454 citations · 5.5k across the 247 of their papers we have counts for
3 papers · 2 filters
Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation
Syogo Mori, Voot Tangkaratt, Tingting Zhao +2
The goal of reinforcement learning (RL) is to let an agent learn an optimal control policy in an unknown environment so that future expected rewards are maximized. The model-free R…
Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation
Song Liu, John A. Quinn, Michael U. Gutmann +2
We propose a new method for detecting changes in Markov network structure between two sets of samples. Instead of naively fitting two Markov network models separately to the two da…
Density Ratio Hidden Markov Models
John A. Quinn, Masashi Sugiyama
Hidden Markov models and their variants are the predominant sequential classification method in such domains as speech recognition, bioinformatics and natural language processing.…