S. Mahadevan

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

Hierarchical Memory-Based Reinforcement Learning

Sridhar Mahadevan, Natalia Hernandez-Gardiol, S. Mahadevan, 2000, NIPS.

Approximate planning with hierarchical partially observable Markov decision process models for robot navigation

Sridhar Mahadevan, Georgios Theocharous, S. Mahadevan, 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

Hierarchical Map Learning For Robot Navigation

S. Mahadevan, Georgios Theocharous, Khashayar Rohanimanesh, 2000 .

Hierarchical multi-agent reinforcement learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, Rajbala Makar, 2001, AGENTS '01.

Regularized Off-Policy TD-Learning

Bo Liu, Ji Liu, Sridhar Mahadevan, 2012, NIPS.

Learning to Take Concurrent Actions

Sridhar Mahadevan, Khashayar Rohanimanesh, S. Mahadevan, 2002, NIPS.

Hierarchical learning and planning in partially observable markov decision processes

Sridhar Mahadevan, Georgios Theocharous, S. Mahadevan, 2002 .

Samuel Meets Amarel: Automating Value Function Approximation Using Global State Space Analysis

Sridhar Mahadevan, S. Mahadevan, 2005, AAAI.

The NSF Workshop on Reinforcement Learning: Summary and Observations

Leslie Pack Kaelbling, Sridhar Mahadevan, S. Mahadevan, 1996 .

Learning Hierarchical Partially Observable Markov Decision Process Models for Robot Navigation

Sridhar Mahadevan, Georgios Theocharous, Khashayar Rohanimanesh, 2001 .

Hierarchical Reinforcement Learning Using Graphical Models

S. Mahadevan, Victoria Manfredi, 2022 .

Learning Representation and Control in Markov Decision Processes: New Frontiers

Sridhar Mahadevan, S. Mahadevan, 2009, Found. Trends Mach. Learn..

Action-based representation discovery in markov decision processes

S. Mahadevan, Sarah Osentoski, 2009 .

Compressive Reinforcement Learning with Oblique Random Projections

S. Mahadevan, Bo Liu, 2011 .

Quantifying Prior Determination Knowledge Using the PAC Learning Model

S. Mahadevan, Prasad Tadepalli, P. Tadepalli, 1994, Machine Learning.

Multiscale Manifold Learning

Chang Wang, Sridhar Mahadevan, S. Mahadevan, 2013, AAAI.

Global Convergence to the Equilibrium of GANs using Variational Inequalities pdf

Sridhar Mahadevan, Ian Gemp, S. Mahadevan, 2018, ArXiv.

Deep Generative Models for Spectroscopic Analysis on Mars pdf

Sridhar Mahadevan, Ian Gemp, Mario Parente, 2016, ArXiv.

Sparse Q-learning with Mirror Descent pdf

Bo Liu, Sridhar Mahadevan, S. Mahadevan, 2012, UAI.

Personalizing with Human Cognitive Biases

Jennifer Healey, Sridhar Mahadevan, Georgios Theocharous, 2019, UMAP.

Learning state-action basis functions for hierarchical MDPs

Sridhar Mahadevan, Sarah Osentoski, S. Mahadevan, 2007, ICML '07.

Online Monotone Games pdf

Sridhar Mahadevan, Ian Gemp, S. Mahadevan, 2017, ArXiv.

Hierarchical Average Reward Reinforcement Learning Hierarchical Average Reward Reinforcement Learning

M. Ghavamzadeh, S. Mahadevan, 2007 .

Errata Preface Recent Advances in Hierarchical Reinforcement Learning

A. Barto, S. Mahadevan, 2003 .

A Greedy Divide-and-Conquer Approach to Optimizing Large Manufacturing Systems using Reinforcement Learning

Sridhar Mahadevan, S. Mahadevan, Gang Wang, 1998 .

Report of the 1996 Workshop on Reinforcement Learning Sponsored by the National Science Foundation Preface and Acknowledgements

S. Mahadevan, L. Kaelbling, 2007 .

Nav RNav G Nav Y Root Cooperative Subtask Communicate Not −

M. Ghavamzadeh, S. Mahadevan, 2022 .

A geometric framework for transfer learning using manifold alignment

S. Mahadevan, Chang Wang, 2010 .

A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy

S. Mahadevan, S. Clegg, M. Dyar, 2015 .

N Average- Ent Learning Algorit Mot Ivat Ion

S. Mahadevan, 1999 .

Award FA 9550-10-1-0383 : Learning Representation and Control in Markov Decision Processes : Final Report

