Ronald Parr

Publication Activity (10 Years)

Years Active: 1993-2024
Publications (10 Years): 11

Top Topics

Relational Domains

Learning Models

Partial Observability

Decision Process

Top Venues

Publications

Cameron Allen, Aaron Kirtland, Ruo Yu Tao, Sam Lobel, Daniel Scott, Nicholas Petrocelli, Omer Gottesman, Ronald Parr, Michael L. Littman, George Konidaris
Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy. CoRR (2024)
Sam Lobel, Ronald Parr
An Optimal Tightness Bound for the Simulation Lemma. CoRR (2024)
Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo I. Seltzer, Ronald Parr, Jiachang Liu, Srikar Katta, Jon Donnelly, Harry Chen, Zachery Boner
Amazing Things Come From Having Many Good Models. CoRR (2024)
Lesia Semenova, Harry Chen, Ronald Parr, Cynthia Rudin
A Path to Simpler Models Starts With Noise. CoRR (2023)
Lesia Semenova, Harry Chen, Ronald Parr, Cynthia Rudin
A Path to Simpler Models Starts With Noise. NeurIPS (2023)
Lesia Semenova, Cynthia Rudin, Ronald Parr
On the Existence of Simpler Machine Learning Models. FAccT (2022)
Srijita Das, Sriraam Natarajan, Kaushik Roy, Ronald Parr, Kristian Kersting
Fitted Q-Learning for Relational Domains. CoRR (2020)
Zhao Song, Ronald Parr, Lawrence Carin
Revisiting the Softmax Bellman Operator: New Benefits and New Perspective. ICML (2019)
Benjamin Burchfiel, Carlo Tomasi, Ronald Parr
Distance Minimization for Reward Learning from Scored Trajectories. AAAI (2016)
Jason Pazis, Ronald Parr, Jonathan P. How
Improving PAC Exploration Using the Median Of Means. NIPS (2016)
Jason Pazis, Ronald Parr
Efficient PAC-Optimal Exploration in Concurrent, Continuous State MDPs with Delayed Updates. AAAI (2016)
Julian Mason, Bhaskara Marthi, Ronald Parr
Unsupervised discovery of object classes with a mobile robot. ICRA (2014)
Jason Pazis, Ronald Parr
Sample Complexity and Performance Bounds for Non-Parametric Approximate Linear Programming. AAAI (2013)
Michail G. Lagoudakis, Ronald Parr
Value Function Approximation in Zero-Sum Markov Games CoRR (2013)
Daphne Koller, Ronald Parr
Policy Iteration for Factored MDPs CoRR (2013)
Ronald Parr
Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems CoRR (2013)
Uri Lerner, Ronald Parr
Inference in Hybrid Networks: Theoretical Limits and Practical Algorithms CoRR (2013)
Jason Pazis, Ronald Parr
PAC Optimal Exploration in Continuous Space Markov Decision Processes. AAAI (2013)
Gavin Taylor, Ronald Parr
Value Function Approximation in Noisy Environments Using Locally Smoothed Regularized Approximate Linear Programs. UAI (2012)
Gavin Taylor, Ronald Parr
Value Function Approximation in Noisy Environments Using Locally Smoothed Regularized Approximate Linear Programs CoRR (2012)
Joshua Letchford, Liam MacDermed, Vincent Conitzer, Ronald Parr, Charles L. Isbell Jr.
Computing Stackelberg strategies in stochastic games. SIGecom Exch. 11 (2) (2012)
Ronald Parr, Linda C. van der Gaag
Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (2007) CoRR (2012)
Julian Mason, Bhaskara Marthi, Ronald Parr
Object disappearance for object discovery. IROS (2012)
Christopher Painter-Wakefield, Ronald Parr
Greedy Algorithms for Sparse Reinforcement Learning. ICML (2012)
Joshua Letchford, Liam MacDermed, Vincent Conitzer, Ronald Parr, Charles L. Isbell Jr.
Computing Optimal Strategies to Commit to in Stochastic Games. AAAI (2012)
Monika Schaeffer, Ronald Parr
Efficient Selection of Disambiguating Actions for Stereo Vision. CoRR (2012)
Julian Mason, Susanna Ricco, Ronald Parr
Textured occupancy grids for monocular localization without features. ICRA (2011)
Carlos Guestrin, Daphne Koller, Ronald Parr, Shobha Venkataraman
Efficient Solution Algorithms for Factored MDPs CoRR (2011)
Jason Pazis, Ronald Parr
Generalized Value Functions for Large Action Sets. ICML (2011)
Dmytro Korzhyk, Vincent Conitzer, Ronald Parr
Security Games with Multiple Attacker Resources. IJCAI (2011)
Dmytro Korzhyk, Vincent Conitzer, Ronald Parr
Solving Stackelberg games with uncertain observability. AAMAS (2011)
Jason Pazis, Ronald Parr
Non-Parametric Approximate Linear Programming for MDPs. AAAI (2011)
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zilberstein
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes. ICML (2010)
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zilberstein
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes CoRR (2010)
Dmytro Korzhyk, Vincent Conitzer, Ronald Parr
