Sridhar Mahadevan

ORCID

Publication Activity (10 Years)

Years Active: 1985-2023
Publications (10 Years): 42

Top Venues

Publications

Yeqi Gao, Sridhar Mahadevan, Zhao Song
An Over-parameterized Exponential Regression. CoRR (2023)
Sridhar Mahadevan
Universal Causality. Entropy 25 (4) (2023)
Kai Wang, Zhao Song, Georgios Theocharous, Sridhar Mahadevan
Smoothed Online Combinatorial Optimization Using Imperfect Predictions. AAAI (2023)
Shiv Shankar, Ritwik Sinha, Saayan Mitra, Viswanathan (Vishy) Swaminathan, Sridhar Mahadevan, Moumita Sinha
Privacy Aware Experiments without Cookies. WSDM (2023)
Yichuan Deng, Sridhar Mahadevan, Zhao Song
Randomized and Deterministic Attention Sparsification Algorithms for Over-parameterized Feature Dimension. CoRR (2023)
Yichuan Deng, Zhihang Li, Sridhar Mahadevan, Zhao Song
Zero-th Order Algorithm for Softmax Attention Optimization. CoRR (2023)
Sridhar Mahadevan
Categoroids: Universal Conditional Independence. CoRR (2022)
Kai Wang, Zhao Song, Georgios Theocharous, Sridhar Mahadevan
Smoothed Online Combinatorial Optimization Using Imperfect Predictions. CoRR (2022)
Sridhar Mahadevan
On The Universality of Diagrams for Causal Inference and The Causal Reproducing Property. CoRR (2022)
Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Viswanathan Swaminathan, Sridhar Mahadevan
Privacy Aware Experiments without Cookies. CoRR (2022)
Md. Mehrab Tanjim, Ritwik Sinha, Krishna Kumar Singh, Sridhar Mahadevan, David Arbour, Moumita Sinha, Garrison W. Cottrell
Generating and Controlling Diversity in Image Search. WACV (2022)
Sridhar Mahadevan
Unifying Causal Inference and Reinforcement Learning using Higher-Order Category Theory. CoRR (2022)
Sridhar Mahadevan
A Layered Architecture for Universal Causality. CoRR (2022)
Sridhar Mahadevan
Causal Inference in Network Economics. CoRR (2021)
Sridhar Mahadevan
Causal Homotopy. CoRR (2021)
Sridhar Mahadevan
Universal Decision Models. CoRR (2021)
Sridhar Mahadevan
Asymptotic Causal Inference. CoRR (2021)
Sridhar Mahadevan, Anup Rao, Georgios Theocharous, Jennifer Healey
Multiscale Manifold Warping. CoRR (2021)
Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas
Optimizing for the Future in Non-Stationary MDPs. CoRR (2020)
Bo Liu, Sridhar Mahadevan, Ji Liu
Regularized Off-Policy TD-Learning. CoRR (2020)
Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik
Finite-Sample Analysis of GTD Algorithms. CoRR (2020)
Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik
Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity. CoRR (2020)
Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas
Optimizing for the Future in Non-Stationary MDPs. ICML (2020)
Georgios Theocharous, Jennifer Healey, Sridhar Mahadevan, Michele A. Saad
Personalizing with Human Cognitive Biases. UMAP (Adjunct Publication) (2019)
Sridhar Mahadevan, Bamdev Mishra, Shalini Ghosh
A Unified Framework for Domain Adaptation using Metric Learning on Manifolds. CoRR (2018)
Sridhar Mahadevan
Imagination Machines: A New Challenge for Artificial Intelligence. AAAI (2018)
Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik
Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity. J. Artif. Intell. Res. 63 (2018)
Ian Gemp, Sridhar Mahadevan
Global Convergence to the Equilibrium of GANs using Variational Inequalities. CoRR (2018)
Sridhar Mahadevan, Bamdev Mishra, Shalini Ghosh
A Unified Framework for Domain Adaptation Using Metric Learning on Manifolds. ECML/PKDD (2) (2018)
Ian Gemp, Sridhar Mahadevan
Online Monotone Games. CoRR (2017)
Stephen Giguere, Francisco Garcia, Sridhar Mahadevan
A Manifold Approach to Learning Mutually Orthogonal Subspaces. CoRR (2017)
Ishan P. Durugkar, Ian Gemp, Sridhar Mahadevan
Generative Multi-Adversarial Networks. ICLR (Poster) (2017)
Ishan P. Durugkar, Clemens Rosenbaum, Stefan Dernbach, Sridhar Mahadevan
Deep Reinforcement Learning With Macro-Actions. CoRR (2016)
Ishan P. Durugkar, Ian Gemp, Sridhar Mahadevan
Generative Multi-Adversarial Networks. CoRR (2016)
Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik
Proximal Gradient Temporal Difference Learning Algorithms. IJCAI (2016)
Ian Gemp, Ishan P. Durugkar, Mario Parente, Melinda Darby Dyar, Sridhar Mahadevan
Deep Generative Models for Spectroscopic Analysis on Mars. CoRR (2016)
Ian Gemp, Sridhar Mahadevan
Online Monotone Optimization. CoRR (2016)
Thomas Boucher, C. J. Carey, Sridhar Mahadevan, Melinda Darby Dyar
Aligning Mixed Manifolds. AAAI (2015)
Lidan Wang, Minwei Feng, Bowen Zhou, Bing Xiang, Sridhar Mahadevan
Efficient Hyper-parameter Optimization for NLP Applications. EMNLP (2015)
Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik
Finite-Sample Analysis of Proximal Gradient TD Algorithms. UAI (2015)
Sridhar Mahadevan, Sarath Chandar
Reasoning about Linguistic Regularities in Word Embeddings using Matrix Manifolds. CoRR (2015)
Ian Gemp, Sridhar Mahadevan, Bo Liu
Solving Large Sustainable Supply Chain Networks Using Variational Inequalities. AAAI Workshop: Computational Sustainability (2015)
CJ Carey, Sridhar Mahadevan
Manifold Spanning Graphs. AAAI (2014)
Sridhar Mahadevan, Bo Liu, Philip S. Thomas, William Dabney, Stephen Giguere, Nicholas Jacek, Ian Gemp, Ji Liu
Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces. CoRR (2014)
Ian Gemp, Sridhar Mahadevan
Modeling Context in Cognition Using Variational Inequalities. AAAI Fall Symposia (2014)
Quanqing Xu, Rajesh Vellore Arumugam, Khai Leong Yong, Sridhar Mahadevan
Efficient and Scalable Metadata Management in EB-Scale File Systems. IEEE Trans. Parallel Distributed Syst. 25 (11) (2014)
Chang Wang, Sridhar Mahadevan
Multiscale Manifold Learning. AAAI (2013)
Chang Wang, Sridhar Mahadevan
Manifold Alignment Preserving Global Geometry. IJCAI (2013)
Khashayar Rohanimanesh, Sridhar Mahadevan
Decision-Theoretic Planning with Concurrent Temporally Extended Actions CoRR (2013)
Sridhar Mahadevan, Stephen Giguere, Nicholas Jacek
Basis Adaptation for Sparse Nonlinear Reinforcement Learning. AAAI (2013)
Quanqing Xu, Rajesh Vellore Arumugam, Khai Leong Yong, Sridhar Mahadevan
DROP: Facilitating distributed metadata management in EB-scale storage systems. MSST (2013)
Philip S. Thomas, William Dabney, Stephen Giguere, Sridhar Mahadevan
Projected Natural Actor-Critic. NIPS (2013)
Sridhar Mahadevan, Bo Liu
Sparse Q-learning with Mirror Descent. UAI (2012)
Sridhar Mahadevan, Bo Liu
Sparse Q-learning with Mirror Descent CoRR (2012)
Hoa Trong Vu, Clifton Carey, Sridhar Mahadevan
Manifold Warping: Manifold Alignment over Time. AAAI (2012)
Bo Liu, Sridhar Mahadevan, Ji Liu
Regularized Off-Policy TD-Learning. NIPS (2012)
Sridhar Mahadevan
Representation Policy Iteration CoRR (2012)
Chang Wang, Sridhar Mahadevan
Jointly Learning Data-Dependent Label and Locality-Preserving Projections. IJCAI (2011)
Chang Wang, Sridhar Mahadevan
Heterogeneous Domain Adaptation Using Manifold Alignment. IJCAI (2011)
Blake Foster, Sridhar Mahadevan, Rui Wang
A GPU-Based Approximate SVD Algorithm. PPAM (1) (2011)
Georgios Theocharous, Sridhar Mahadevan
Compressing POMDPs Using Locality Preserving Non-Negative Matrix Factorization. AAAI (2010)
Sarah Osentoski, Sridhar Mahadevan
Basis function construction for hierarchical reinforcement learning. AAMAS (2010)
Sridhar Mahadevan, Bo Liu
Basis Construction from Power Series Expansions of Value Functions. NIPS (2010)
Sridhar Mahadevan
Representation Discovery in Sequential Decision Making. AAAI (2010)
Kimberly Ferguson, Beverly Park Woolf, Sridhar Mahadevan
Transfer Learning and Representation Discovery in Intelligent Tutoring Systems. AIED (2009)
Sridhar Mahadevan
Learning Representation and Control in Markov Decision Processes: New Frontiers. Found. Trends Mach. Learn. 1 (4) (2009)
Jeffrey Johns, Marek Petrik, Sridhar Mahadevan
Hybrid least-squares algorithms for approximate policy evaluation. Mach. Learn. 76 (2-3) (2009)
Chang Wang, Sridhar Mahadevan
A General Framework for Manifold Alignment. AAAI Fall Symposium: Manifold Learning and Its Applications (2009)
Chang Wang, Sridhar Mahadevan
Manifold Alignment without Correspondence. IJCAI (2009)
Chang Wang, Sridhar Mahadevan