S. Mahadevan, 2009 .

Learning to Act using Concurrent Temporally Extended Actions

S. Mahadevan, Khashayar Rohanimanesh, 2007 .

Multiscale Manifold Alignment

S. Mahadevan, Chang Wang, 2010 .

Proximal methods for calibration transfer

S. Mahadevan, M. Dyar, T. Boucher, 2017 .

Learning Locality-Preserving Discriminative Features

S. Mahadevan, Chang Wang, 2010 .

Finding Equilibria in Large Games using Variational Inequalities

S. Mahadevan, I. Gemp, 2015 .

Manifold preprocessing for laser‐induced breakdown spectroscopy under Mars conditions

S. Mahadevan, S. Clegg, R. Wiens, 2015 .

An apprentice-based approach to learning problem-solving knowledge

Tom M. Mitchell, Sridhar Mahadevan, Tom Michael Mitchell, 1990 .

Face Recognition Using Foveal Vision

S. Mahadevan, J. Henderson, F. Dyer, 2000, Biologically Motivated Computer Vision.

Face Recognition Using Foveal Vision : Preliminary Report

S. Mahadevan, J. Henderson, F. Dyer, 2007 .

Kalman filters for prediction and tracking in an adaptive sensor network

Jim Kurose, Sridhar Mahadevan, Victoria Manfredi, 2005 .

Hierarchical multi-agent reinforcement learning

M. Ghavamzadeh, S. Mahadevan, R. Makar, 2001, Agents.

Hierarchical reinforcement learning in continuous state and multi-agent environments

M. Ghavamzadeh, S. Mahadevan, 2005 .

On The Universality of Diagrams for Causal Inference and The Causal Reproducing Property

S. Mahadevan, 2022, ArXiv.

Unifying Causal Inference and Reinforcement Learning using Higher-Order Category Theory

S. Mahadevan, 2022, ArXiv.

Automatic Whole-Spectrum Matching

Sridhar Mahadevan, Stephen Giguere, Thomas Boucher, 2015 .

Smoothed Online Combinatorial Optimization Using Imperfect Predictions

S. Mahadevan, Georgios Theocharous, Zhao Song, 2022, ArXiv.

U NIFYING C AUSAL I NFERENCE AND R EINFORCEMENT L EARNING USING H IGHER -O RDER C ATEGORY T HEORY ∗

S. Mahadevan, 2022 .

Manifold Alignment without Correspondence

S. Mahadevan, Chang Wang, 2009, IJCAI.

Concurrent decision making in markov decision processes

Sridhar Mahadevan, Khashayar Rohanimanesh, S. Mahadevan, 2006 .

11 Hierarchical Approaches to Concurrency , Multiagency , and Partial Observability

M. Ghavamzadeh, S. Mahadevan, Georgios Theocharous, 2004 .

Extending Hierarchical Reinforcement Learning to Continuous-Time, Average-Reward, and Multi-Agent Models

Sridhar Mahadevan, Mohammad Ghavamzadeh, Rajbala Makar, 2003 .

Spatiotemporal Abstraction of Stochastic Sequential Processes

S. Mahadevan, 2002, SARA.

A reinforcement learning model of selective visual attention

Sridhar Mahadevan, Silviu Minut, S. Mahadevan, 2001, AGENTS '01.

Imagination Machines: A New Challenge for Artificial Intelligence

Sridhar Mahadevan, S. Mahadevan, 2018, AAAI.

An Apprentice-Based Approach to Knowledge Acquisition

Tom M. Mitchell, Jack Mostow, Sridhar Mahadevan, 1993, Artif. Intell..

Heterogeneous Domain Adaptation Using Manifold Alignment

Chang Wang, Sridhar Mahadevan, S. Mahadevan, 2011, IJCAI.

Manifold Spanning Graphs

Sridhar Mahadevan, Clifton Carey, S. Mahadevan, 2014, AAAI.

Manifold alignment using Procrustes analysis

Sridhar Mahadevan, Chang Wang, S. Mahadevan, 2008, ICML '08.

Representation Discovery using Harmonic Analysis

Sridhar Mahadevan, S. Mahadevan, 2008, Representation Discovery using Harmonic Analysis.

Reconfigurable and Adaptable Micro-Robots

Ning Xi, Ranjan Mukherjee, R L Tummala, 2004 .

Universal Decision Models pdf

Sridhar Mahadevan, S. Mahadevan, 2021, ArXiv.

