Sridhar Mahadevan

发表

Reconfigurable and Adaptable Micro-Robots

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

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..

An Average-Reward Reinforcement Learning Algorithm for Computing Bias-Optimal Policies

Sridhar Mahadevan, 1996, AAAI/IAAI, Vol. 1.

Global Convergence to the Equilibrium of GANs using Variational Inequalities pdf

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

Manifold Spanning Graphs

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

Jointly Learning Data-Dependent Label and Locality-Preserving Projections

Chang Wang, Sridhar Mahadevan, 2011, IJCAI.

Hierarchical learning and planning in partially observable markov decision processes

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

Online Monotone Optimization pdf

Sridhar Mahadevan, Ian Gemp, 2016, ArXiv.

Coarticulation in Markov Decision Processes

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

Inverting VAEs for Improved Generative Accuracy

Sridhar Mahadevan, Ian Gemp, 2017 .

An Apprentice-Based Approach to Knowledge Acquisition

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

Hybrid Least-Squares Algorithms for Approximate Policy Evaluation

Marek Petrik, Sridhar Mahadevan, Jeffrey Johns, 2009, ECML/PKDD.

Sensitive Discount Optimality: Unifying Discounted and Average Reward Reinforcement Learning

Sridhar Mahadevan, S. Mahadevan, 1996, ICML.

Multiscale Dimensionality Reduction Based on Diffusion Wavelets

Chang Wang, Sridhar Mahadevan, 2009 .

Hierarchical Average Reward Reinforcement Learning

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2007, J. Mach. Learn. Res..

The NSF Workshop on Reinforcement Learning: Summary and Observations

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

Hierarchical Optimization of Policy-Coupled Semi-Markov Decision Processes

Gang Wang, Sridhar Mahadevan, S. Mahadevan, 1999, ICML.

Optimizing Production Manufacturing Using Reinforcement Learning

Sridhar Mahadevan, Georgios Theocharous, S. Mahadevan, 1998, FLAIRS.

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).

Using Determinations in EBL: A Solution to the incomplete Theory Problem

Sridhar Mahadevan, 1989, ML.

Deep Reinforcement Learning With Macro-Actions pdf

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

DROP: Facilitating distributed metadata management in EB-scale storage systems

Sridhar Mahadevan, Quanqing Xu, Rajesh Vellore Arumugam, 2013, 2013 IEEE 29th Symposium on Mass Storage Systems and Technologies (MSST).

Personalizing with Human Cognitive Biases

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

Hierarchical Policy Gradient Algorithms

Sridhar Mahadevan, Mohammad Ghavamzadeh, M. Ghavamzadeh, 2003, ICML.

Hierarchical Multiagent Reinforcement Learning

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

Rapid Concept Learning for Mobile Robots

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

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.

A Manifold Approach to Learning Mutually Orthogonal Subspaces pdf

Sridhar Mahadevan, Francisco Garcia, Stephen Giguere, 2017, ArXiv.

Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces pdf

Bo Liu, Ji Liu, Sridhar Mahadevan, 2014, ArXiv.

Kalman filters for prediction and tracking in an adaptive sensor network

Jim Kurose, Sridhar Mahadevan, Victoria Manfredi, 2005 .

Improving Intelligent Tutoring Systems: Using Expectation Maximization to Learn Student Skill Levels

Beverly Park Woolf, Sridhar Mahadevan, Andrew G. Barto, 2006, Intelligent Tutoring Systems.

Enhancing Transfer in Reinforcement Learning by Building Stochastic Models of Robot Actions

Sridhar Mahadevan, S. Mahadevan, 1992, ML.

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).

Scaling Reinforcement Learning to Robotics by Exploiting the Subsumption Architecture

Sridhar Mahadevan, Jonathan H. Connell, S. Mahadevan, 1991, ML.

Sparse Q-learning with Mirror Descent pdf

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

Self-Improving Factory Simulation using Continuous-time Average-Reward Reinforcement Learning

Abhijit Gosavi, Tapas K. Das, Sridhar Mahadevan, 2007 .

Robot Learning

Sridhar Mahadevan, Jonathan H. Connell, S. Mahadevan, 1993 .

