| Learning linear structural equation models in polynomial time and sample complexity A Ghoshal, J Honorio International Conference on Artificial Intelligence and Statistics, 1466-1475, 2018 | 92 | 2018 |
| Low-resource domain adaptation for compositional task-oriented semantic parsing X Chen, A Ghoshal, Y Mehdad, L Zettlemoyer, S Gupta arXiv preprint arXiv:2010.03546, 2020 | 91 | 2020 |
| Learning identifiable gaussian bayesian networks in polynomial time and sample complexity A Ghoshal, J Honorio Advances in Neural Information Processing Systems 30, 2017 | 65 | 2017 |
| MicroRNA target prediction using thermodynamic and sequence curves A Ghoshal, R Shankar, S Bagchi, A Grama, S Chaterji BMC genomics 16, 1-21, 2015 | 41 | 2015 |
| Information-theoretic limits of Bayesian network structure learning A Ghoshal, J Honorio Artificial Intelligence and Statistics, 767-775, 2017 | 32 | 2017 |
| An ensemble svm model for the accurate prediction of non-canonical microrna targets A Ghoshal, A Grama, S Bagchi, S Chaterji Proceedings of the 6th ACM Conference on Bioinformatics, Computational …, 2015 | 29 | 2015 |
| Fid-ex: Improving sequence-to-sequence models for extractive rationale generation K Lakhotia, B Paranjape, A Ghoshal, W Yih, Y Mehdad, S Iyer arXiv preprint arXiv:2012.15482, 2020 | 23 | 2020 |
| CITADEL: Conditional token interaction via dynamic lexical routing for efficient and effective multi-vector retrieval M Li, SC Lin, B Oguz, A Ghoshal, J Lin, Y Mehdad, W Yih, X Chen arXiv preprint arXiv:2211.10411, 2022 | 21 | 2022 |
| Learning better structured representations using low-rank adaptive label smoothing A Ghoshal, X Chen, S Gupta, L Zettlemoyer, Y Mehdad International Conference on Learning Representations, 2021 | 18 | 2021 |
| From behavior to sparse graphical games: Efficient recovery of equilibria A Ghoshal, J Honorio 2016 54th Annual Allerton Conference on Communication, Control, and …, 2016 | 18 | 2016 |
| Direct estimation of difference between structural equation models in high dimensions A Ghoshal, J Honorio arXiv preprint arXiv:1906.12024, 2019 | 16* | 2019 |
| Learning graphical games from behavioral data: Sufficient and necessary conditions A Ghoshal, J Honorio Artificial Intelligence and Statistics, 1532-1540, 2017 | 16 | 2017 |
| Towards understanding the behaviors of optimal deep active learning algorithms Y Zhou, A Renduchintala, X Li, S Wang, Y Mehdad, A Ghoshal International Conference on Artificial Intelligence and Statistics, 1486-1494, 2021 | 14 | 2021 |
| A distributed classifier for microrna target prediction with validation through tcga expression data A Ghoshal, J Zhang, MA Roth, KM Xia, AY Grama, S Chaterji IEEE/ACM transactions on computational biology and bioinformatics 15 (4 …, 2018 | 11 | 2018 |
| Learning sparse polymatrix games in polynomial time and sample complexity A Ghoshal, J Honorio arXiv preprint arXiv:1706.05648, 2017 | 10 | 2017 |
| Learning maximum-a-posteriori perturbation models for structured prediction in polynomial time A Ghoshal, J Honorio International Conference on Machine Learning, 1754-1762, 2018 | 9 | 2018 |
| Quaser: Question answering with scalable extractive rationalization A Ghoshal, S Iyer, B Paranjape, K Lakhotia, SW Yih, Y Mehdad Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 4 | 2022 |
| Minimax bounds for structured prediction based on factor graphs K Bello, A Ghoshal, J Honorio International Conference on Artificial Intelligence and Statistics, 213-222, 2020 | 4 | 2020 |
| Fast training on large genomics data using distributed support vector machines N Theera-Ampornpunt, SG Kim, A Ghoshal, S Bagchi, A Grama, ... 2016 8th International Conference on Communication Systems and Networks …, 2016 | 4 | 2016 |
| Covering space with simple robots: from chains to random trees A Ghoshal, DA Shell 2013 IEEE International Conference on Robotics and Automation, 914-920, 2013 | 3 | 2013 |