14 - Gaze Control for Face Learning and Recognition by Humans and Machines

Sridhar Mahadevan, John M. Henderson, Fred C. Dyer, 2001 .

Smoothed Online Combinatorial Optimization Using Imperfect Predictions

S. Mahadevan, Georgios Theocharous, Zhao Song, 2022, ArXiv.

Rapid Concept Learning for Mobile Robots

Sridhar Mahadevan, Georgios Theocharous, Nikfar Khaleeli, 2004, Machine Learning.

Rapid Concept Learning for Mobile Robots

Sridhar Mahadevan, Georgios Theocharous, Nikfar Khaleeli, 1998, Auton. Robots.

Representation Discovery in Sequential Decision Making

Sridhar Mahadevan, S. Mahadevan, 2010, AAAI.

Compressing POMDPs Using Locality Preserving Non-Negative Matrix Factorization

Sridhar Mahadevan, Georgios Theocharous, S. Mahadevan, 2010, AAAI.

Award FA 9550-10-1-0383 : Learning Representation and Control in Markov Decision Processes : Final Report

S. Mahadevan, 2009 .

Learning hierarchical observable Markov decision process models for robot navigation

Sridhar Mahadevan, Georgios Theocharous, Khashayar Rohanimanesh, 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

Face Recognition Using Foveal Vision

S. Mahadevan, J. Henderson, F. Dyer, 2000, Biologically Motivated Computer Vision.

A General Framework for Manifold Alignment

Chang Wang, Sridhar Mahadevan, S. Mahadevan, 2009, AAAI Fall Symposium: Manifold Learning and Its Applications.

Optimizing for the Future in Non-Stationary MDPs pdf

Sridhar Mahadevan, Philip S. Thomas, Georgios Theocharous, 2020, ICML.

Randomized and Deterministic Attention Sparsification Algorithms for Over-parameterized Feature Dimension

S. Mahadevan, Zhao Song, Yichuan Deng, 2023, ArXiv.

An Over-parameterized Exponential Regression

S. Mahadevan, Zhao Song, Yeqi Gao, 2023, ArXiv.

Machine learning tools formineral recognition and classification from Raman spectroscopy

Sridhar Mahadevan, Paul R. Bartholomew, Melinda Darby Dyar, 2014 .

A GPU-Based Approximate SVD Algorithm

Rui Wang, Sridhar Mahadevan, Blake Foster, 2011, PPAM.

Machine Learning for Robots A Comparison of Di erent Paradigms

Sridhar Mahadevan, S. Mahadevan, 2002 .

Efficient Hyper-parameter Optimization for NLP Applications

Bowen Zhou, Bing Xiang, Lidan Wang, 2015, EMNLP.

Probabilistic Plan Recognition in Multiagent Systems

Suchi Saria, Sridhar Mahadevan, S. Mahadevan, 2004, ICAPS.

A Unified Framework for Domain Adaptation using Metric Learning on Manifolds

Bamdev Mishra, Sridhar Mahadevan, Shalini Ghosh, 2018, ECML/PKDD.

A Variational Learning Algorithm for the Abstract Hidden Markov Model

Sridhar Mahadevan, Jeffrey Johns, S. Mahadevan, 2005, AAAI.

Learning to Plan Using Harmonic Analysis of Diffusion Models

Chang Wang, Sridhar Mahadevan, Sarah Osentoski, 2007, ICAPS.

Generative Multi-Adversarial Networks pdf

Sridhar Mahadevan, Ian Gemp, Ishan P. Durugkar, 2016, ICLR.

Fast direct policy evaluation using multiscale analysis of Markov diffusion processes

Sridhar Mahadevan, Mauro Maggioni, S. Mahadevan, 2006, ICML.

Continuous-Time Hierarchical Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2001, ICML.

Sparse Manifold Alignment

Sridhar Mahadevan, Bo Liu, S. Mahadevan, 2012 .

An Expert System for Assigning Patients into Clinical Trials Based on Bayesian Networks

Sridhar Mahadevan, Georgios Theocharous, S. Mahadevan, 1998, Journal of Medical Systems.

Learning Representation and Control in Continuous Markov Decision Processes

Sridhar Mahadevan, Sarah Osentoski, Mauro Maggioni, 2006, AAAI.

Spatial and Temporal Abstractions in POMDPs Applied to Robot Navigation

Leslie Pack Kaelbling, Sridhar Mahadevan, Georgios Theocharous, 2005 .

n Average- ent Learning Algorit

Sridhar Mahadevan, S. Mahadevan, 1996 .

