454 citations · 5.5k across the 247 of their papers we have counts for
6 papers · 1 filter
Support Consistency of Direct Sparse-Change Learning in Markov Networks
Song Liu, Taiji Suzuki, Raissa Relator +3
We study the problem of learning sparse structure changes between two Markov networks and . Rather than fitting two Markov networks separately to two sets of data and figuri…
Direct Density-Derivative Estimation and Its Application in KL-Divergence Approximation
Hiroaki Sasaki, Yung-Kyun Noh, Masashi Sugiyama
Estimation of density derivatives is a versatile tool in statistical data analysis. A naive approach is to first estimate the density and then compute its derivative. However, such…
Efficient Reuse of Previous Experiences to Improve Policies in Real Environment
Norikazu Sugimoto, Voot Tangkaratt, Thijs Wensveen +3
In this study, we show that a movement policy can be improved efficiently using the previous experiences of a real robot. Reinforcement Learning (RL) is becoming a popular approach…
Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization
Voot Tangkaratt, Ning Xie, Masashi Sugiyama
Regression aims at estimating the conditional mean of output given input. However, regression is not informative enough if the conditional density is multimodal, heteroscedastic, a…
Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density
Hiroaki Sasaki, Aapo Hyvärinen, Masashi Sugiyama
Mean shift clustering finds the modes of the data probability density by identifying the zero points of the density gradient. Since it does not require to fix the number of cluster…
Transductive Learning with Multi-class Volume Approximation
Gang Niu, Bo Dai, Marthinus Christoffel du Plessis +1
Given a hypothesis space, the large volume principle by Vladimir Vapnik prioritizes equivalence classes according to their volume in the hypothesis space. The volume approximation…