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» Finite State Transducers Approximating Hidden Markov Models
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UAI
2004
14 years 11 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
105
Voted
ICML
2005
IEEE
15 years 11 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
96
Voted
ECML
2005
Springer
15 years 3 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
97
Voted
CVPR
1999
IEEE
16 years 7 days 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 4 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