Comparison of univariate and multivariate models for prediction of major and minor elements from laser-induced breakdown spectra with and without masking

Sridhar Mahadevan, Stephen Giguere, M. Darby Dyar, 2016 .

Zero-th Order Algorithm for Softmax Attention Optimization

S. Mahadevan, Zhihang Li, Yichuan Deng, 2023, ArXiv.

Hybrid least-squares algorithms for approximate policy evaluation

Marek Petrik, Sridhar Mahadevan, Jeffrey Johns, 2009, Machine Learning.

Proximal Gradient Temporal Difference Learning Algorithms

Marek Petrik, Bo Liu, Ji Liu, 2016, IJCAI.

Constructing basis functions from directed graphs for value function approximation

Sridhar Mahadevan, Jeffrey Johns, S. Mahadevan, 2007, ICML '07.

Sensitive Discount Optimality: Unifying Discounted and Average Reward Reinforcement Learning

Sridhar Mahadevan, S. Mahadevan, 1996, ICML.

Quantifying prior determination knowledge using the PAC learning model

Sridhar Mahadevan, Prasad Tadepalli, S. Mahadevan, 2004, Machine Learning.

Universal Causality

S. Mahadevan, 2023, Entropy.

Learning to Communicate and Act in Cooperative Multiagent Systems using Hierarchical Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2004 .

Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity pdf

Marek Petrik, Ji Liu, Bo Liu, 2018, J. Artif. Intell. Res..

Finite-Sample Analysis of GTD Algorithms pdf

Bo Liu, Ji Liu, Sridhar Mahadevan, 2020, ArXiv.

The National Science Foundation Workshop on Reinforcement Learning

Leslie Pack Kaelbling, Sridhar Mahadevan, S. Mahadevan, 1996, AI Mag..

Coarticulation: an approach for generating concurrent plans in Markov decision processes

Sridhar Mahadevan, Khashayar Rohanimanesh, S. Mahadevan, 2005, ICML.

Coarticulation in Markov Decision Processes

Robert Platt, Roderic A. Grupen, Sridhar Mahadevan, 2004, NIPS.

Deep Reinforcement Learning With Macro-Actions pdf

Sridhar Mahadevan, Stefan Dernbach, Clemens Rosenbaum, 2016, ArXiv.

Basis function construction for hierarchical reinforcement learning

Sridhar Mahadevan, Sarah Osentoski, S. Mahadevan, 2010, AAMAS.

Hierarchically Optimal Average Reward Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2002, ICML.

Representation Discovery in Planning using Harmonic Analysis

Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns, 2007, AAAI Fall Symposium: Computational Approaches to Representation Change during Learning and Development.

Learning to Cooperate using Hierarchical Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2006 .

Robust Mobile Robot Navigation using Partially-Observable Semi-Markov Decision Processes

Sridhar Mahadevan, Nikfar Khaleeli, S. Mahadevan, 1999 .

Projected Natural Actor-Critic

Sridhar Mahadevan, Philip S. Thomas, Stephen Giguere, 2013, NIPS.

A Study of Reinforcement Learning in the Continuous Case by the Means of Viscosity Solutions

S. Mahadevan, R. Emi Munos, 1999 .

Causal Homotopy pdf

Sridhar Mahadevan, S. Mahadevan, 2021, ArXiv.

Switching kalman filters for prediction and tracking in an adaptive meteorological sensing network

Sridhar Mahadevan, James F. Kurose, Victoria Manfredi, 2005, 2005 Second Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2005. IEEE SECON 2005..

Learning hierarchical models of activity

Sridhar Mahadevan, Sarah Osentoski, Victoria Manfredi, 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

Representation Policy Iteration

Sridhar Mahadevan, S. Mahadevan, 2005, UAI.

Estimating Student Proficiency Using an Item Response Theory Model

Beverly Park Woolf, Sridhar Mahadevan, Jeffrey Johns, 2006, Intelligent Tutoring Systems.

Solving Large Sustainable Supply Chain Networks Using Variational Inequalities

Bo Liu, Sridhar Mahadevan, Ian Gemp, 2015, AAAI Workshop: Computational Sustainability.

Modeling Context in Cognition Using Variational Inequalities

Sridhar Mahadevan, Ian Gemp, S. Mahadevan, 2014, AAAI Fall Symposia.

Machine learning tools formineral recognition and classification from Raman spectroscopy

S. Mahadevan, M. Dyar, C. Carey, 2014 .

The Protein Data Bank: A Case Study in Management of Community Data

Tom Michael Mitchell, S. Mahadevan, L. Steinberg, 2004 .