Proximal Gradient Temporal Difference Learning Algorithms

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

Aligning Mixed Manifolds

Sridhar Mahadevan, Melinda Darby Dyar, Thomas Boucher, 2015, AAAI.

A Unified Framework for Domain Adaptation using Metric Learning on Manifolds

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

Representation Discovery using Harmonic Analysis

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

Estimating Student Proficiency Using an Item Response Theory Model

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

A multiagent reinforcement learning algorithm by dynamically merging markov decision processes

Sridhar Mahadevan, Mohammad Ghavamzadeh, 2002, AAMAS '02.

A Fully Customized Baseline Removal Framework for Spectroscopic Applications

Sridhar Mahadevan, Stephen Giguere, Thomas Boucher, 2017, Applied spectroscopy.

Hybrid least-squares algorithms for approximate policy evaluation

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

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

Sridhar Mahadevan, S. Mahadevan, 1994, ICML.

Adaptive mesh compression in 3D computer graphics using multiscale manifold learning

Sridhar Mahadevan, 2007, ICML '07.

A General Framework for Manifold Alignment

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

Recent Advances in Hierarchical Reinforcement Learning

Sridhar Mahadevan, Andrew G. Barto, A. Barto, 2003, Discret. Event Dyn. Syst..

Manifold Alignment Preserving Global Geometry

Chang Wang, Sridhar Mahadevan, 2013, IJCAI.

Inverting Variational Autoencoders for Improved Generative Accuracy

Sridhar Mahadevan, Ian Gemp, M. Darby Dyar, 2016 .

Spatiotemporal Abstraction of Stochastic Sequential Processes

Sridhar Mahadevan, 2002, SARA.

Spatial and Temporal Abstractions in POMDPs Applied to Robot Navigation

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

Hierarchical multi-agent reinforcement learning

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

Modeling Context in Cognition Using Variational Inequalities

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

An apprentice-based approach to learning problem-solving knowledge

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

Representation Policy Iteration

Sridhar Mahadevan, S. Mahadevan, 2005, UAI.

LEAP: A Learning Apprentice for VLSI Design

Tom M. Mitchell, Sridhar Mahadevan, Louis I. Steinberg, 1985, IJCAI.

Verification-based Learning: A Generalized Strategy for Inferring Problem-Reduction Methods

Sridhar Mahadevan, S. Mahadevan, 1985, IJCAI.

A GPU-Based Approximate SVD Algorithm

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

Fast Spectral Learning using Lanczos Eigenspace Projections

Sridhar Mahadevan, 2008, AAAI.

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).

A learning apprentice system for VLSI design

Tom M. Mitchell, Sridhar Mahadevan, Louis I. Steinberg, 1986 .

Recent Advances in Hierarchical Reinforcement Learning

Sridhar Mahadevan, Andrew G. Barto, A. Barto, 2003, Discret. Event Dyn. Syst..

Compact Spectral Bases for Value Function Approximation Using Kronecker Factorization

Chang Wang, Sridhar Mahadevan, Jeffrey Johns, 2007, AAAI.

Learning state-action basis functions for hierarchical MDPs

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

On the Tractability of Learning from Incomplete Theories

Sridhar Mahadevan, Prasad Tadepalli, 1988, ML.

Hierarchical Memory-Based Reinforcement Learning

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

Basis Adaptation for Sparse Nonlinear Reinforcement Learning

Sridhar Mahadevan, Stephen Giguere, Nicholas Jacek, 2013, AAAI.

Learning Representation and Control in Continuous Markov Decision Processes

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

Automatic Programming of Behavior-Based Robots Using Reinforcement Learning

Sridhar Mahadevan, Jonathan H. Connell, S. Mahadevan, 1991, Artif. Intell..

Machine Learning for Robots A Comparison of Di erent Paradigms

Sridhar Mahadevan, S. Mahadevan, 2002 .

Verification-based learning: a generalisation strategy for inferring problem-reduction methods

Sridhar Mahadevan, S. Mahadevan, 1985, IJCAI 1985.

Learning to Plan Using Harmonic Analysis of Diffusion Models

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

Manifold alignment using Procrustes analysis

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

Average reward reinforcement learning: Foundations, algorithms, and empirical results

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

Learning the hierarchical structure of spatial environments using multiresolution statistical models

Sridhar Mahadevan, Georgios Theocharous, 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

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

Sridhar Mahadevan, S. Mahadevan, 2005, AAAI.