Multiscale Analysis of Document Corpora Based on Diffusion Models. IJCAI (2009)
Jeffrey Johns, Marek Petrik, Sridhar Mahadevan
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation. ECML/PKDD (1) (2009)
Chang Wang, Sridhar Mahadevan
Manifold alignment using Procrustes analysis. ICML (2008)
Sridhar Mahadevan
Fast Spectral Learning using Lanczos Eigenspace Projections. AAAI (2008)
Sarah Osentoski, Sridhar Mahadevan
Learning state-action basis functions for hierarchical MDPs. ICML (2007)
Jeffrey Johns, Sarah Osentoski, Sridhar Mahadevan
Representation Discovery in Planning using Harmonic Analysis. AAAI Fall Symposium: Computational Approaches to Representation Change during Learning and Development (2007)
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns, Kimberly Ferguson, Chang Wang
Learning to Plan Using Harmonic Analysis of Diffusion Models. ICAPS (2007)
Sridhar Mahadevan, Mauro Maggioni
Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes. J. Mach. Learn. Res. 8 (2007)
Jeffrey Johns, Sridhar Mahadevan, Chang Wang
Compact Spectral Bases for Value Function Approximation Using Kronecker Factorization. AAAI (2007)
Ivon Arroyo, Kimberly Ferguson, Jeffrey Johns, Toby Dragon, Hasmik Meheranian, Don Fisher, Andrew G. Barto, Sridhar Mahadevan, Beverly Park Woolf
Repairing Disengagement With Non-Invasive Interventions. AIED (2007)
Jeffrey Johns, Sridhar Mahadevan
Constructing basis functions from directed graphs for value function approximation. ICML (2007)
Mohammad Ghavamzadeh, Sridhar Mahadevan
Hierarchical Average Reward Reinforcement Learning. J. Mach. Learn. Res. 8 (2007)
Sridhar Mahadevan
Adaptive mesh compression in 3D computer graphics using multiscale manifold learning. ICML (2007)
Jeffrey Johns, Sridhar Mahadevan, Beverly Park Woolf
Estimating Student Proficiency Using an Item Response Theory Model. Intelligent Tutoring Systems (2006)
Sridhar Mahadevan, Mauro Maggioni, Kimberly Ferguson, Sarah Osentoski
Learning Representation and Control in Continuous Markov Decision Processes. AAAI (2006)
Mauro Maggioni, Sridhar Mahadevan
Fast direct policy evaluation using multiscale analysis of Markov diffusion processes. ICML (2006)
Mohammad Ghavamzadeh, Sridhar Mahadevan, Rajbala Makar
Hierarchical multi-agent reinforcement learning. Auton. Agents Multi Agent Syst. 13 (2) (2006)
Kimberly Ferguson, Ivon Arroyo, Sridhar Mahadevan, Beverly Park Woolf, Andrew G. Barto
Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels. Intelligent Tutoring Systems (2006)
Sridhar Mahadevan
Representation Policy Iteration. UAI (2005)
Khashayar Rohanimanesh, Sridhar Mahadevan
Coarticulation: an approach for generating concurrent plans in Markov decision processes. ICML (2005)
Jeffrey Johns, Sridhar Mahadevan
A Variational Learning Algorithm for the Abstract Hidden Markov Model. AAAI (2005)
Sridhar Mahadevan
Proto-value functions: developmental reinforcement learning. ICML (2005)
Victoria Manfredi, Sridhar Mahadevan, James F. Kurose
Switching kalman filters for prediction and tracking in an adaptive meteorological sensing network. SECON (2005)
Sridhar Mahadevan
Samuel Meets Amarel: Automating Value Function Approximation Using Global State Space Analysis. AAAI (2005)
Sridhar Mahadevan, Mauro Maggioni
Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions. NIPS (2005)
Mohammad Ghavamzadeh, Sridhar Mahadevan
Learning to Communicate and Act Using Hierarchical Reinforcement Learning. AAMAS (2004)
Khashayar Rohanimanesh, Robert Platt Jr., Sridhar Mahadevan, Roderic A. Grupen
Coarticulation in Markov Decision Processes. NIPS (2004)
Sarah Osentoski, Victoria Manfredi, Sridhar Mahadevan
Learning hierarchical models of activity. IROS (2004)
Suchi Saria, Sridhar Mahadevan
Probabilistic Plan Recognition in Multiagent Systems. ICAPS (2004)
Mohammad Ghavamzadeh, Sridhar Mahadevan
Hierarchical Policy Gradient Algorithms. ICML (2003)
Andrew G. Barto, Sridhar Mahadevan
Recent Advances in Hierarchical Reinforcement Learning. Discret. Event Dyn. Syst. 13 (1-2) (2003)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sridhar Mahadevan