77 citations · 732 across the 55 of their papers we have counts for
6 papers · 1 filter
Online and Distributed learning of Gaussian mixture models by Bayesian Moment Matching
Priyank Jaini, Pascal Poupart
The Gaussian mixture model is a classic technique for clustering and data modeling that is used in numerous applications. With the rise of big data, there is a need for parameter e…
Exploiting Structure in Weighted Model Counting Approaches to Probabilistic Inference
Wei Li, Pascal Poupart, Peter van Beek
Previous studies have demonstrated that encoding a Bayesian network into a SAT formula and then performing weighted model counting using a backtracking search algorithm can be an e…
Value-Directed Sampling Methods for POMDPs
Pascal Poupart, Luis E. Ortiz, Craig Boutilier
We consider the problem of approximate belief-state monitoring using particle filtering for the purposes of implementing a policy for a partially-observable Markov decision process…
Vector-space Analysis of Belief-state Approximation for POMDPs
Pascal Poupart, Craig Boutilier
We propose a new approach to value-directed belief state approximation for POMDPs. The value-directed model allows one to choose approximation methods for belief state monitoring t…
Hierarchical POMDP Controller Optimization by Likelihood Maximization
Marc Toussaint, Laurent Charlin, Pascal Poupart
Planning can often be simpli ed by decomposing the task into smaller tasks arranged hierarchically. Charlin et al. [4] recently showed that the hierarchy discovery problem can be f…
Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker
Farheen Omar, Mathieu Sinn, Jakub Truszkowski +3
Rollating walkers are popular mobility aids used by older adults to improve balance control. There is a need to automatically recognize the activities performed by walker users to…