Complexity of Computing Optimal Stackelberg Strategies in Security Resource Allocation Games. AAAI (2010)
Jeffrey Johns, Christopher Painter-Wakefield, Ronald Parr
Linear Complementarity for Regularized Policy Evaluation and Improvement. NIPS (2010)
Erik Halvorson, Ronald Parr
Counting Objects with a Combination of Horizontal and Overhead Sensors. Int. J. Robotics Res. 29 (7) (2010)
Erik Halvorson, Vincent Conitzer, Ronald Parr
Multi-Step Multi-Sensor Hider-Seeker Games. IJCAI (2009)
Gavin Taylor, Ronald Parr
Kernelized value function approximation for reinforcement learning. ICML (2009)
Erik Halvorson, Ronald Parr
Planning Aims for a Network of Horizontal and Overhead Sensors. WAFR (2008)
Ronald Parr, Lihong Li, Gavin Taylor, Christopher Painter-Wakefield, Michael L. Littman
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning. ICML (2008)
Erik Halvorson, Ronald Parr
Planning Aims for a Network of Horizontal and Overhead Sensors. ISAIM (2008)
Shihao Ji, Ronald Parr, Lawrence Carin
Nonmyopic Multiaspect Sensing With Partially Observable Markov Decision Processes. IEEE Trans. Signal Process. 55 (6-1) (2007)
Ronald Parr, Christopher Painter-Wakefield, Lihong Li, Michael L. Littman
Analyzing feature generation for value-function approximation. ICML (2007)
Shihao Ji, Ronald Parr, Hui Li, Xuejun Liao, Lawrence Carin
Point-Based Policy Iteration. AAAI (2007)
Monika Schaeffer, Ronald Parr
Efficient Selection of Disambiguating Actions for Stereo Vision. UAI (2006)
Austin I. Eliazar, Ronald Parr
Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps. NIPS (2005)
Austin I. Eliazar, Ronald Parr
Learning probabilistic motion models for mobile robots. ICML (2004)
Austin I. Eliazar, Ronald Parr
DP-SLAM 2.0. ICRA (2004)
Austin I. Eliazar, Ronald Parr
DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks. IJCAI (2003)
Carlos Guestrin, Daphne Koller, Ronald Parr, Shobha Venkataraman
Efficient Solution Algorithms for Factored MDPs. J. Artif. Intell. Res. 19 (2003)
Michail G. Lagoudakis, Ronald Parr
Least-Squares Policy Iteration. J. Mach. Learn. Res. 4 (2003)
Michail G. Lagoudakis, Ronald Parr
Reinforcement Learning as Classification: Leveraging Modern Classifiers. ICML (2003)
Michail G. Lagoudakis, Ronald Parr
Approximate Policy Iteration using Large-Margin Classifiers. IJCAI (2003)
Michail G. Lagoudakis, Ronald Parr, Michael L. Littman
Least-Squares Methods in Reinforcement Learning for Control. SETN (2002)
Carlos Guestrin, Michail G. Lagoudakis, Ronald Parr
Coordinated Reinforcement Learning. ICML (2002)
Michail G. Lagoudakis, Ronald Parr
Value Function Approximation in Zero-Sum Markov Games. UAI (2002)
Lipyeow Lim, Min Wang, Sriram Padmanabhan, Jeffrey Scott Vitter, Ronald Parr
XPathLearner: An On-line Self-Tuning Markov Histogram for XML Path Selectivity Estimation. VLDB (2002)
Michail G. Lagoudakis, Ronald Parr
Learning in Zero-Sum Team Markov Games Using Factored Value Functions. NIPS (2002)
Carlos Guestrin, Daphne Koller, Ronald Parr
Multiagent Planning with Factored MDPs. NIPS (2001)
Michail G. Lagoudakis, Ronald Parr
Model-Free Least-Squares Policy Iteration. NIPS (2001)
Uri Lerner, Ronald Parr
Inference in Hybrid Networks: Theoretical Limits and Practical Algorithms. UAI (2001)
Carlos Guestrin, Daphne Koller, Ronald Parr
Max-norm Projections for Factored MDPs. IJCAI (2001)
Uri Lerner, Ronald Parr, Daphne Koller, Gautam Biswas
Bayesian Fault Detection and Diagnosis in Dynamic Systems. AAAI/IAAI (2000)
Urszula Chajewska, Daphne Koller, Ronald Parr
Making Rational Decisions Using Adaptive Utility Elicitation. AAAI/IAAI (2000)
Daphne Koller, Ronald Parr
Policy Iteration for Factored MDPs. UAI (2000)
Daphne Koller, Ronald Parr
Computing Factored Value Functions for Policies in Structured MDPs. IJCAI (1999)
Andrew Y. Ng, Ronald Parr, Daphne Koller
Policy Search via Density Estimation. NIPS (1999)
Andres C. Rodriguez, Ronald Parr, Daphne Koller
Reinforcement Learning Using Approximate Belief States. NIPS (1999)
Ronald Parr
Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems. UAI (1998)
David Andre, Nir Friedman, Ronald Parr
Generalized Prioritized Sweeping. NIPS (1997)
Ronald Parr, Stuart J. Russell
Reinforcement Learning with Hierarchies of Machines. NIPS (1997)
Ronald Parr, Stuart J. Russell
Approximating Optimal Policies for Partially Observable Stochastic Domains. IJCAI (1995)
Stuart J. Russell, Devika Subramanian, Ronald Parr
Provably Bounded Optimal Agents. IJCAI (1993)