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ICASSP
2011
IEEE
12 years 11 months ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur
ENTCS
2008
91views more  ENTCS 2008»
13 years 7 months ago
Expressing Priorities and External Probabilities in Process Algebra via Mixed Open/Closed Systems
Defining operational semantics for a process algebra is often based either on labeled transition systems that account for interaction with a context or on the so-called reduction ...
Mario Bravetti
ECML
2007
Springer
14 years 1 months ago
Policy Gradient Critics
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
Daan Wierstra, Jürgen Schmidhuber
CVPR
1998
IEEE
14 years 9 months ago
Action Recognition Using Probabilistic Parsing
A new approach to the recognition of temporal behaviors and activities is presented. The fundamental idea, inspired by work in speech recognition, is to divide the inference probl...
Aaron F. Bobick, Yuri A. Ivanov
CIKM
2009
Springer
14 years 2 months ago
A social recommendation framework based on multi-scale continuous conditional random fields
This paper addresses the issue of social recommendation based on collaborative filtering (CF) algorithms. Social recommendation emphasizes utilizing various attributes informatio...
Xin Xin, Irwin King, Hongbo Deng, Michael R. Lyu