Bart Selman:
S. Russell, P. Norvig, Artificial Intelligence: A Modern Approach, Third Edition. Artif. Intell. 175(5-6): 935-937 (2011) - [j10]Lukas Kroc, Ashish Sabharwal, Bart Selman:
Leveraging belief propagation, backtrack search, and statistics for model counting. Ann. Oper. Res. 184(1): 209-231 (2011) - [c42]Siddhartha Jain, Ashish Sabharwal, Meinolf Sellmann:
A General Nogood-Learning Framework for Pseudo-Boolean Multi-Valued SAT. AAAI 2011 - [c41]Serdar Kadioglu, Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Algorithm Selection and Scheduling. CP 2011: 454-469 - [c40]Ronan LeBras, Theodoros Damoulas, John M. Gregoire, Ashish Sabharwal, Carla P. Gomes, R. Bruce van Dover:
Constraint Reasoning and Kernel Clustering for Pattern Decomposition with Scaling. CP 2011: 508-522 - [c39]Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman:
Accelerated Adaptive Markov Chain for Partition Function Computation. NIPS 2011: 2744-2752 - [c38]Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann:
Non-Model-Based Algorithm Portfolios for SAT. SAT 2011: 369-370 - [i2]Paul Beame, Henry A. Kautz, Ashish Sabharwal:
Towards Understanding and Harnessing the Potential of Clause Learning. CoRR abs/1107.0044 (2011) - 2010
- [j9]David W. Aha, Mark S. Boddy, Vadim Bulitko, Artur S. d'Avila Garcez, Prashant Doshi, Stefan Edelkamp, Christopher W. Geib, Piotr J. Gmytrasiewicz, Robert P. Goldman, Pascal Hitzler, Charles L. Isbell Jr., Darsana P. Josyula, Leslie Pack Kaelbling, Kristian Kersting, Maithilee Kunda, Luís C. Lamb, Bhaskara Marthi, Keith McGreggor, Vivi Nastase, Gregory M. Provan, Anita Raja, Ashwin Ram, Mark O. Riedl, Stuart J. Russell, Ashish Sabharwal, Jan-Georg Smaus, Gita Sukthankar, Karl Tuyls, Ron van der Meyden, Alon Y. Halevy, Lilyana Mihalkova, Sriraam Natarajan:
Reports of the AAAI 2010 Conference Workshops. AI Mag. 31(4): 95-108 (2010) - [j8]Ethan Kim, Ashish Sabharwal, Adrian Vetta, Mathieu Blanchette:
Predicting direct protein interactions from affinity purification mass spectrometry data. Algorithms Mol. Biol. 5: 34 (2010) - [j7]Matthew Cary, Atri Rudra, Ashish Sabharwal, Erik Vee:
Floodlight illumination of infinite wedges. Comput. Geom. 43(1): 23-34 (2010) - [c37]Lukas Kroc, Ashish Sabharwal, Bart Selman:
Approximate Inference for Clusters in Solution Spaces. Abstraction, Reformulation, and Approximation 2010 - [c36]Gregory M. Provan, Ashish Sabharwal:
Preface. Abstraction, Reformulation, and Approximation 2010 - [c35]Raghuram Ramanujan, Ashish Sabharwal, Bart Selman:
On Adversarial Search Spaces and Sampling-Based Planning. ICAPS 2010: 242-245 - [c34]Kiyan Ahmadizadeh, Bistra Dilkina, Carla P. Gomes, Ashish Sabharwal:
An Empirical Study of Optimization for Maximizing Diffusion in Networks. CP 2010: 514-521 - [c33]Lukas Kroc, Ashish Sabharwal, Bart Selman:
An Empirical Study of Optimal Noise and Runtime Distributions in Local Search. SAT 2010: 346-351 - [c32]Raghuram Ramanujan, Ashish Sabharwal, Bart Selman:
Understanding Sampling Style Adversarial Search Methods. UAI 2010: 474-483 - [c31]Daniel Sheldon, Bistra Dilkina, Adam N. Elmachtoub, Ryan Finseth, Ashish Sabharwal, Jon Conrad, Carla P. Gomes, David B. Shmoys, William Allen, Ole Amundsen, William Vaughan:
Maximizing the Spread of Cascades Using Network Design. UAI 2010: 517-526
2000 – 2009
- 2009
- [j6]Willem Jan van Hoeve, Gilles Pesant, Louis-Martin Rousseau, Ashish Sabharwal:
New filtering algorithms for combinations of among constraints. Constraints An Int. J. 14(2): 273-292 (2009) - [j5]