Ph.D. Dissertations - Stuart J. Russell

Efficient inference algorithms for near-deterministic systems
Shaunak Chatterjee [2013]

Model-based Bayesian Seismic Monitoring
Nimar S Arora [2012]

Hierarchical Methods for Optimal Long-Term Planning
Jason Wolfe [2011]

Nonparametric Hierarchical Bayesian Models of Categorization
Kevin Canini [2011]

Efficient Motor Control Learning
Gregory Donnell Lawrence [2009]

Probabilistic Models with Unknown Objects
Brian Christopher Milch [2006]

Exploiting Locality in Probabilistic Inference
Mark A. Paskin [2004]

Probabilistic Graphical Models and Algorithms for Genomic Analysis
Eric Poe Xing [2004]

Identity Uncertainty
Hanna M. Pasula [2003]

Programmable Reinforcement Learning Agents
David Andre [2003]

Value Determination with Function Approximation
Vassilis A. Papavassiliou [2003]

Dynamic Bayesian Networks: Representation, Inference and Learning
Kevin P. Murphy [2002]

Reinforcement Learning for Autonomous Vehicles
Jeffrey R. N. Forbes [2002]

Online Ensemble Learning
Nikunj C. Oza [2001]

Probabilistic Reasoning in Intelligent Vehicle Highway Systems
Timothy T.-M. Huang [1999]

Bayesian Problem-Solving Applied to Scheduling
Othar Hansson [1998]

Hierarchical Control and Learning for Markov Decision Processes
Ronald E. Parr [1998]

Speech Recognition with Dynamic Bayesian Networks
Geoffrey G. Zweig [1998]

Belief Network Induction
Charles Ronald Musick [1994]

Rational Search
Andrew E. Mayer [1994]

Operational Rationality through Compilation of Anytime Algorithms
Shlomo Zilberstein [1993]

RALPH-MEA: A Real-Time, Decision-Theoretic Agent Architecture
Gary Hayato Ogasawara [1993]

PAGODA: A Model for Autonomous Learning in Probabilistic Domains
Marie Ellen desJardins [1992]