Evaluating the Feasibility of Learning Student Models from Data

Hasmik Mehranian, Donald L. Fisher, Beverly Park Woolf, 2005 .

Learning Hierarchical Partially Observable Markov Decision Process Models for Robot Navigation

Sridhar Mahadevan, Georgios Theocharous, Khashayar Rohanimanesh, 2001 .

Repairing Disengagement With Non-Invasive Interventions

Beverly Park Woolf, Sridhar Mahadevan, Andrew G. Barto, 2007, AIED.

The National Science Foundation Workshop on Reinforcement Learning

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

Machine learning tools for mineral recognition and

Sridhar Mahadevan, Paul R. Bartholomew, Melinda Darby Dyar, 2015 .

Hierarchical multi-agent reinforcement learning

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

Heterogeneous Domain Adaptation Using Manifold Alignment

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

Basis function construction for hierarchical reinforcement learning

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

Applying Machine Learning to Star Cluster Classification

Sridhar Mahadevan, K. Grasha, Kristina Fedorenko, 2016 .

Projected Natural Actor-Critic

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

Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes

Sridhar Mahadevan, Mauro Maggioni, S. Mahadevan, 2007, J. Mach. Learn. Res..

Finite-Sample Analysis of GTD Algorithms pdf

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

Generative Multi-Adversarial Networks pdf

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

Learning to Take Concurrent Actions

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

A Variational Learning Algorithm for the Abstract Hidden Markov Model

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

Rapid Concept Learning for Mobile Robots

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

Imagination Machines: A New Challenge for Artificial Intelligence

Sridhar Mahadevan, S. Mahadevan, 2018, AAAI.

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

Sridhar Mahadevan, Mohammad Ghavamzadeh, Rajbala Makar, 2003 .

Fast direct policy evaluation using multiscale analysis of Markov diffusion processes

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

Extraction of Key Words from News Stories

James Allan, Ramesh Nallapati, Sridhar Mahadevan, 2004 .

Rapid Task Learning for Real Robots

Sridhar Mahadevan, Jonathan H. Connell, S. Mahadevan, 1993 .

Basis Construction from Power Series Expansions of Value Functions

Bo Liu, Sridhar Mahadevan, S. Mahadevan, 2010, NIPS.

Efficient and Scalable Metadata Management in EB-Scale File Systems

Sridhar Mahadevan, Quanqing Xu, Rajesh Vellore Arumugam, 2014, IEEE Transactions on Parallel and Distributed Systems.

Finite-Sample Analysis of Proximal Gradient TD Algorithms

Marek Petrik, Bo Liu, Ji Liu, 2015, UAI.

n Average- ent Learning Algorit

Sridhar Mahadevan, S. Mahadevan, 1996 .

Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions

Sridhar Mahadevan, Mauro Maggioni, S. Mahadevan, 2005, NIPS.

Representation Discovery in Sequential Decision Making

Sridhar Mahadevan, S. Mahadevan, 2010, AAAI.

Regularized Off-Policy TD-Learning

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

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

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

Hierarchically Optimal Average Reward Reinforcement Learning

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

Constructing basis functions from directed graphs for value function approximation

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

Multiscale analysis of document corpora based on diffusion models

Sridhar Mahadevan, Chang Wang, 2009, IJCAI 2009.

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

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

Online Monotone Games pdf

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

Concurrent decision making in markov decision processes

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

Efficient Hyper-parameter Optimization for NLP Applications

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

Learning to communicate and act using hierarchical reinforcement learning

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

Optimizing for the Future in Non-Stationary MDPs pdf

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

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

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

Deep Generative Models for Spectroscopic Analysis on Mars pdf

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

Transfer Learning and Representation Discovery in Intelligent Tutoring Systems

Beverly Park Woolf, Sridhar Mahadevan, Kimberly Ferguson, 2009, AIED.

Manifold Warping: Manifold Alignment over Time

Sridhar Mahadevan, Clifton Carey, Hoa Trong Vu, 2012, AAAI.

Machine learning tools formineral recognition and classification from Raman spectroscopy

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