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» Finite State Transducers Approximating Hidden Markov Models
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UAI
2004
15 years 6 months ago
Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences
We present a new method for nonlinear prediction of discrete random sequences under minimal structural assumptions. We give a mathematical construction for optimal predictors of s...
Cosma Rohilla Shalizi, Kristina Lisa Shalizi
ICML
2005
IEEE
16 years 5 months ago
Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM
This paper explores the issue of recognizing, generalizing and reproducing arbitrary gestures. We aim at extracting a representation that encapsulates only the key aspects of the ...
Sylvain Calinon, Aude Billard
172
Voted
ECML
2005
Springer
15 years 10 months ago
Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
Masoumeh T. Izadi, Doina Precup
CVPR
1999
IEEE
16 years 7 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
AVSS
2008
IEEE
15 years 11 months ago
Object and Scene-Centric Activity Detection Using State Occupancy Duration Modeling
We propose a video event analysis framework based on object segmentation and tracking, combined with a Hidden Semi-Markov Model (HSMM) that uses state occupancy duration modeling....
Murtaza Taj, Andrea Cavallaro