Balaraman Ravindran, Ph.D.
Affiliations: | University of Massachusetts, Amherst, Amherst, MA |
Area:
Reinforcement LearningGoogle:
"Balaraman Ravindran"Mean distance: 16.58 (cluster 29)
Parents
Sign in to add mentor| Andrew Barto | grad student | 2004 | U Mass Amherst | |
| (An algebraic approach to abstraction in reinforcement learning.) | ||||
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Publications
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| Ghose A, Ravindran B. (2020) Interpretability With Accurate Small Models. Frontiers in Artificial Intelligence. 3: 3 |
| Ganapathy S, Venkataramani S, Ravindran B, et al. (2017) DyVEDeep: Dynamic Variable Effort Deep Neural Networks Acm Transactions in Embedded Computing Systems. 19: 1-24 |
| Chandar S, Khapra MM, Larochelle H, et al. (2015) Correlational Neural Networks. Neural Computation. 1-29 |
| Balasubramani PP, Chakravarthy VS, Ravindran B, et al. (2015) A network model of basal ganglia for understanding the roles of dopamine and serotonin in reward-punishment-risk based decision making. Frontiers in Computational Neuroscience. 9: 76 |
| Sankar MV, Ravindran B. (2015) Parallelization of game theoretic centrality algorithms Sadhana - Academy Proceedings in Engineering Sciences. 40: 1821-1843 |
| Ravindran B. (2013) Relativized hierarchical decomposition of Markov decision processes. Progress in Brain Research. 202: 465-88 |
| Michalak TP, Aadithya KV, Szczepanski PL, et al. (2013) Efficient computation of the shapley value for game-theoretic network centrality Journal of Artificial Intelligence Research. 46: 607-650 |
| Saravanan M, Ravindran B. (2010) Identification of Rhetorical Roles for Segmentation and Summarization of a Legal Judgment Artificial Intelligence and Law. 18: 45-76 |