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ICML
2004
IEEE
14 years 9 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
ICML
2009
IEEE
14 years 9 months ago
Nonparametric factor analysis with beta process priors
We propose a nonparametric extension to the factor analysis problem using a beta process prior. This beta process factor analysis (BPFA) model allows for a dataset to be decompose...
John William Paisley, Lawrence Carin
ECML
2005
Springer
14 years 2 months ago
U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...
IJCAI
2007
13 years 10 months ago
Bayesian Tensor Inference for Sketch-Based Facial Photo Hallucination
This paper develops a statistical inference approach, Bayesian Tensor Inference, for style transformation between photo images and sketch images of human faces. Motivated by the r...
Wei Liu, Xiaoou Tang, Jianzhuang Liu
ICML
2007
IEEE
14 years 9 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...