Mahadevan, Sridhar

67 publications

NeurIPS 2025 Universal Causal Inference in a Topos Sridhar Mahadevan

AAAI 2023 Smoothed Online Combinatorial Optimization Using Imperfect Predictions Kai Wang, Zhao Song, Georgios Theocharous, Sridhar Mahadevan

WACV 2022 Generating and Controlling Diversity in Image Search Md. Mehrab Tanjim, Ritwik Sinha, Krishna Kumar Singh, Sridhar Mahadevan, David Arbour, Moumita Sinha, Garrison W. Cottrell

ICML 2020 Optimizing for the Future in Non-Stationary MDPs Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip Thomas

ICMLW 2020 Optimizing for the Future in Non-Stationary MDPs Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas

ECML-PKDD 2018 A Unified Framework for Domain Adaptation Using Metric Learning on Manifolds Sridhar Mahadevan, Bamdev Mishra, Shalini Ghosh

AAAI 2018 Imagination Machines: A New Challenge for Artificial Intelligence Sridhar Mahadevan

JAIR 2018 Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik

ICLR 2017 Generative Multi-Adversarial Networks Ishan P. Durugkar, Ian Gemp, Sridhar Mahadevan

IJCAI 2016 Proximal Gradient Temporal Difference Learning Algorithms Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

AAAI 2015 Aligning Mixed Manifolds Thomas Boucher, Cj Carey, Sridhar Mahadevan, Melinda Darby Dyar

UAI 2015 Finite-Sample Analysis of Proximal Gradient TD Algorithms Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

AAAI 2014 Manifold Spanning Graphs Cj Carey, Sridhar Mahadevan

AAAI 2013 Basis Adaptation for Sparse Nonlinear Reinforcement Learning Sridhar Mahadevan, Stephen Giguere, Nicholas Jacek

IJCAI 2013 Manifold Alignment Preserving Global Geometry Chang Wang, Sridhar Mahadevan

AAAI 2013 Multiscale Manifold Learning Chang Wang, Sridhar Mahadevan

NeurIPS 2013 Projected Natural Actor-Critic Philip S. Thomas, William C Dabney, Stephen Giguere, Sridhar Mahadevan

AAAI 2012 Manifold Warping: Manifold Alignment over Time Hoa Trong Vu, Clifton Carey, Sridhar Mahadevan

NeurIPS 2012 Regularized Off-Policy TD-Learning Bo Liu, Sridhar Mahadevan, Ji Liu

UAI 2012 Sparse Q-Learning with Mirror Descent Sridhar Mahadevan, Bo Liu

IJCAI 2011 Heterogeneous Domain Adaptation Using Manifold Alignment Chang Wang, Sridhar Mahadevan

IJCAI 2011 Jointly Learning Data-Dependent Label and Locality-Preserving Projections Chang Wang, Sridhar Mahadevan

NeurIPS 2010 Basis Construction from Power Series Expansions of Value Functions Sridhar Mahadevan, Bo Liu

AAAI 2010 Compressing POMDPs Using Locality Preserving Non-Negative Matrix Factorization Georgios Theocharous, Sridhar Mahadevan

AAAI 2010 Representation Discovery in Sequential Decision Making Sridhar Mahadevan

ECML-PKDD 2009 Hybrid Least-Squares Algorithms for Approximate Policy Evaluation Jeffrey Johns, Marek Petrik, Sridhar Mahadevan

MLJ 2009 Hybrid Least-Squares Algorithms for Approximate Policy Evaluation Jeffrey Johns, Marek Petrik, Sridhar Mahadevan

FnTML 2009 Learning Representation and Control in Markov Decision Processes: New Frontiers Sridhar Mahadevan

IJCAI 2009 Manifold Alignment Without Correspondence Chang Wang, Sridhar Mahadevan

IJCAI 2009 Multiscale Analysis of Document Corpora Based on Diffusion Models Chang Wang, Sridhar Mahadevan

AAAI 2008 Fast Spectral Learning Using Lanczos Eigenspace Projections Sridhar Mahadevan

ICML 2008 Manifold Alignment Using Procrustes Analysis Chang Wang, Sridhar Mahadevan

ICML 2007 Adaptive Mesh Compression in 3D Computer Graphics Using Multiscale Manifold Learning Sridhar Mahadevan

AAAI 2007 Compact Spectral Bases for Value Function Approximation Using Kronecker Factorization Jeffrey Johns, Sridhar Mahadevan, Chang Wang

