Ronald Parr

2008
33	EE	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: 752-759
2007
32		Shihao Ji, Ronald Parr, Hui Li, Xuejun Liao, Lawrence Carin: Point-Based Policy Iteration. AAAI 2007: 1243-1249
31	EE	Ronald Parr, Christopher Painter-Wakefield, Lihong Li, Michael L. Littman: Analyzing feature generation for value-function approximation. ICML 2007: 737-744
30	EE	Shihao Ji, Ronald Parr, Lawrence Carin: Nonmyopic Multiaspect Sensing With Partially Observable Markov Decision Processes. IEEE Transactions on Signal Processing 55(6-1): 2720-2730 (2007)
2006
29	EE	Monika Schaeffer, Ronald Parr: Efficient Selection of Disambiguating Actions for Stereo Vision. UAI 2006
2005
28	EE	Austin I. Eliazar, Ronald Parr: Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps. NIPS 2005
2004
27	EE	Austin I. Eliazar, Ronald Parr: Learning probabilistic motion models for mobile robots. ICML 2004
26	EE	Austin I. Eliazar, Ronald Parr: DP-SLAM 2.0. ICRA 2004: 1314-1320
2003
25		Michail G. Lagoudakis, Ronald Parr: Reinforcement Learning as Classification: Leveraging Modern Classifiers. ICML 2003: 424-431
24		Austin I. Eliazar, Ronald Parr: DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks. IJCAI 2003: 1135-1142
23		Michail G. Lagoudakis, Ronald Parr: Approximate Policy Iteration using Large-Margin Classifiers. IJCAI 2003: 1432-1434
22	EE	Carlos Guestrin, Daphne Koller, Ronald Parr, Shobha Venkataraman: Efficient Solution Algorithms for Factored MDPs. J. Artif. Intell. Res. (JAIR) 19: 399-468 (2003)
21	EE	Michail G. Lagoudakis, Ronald Parr: Least-Squares Policy Iteration. Journal of Machine Learning Research 4: 1107-1149 (2003)
2002
20		Carlos Guestrin, Michail G. Lagoudakis, Ronald Parr: Coordinated Reinforcement Learning. ICML 2002: 227-234
19	EE	Michail G. Lagoudakis, Ronald Parr: Learning in Zero-Sum Team Markov Games Using Factored Value Functions. NIPS 2002: 1627-1634
18	EE	Michail G. Lagoudakis, Ronald Parr, Michael L. Littman: Least-Squares Methods in Reinforcement Learning for Control. SETN 2002: 249-260
17		Michail G. Lagoudakis, Ronald Parr: Value Function Approximation in Zero-Sum Markov Games. UAI 2002: 283-292
16	EE	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: 442-453
2001
15		Carlos Guestrin, Daphne Koller, Ronald Parr: Max-norm Projections for Factored MDPs. IJCAI 2001: 673-682
14	EE	Carlos Guestrin, Daphne Koller, Ronald Parr: Multiagent Planning with Factored MDPs. NIPS 2001: 1523-1530
13	EE	Michail G. Lagoudakis, Ronald Parr: Model-Free Least-Squares Policy Iteration. NIPS 2001: 1547-1554
12	EE	Uri Lerner, Ronald Parr: Inference in Hybrid Networks: Theoretical Limits and Practical Algorithms. UAI 2001: 310-318
2000
11		Urszula Chajewska, Daphne Koller, Ronald Parr: Making Rational Decisions Using Adaptive Utility Elicitation. AAAI/IAAI 2000: 363-369
10		Uri Lerner, Ronald Parr, Daphne Koller, Gautam Biswas: Bayesian Fault Detection and Diagnosis in Dynamic Systems. AAAI/IAAI 2000: 531-537
9	EE	Daphne Koller, Ronald Parr: Policy Iteration for Factored MDPs. UAI 2000: 326-334
1999
8		Daphne Koller, Ronald Parr: Computing Factored Value Functions for Policies in Structured MDPs. IJCAI 1999: 1332-1339
7	EE	Andrew Y. Ng, Ronald Parr, Daphne Koller: Policy Search via Density Estimation. NIPS 1999: 1022-1028
6	EE	Andrés Rodríguez, Ronald Parr, Daphne Koller: Reinforcement Learning Using Approximate Belief States. NIPS 1999: 1036-1042
1998
5	EE	Ronald Parr: Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems. UAI 1998: 422-430
1997
4		David Andre, Nir Friedman, Ronald Parr: Generalized Prioritized Sweeping. NIPS 1997
3		Ronald Parr, Stuart J. Russell: Reinforcement Learning with Hierarchies of Machines. NIPS 1997
1995
2		Ronald Parr, Stuart J. Russell: Approximating Optimal Policies for Partially Observable Stochastic Domains. IJCAI 1995: 1088-1095
1993
1		Stuart J. Russell, Devika Subramanian, Ronald Parr: Provably Bounded Optimal Agents. IJCAI 1993: 338-345

Coauthor Index

1	David Andre	[4]
2	Gautam Biswas	[10]
3	Lawrence Carin	[30] [32]
4	Urszula Chajewska	[11]
5	Austin I. Eliazar	[24] [26] [27] [28]
6	Nir Friedman	[4]
7	Carlos Guestrin	[14] [15] [20] [22]
8	Shihao Ji	[30] [32]
9	Daphne Koller	[6] [7] [8] [9] [10] [11] [14] [15] [22]
10	Michail G. Lagoudakis	[13] [17] [18] [19] [20] [21] [23] [25]
11	Uri Lerner	[10] [12]
12	Hui Li	[32]
13	Lihong Li	[31] [33]
14	Xuejun Liao	[32]
15	Lipyeow Lim	[16]
16	Michael L. Littman	[18] [31] [33]
17	Andrew Y. Ng	[7]
18	Sriram Padmanabhan	[16]
19	Christopher Painter-Wakefield	[31] [33]
20	Andrés Rodríguez	[6]
21	Stuart J. Russell	[1] [2] [3]
22	Monika Schaeffer	[29]
23	Devika Subramanian	[1]
24	Gavin Taylor	[33]
25	Shobha Venkataraman	[22]
26	Jeffrey Scott Vitter	[16]
27	Min Wang	[16]

Colors in the list of coauthors