Thinking Fast and Slow in AI G Booch, F Fabiano, L Horesh, K Kate, J Lenchner, N Linck, A Loreggia, ... Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021 | 113 | 2021 |
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines K Murugesan, M Atzeni, P Kapanipathi, P Shukla, S Kumaravel, ... Proceedings of the 35th AAAI Conference on Artificial Intelligence, 2021 | 64 | 2021 |
Adaptive Smoothed Online Multi-Task Learning K Murugesan, H Liu, J Carbonell, Y Yang Advances in Neural Information Processing Systems (NIPS 2016), 2016 | 50 | 2016 |
Plansformer: Generating symbolic plans using transformers V Pallagani, B Muppasani, K Murugesan, F Rossi, L Horesh, B Srivastava, ... arXiv preprint arXiv:2212.08681, 2022 | 48 | 2022 |
Self-Paced Multitask Learning with Shared Knowledge K Murugesan, J Carbonell Proceedings of the 26th International Joint Conference on Artificial …, 2017 | 42 | 2017 |
Hybrid bisect K-means clustering algorithm K Murugesan, J Zhang 2011 International Conference on Business Computing and Global …, 2011 | 42 | 2011 |
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach HD Fernando, H Shen, M Liu, S Chaudhury, K Murugesan, T Chen Proceeding of 11th International Conference on Learning Representations …, 2023 | 40 | 2023 |
On the prospects of incorporating large language models (llms) in automated planning and scheduling (aps) V Pallagani, BC Muppasani, K Roy, F Fabiano, A Loreggia, K Murugesan, ... Proceedings of the International Conference on Automated Planning and …, 2024 | 34 | 2024 |
Enhancing text-based reinforcement learning agents with commonsense knowledge K Murugesan, M Atzeni, P Shukla, M Sachan, P Kapanipathi, ... arXiv preprint arXiv:2005.00811, 2020 | 32 | 2020 |
Understanding the capabilities of large language models for automated planning V Pallagani, B Muppasani, K Murugesan, F Rossi, B Srivastava, L Horesh, ... arXiv preprint arXiv:2305.16151, 2023 | 26 | 2023 |
Active learning from peers K Murugesan, J Carbonell Advances in Neural Information Processing Systems 30, 2017 | 24 | 2017 |
Hybrid hierarchical clustering: An experimental analysis K Murugesan, J Zhang University of Kentucky, Lexington, Technical Report: CMIDA-HiPSCCS, 001-11, 2011 | 22 | 2011 |
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with -Greedy Exploration S Zhang, H Li, M Wang, M Liu, PY Chen, S Lu, S Liu, K Murugesan, ... Advances in Neural Information Processing Systems 36, 2024 | 19 | 2024 |
Multi-Task Multiple Kernel Relationship Learning K Murugesan, J Carbonell Proceedings of the 17th SIAM International Conference on Data Mining (SDM …, 2017 | 19 | 2017 |
Case-based Reasoning for Better Generalization in Text-Adventure Games M Atzeni, S Dhuliawala, K Murugesan, M Sachan Proceedings of 10th International Conference on Learning Representations …, 2022 | 16* | 2022 |
Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations K Murugesan, M Atzeni, P Kapanipathi, K Talamadupula, M Sachan, ... Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 16 | 2021 |
Multitask Matrix Completion for Learning Protein Interactions Across Diseases M Kshirsagar, J Carbonell, J Klein-Seetharaman, K Murugesan International Conference on Research in Computational Molecular Biology …, 2016 | 16 | 2016 |
A hybrid neuro-symbolic approach for text-based games using inductive logic programming K Basu, K Murugesan, M Atzeni, P Kapanipathi, K Talamadupula, ... Combining learning and reasoning: programming languages, formalisms, and …, 2021 | 13 | 2021 |
Co-clustering for multitask learning K Murugesan, J Carbonell, Y Yang arXiv preprint arXiv:1703.00994, 2017 | 12 | 2017 |
Detectors for safe and reliable llms: Implementations, uses, and limitations S Achintalwar, AA Garcia, A Anaby-Tavor, I Baldini, SE Berger, ... arXiv preprint arXiv:2403.06009, 2024 | 11 | 2024 |