ICML 2007 Constructing Basis Functions from Directed Graphs for Value Function Approximation Jeffrey Johns, Sridhar Mahadevan

JMLR 2007 Hierarchical Average Reward Reinforcement Learning Mohammad Ghavamzadeh, Sridhar Mahadevan

ICML 2007 Learning State-Action Basis Functions for Hierarchical MDPs Sarah Osentoski, Sridhar Mahadevan

JMLR 2007 Proto-Value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes Sridhar Mahadevan, Mauro Maggioni

ICML 2006 Fast Direct Policy Evaluation Using Multiscale Analysis of Markov Diffusion Processes Mauro Maggioni, Sridhar Mahadevan

AAAI 2006 Learning Representation and Control in Continuous Markov Decision Processes Sridhar Mahadevan, Mauro Maggioni, Kimberly Ferguson, Sarah Osentoski

AAAI 2005 A Variational Learning Algorithm for the Abstract Hidden Markov Model Jeffrey Johns, Sridhar Mahadevan

ICML 2005 Coarticulation: An Approach for Generating Concurrent Plans in Markov Decision Processes Khashayar Rohanimanesh, Sridhar Mahadevan

ICML 2005 Proto-Value Functions: Developmental Reinforcement Learning Sridhar Mahadevan

UAI 2005 Representation Policy Iteration Sridhar Mahadevan

AAAI 2005 Samuel Meets Amarel: Automating Value Function Approximation Using Global State Space Analysis Sridhar Mahadevan

NeurIPS 2005 Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions Sridhar Mahadevan, Mauro Maggioni

NeurIPS 2004 Coarticulation in Markov Decision Processes Khashayar Rohanimanesh, Robert Platt, Sridhar Mahadevan, Roderic Grupen

ICML 2003 Hierarchical Policy Gradient Algorithms Mohammad Ghavamzadeh, Sridhar Mahadevan

ICML 2002 Hierarchically Optimal Average Reward Reinforcement Learning Mohammad Ghavamzadeh, Sridhar Mahadevan

NeurIPS 2002 Learning to Take Concurrent Actions Khashayar Rohanimanesh, Sridhar Mahadevan

ICML 2001 Continuous-Time Hierarchical Reinforcement Learning Mohammad Ghavamzadeh, Sridhar Mahadevan

UAI 2001 Decision-Theoretic Planning with Concurrent Temporally Extended Actions Khashayar Rohanimanesh, Sridhar Mahadevan

NeurIPS 2000 Hierarchical Memory-Based Reinforcement Learning Natalia Hernandez-Gardiol, Sridhar Mahadevan

ICML 1999 Hierarchical Optimization of Policy-Coupled Semi-Markov Decision Processes Gang Wang, Sridhar Mahadevan

MLJ 1998 Rapid Concept Learning for Mobile Robots Sridhar Mahadevan, Georgios Theocharous, Nikfar Khaleeli

AAAI 1996 An Average-Reward Reinforcement Learning Algorithm for Computing Bias-Optimal Policies Sridhar Mahadevan

MLJ 1996 Average Reward Reinforcement Learning: Foundations, Algorithms, and Empirical Results Sridhar Mahadevan

ICML 1996 Sensitive Discount Optimality: Unifying Discounted and Average Reward Reinforcement Learning Sridhar Mahadevan

MLJ 1994 Quantifying Prior Determination Knowledge Using the PAC Learning Model Sridhar Mahadevan, Prasad Tadepalli

ICML 1994 To Discount or Not to Discount in Reinforcement Learning: A Case Study Comparing R Learning and Q Learning Sridhar Mahadevan

ICML 1992 Enhancing Transfer in Reinforcement Learning by Building Stochastic Models of Robot Actions Sridhar Mahadevan

AAAI 1991 Automatic Programming of Behavior-Based Robots Using Reinforcement Learning Sridhar Mahadevan, Jonathan Connell

ICML 1991 Scaling Reinforcement Learning to Robotics by Exploiting the Subsumption Architecture Sridhar Mahadevan, Jonathan Connell

ICML 1989 Using Determinations in EBL: A Solution to the Incomplete Theory Problem Sridhar Mahadevan

ICML 1988 On the Tractability of Learning from Incomplete Theories Sridhar Mahadevan, Prasad Tadepalli

IJCAI 1985 LEAP: A Learning Apprentice for VLSI Design Tom M. Mitchell, Sridhar Mahadevan, Louis I. Steinberg

IJCAI 1985 Verification-Based Learning: A Generalized Strategy for Inferring Problem-Reduction Methods Sridhar Mahadevan