226 citations · 686 across the 13 of their papers we have counts for
13 papers
Matroids Hitting Sets and Unsupervised Dependency Grammar Induction
Nicholas Harvey, Vahab Mirrokni, David Karger +2
This paper formulates a novel problem on graphs: find the minimal subset of edges in a fully connected graph, such that the resulting graph contains all spanning trees for a set of…
Learning to Cooperate via Policy Search
Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau +1
Cooperative games are those in which both agents share the same payoff structure. Value-based reinforcement-learning algorithms, such as variants of Q-learning, have been applied t…
Learning Finite-State Controllers for Partially Observable Environments
Nicolas Meuleau, Leonid Peshkin, Kee-Eung Kim +1
Reactive (memoryless) policies are sufficient in completely observable Markov decision processes (MDPs), but some kind of memory is usually necessary for optimal control of a parti…
Factored Particles for Scalable Monitoring
Brenda Ng, Leonid Peshkin, Avi Pfeffer
Exact monitoring in dynamic Bayesian networks is intractable, so approximate algorithms are necessary. This paper presents a new family of approximate monitoring algorithms that co…
Reinforcement Learning for Adaptive Routing
Leonid Peshkin, Virginia Savova
Reinforcement learning means learning a policy--a mapping of observations into actions--based on feedback from the environment. The learning can be viewed as browsing a set of poli…
Dependency Parsing with Dynamic Bayesian Network
Virginia Savova, Leonid Peshkin
Exact parsing with finite state automata is deemed inappropriate because of the unbounded non-locality languages overwhelmingly exhibit. We propose a way to structure the parsing t…