A model for reasoning about persistence and causation
Computational Intelligence
The power of amnesia: learning probabilistic automata with variable memory length
Machine Learning - Special issue on COLT '94
Adaptive Probabilistic Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
Nonlinear manifold learning for visual speech recognition
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A Prefetching Protocol Using Client Speculation for the WWW
A Prefetching Protocol Using Client Speculation for the WWW
Characteristics of WWW Client-based Traces
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An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Hybrid modeling, hmm/nn architectures, and protein applications
Neural Computation
Bayesian Clustering by Dynamics
Machine Learning - Special issue: Unsupervised learning
Sequence Learning via Bayesian Clustering by Dynamics
Sequence Learning - Paradigms, Algorithms, and Applications
Rapid on-line temporal sequence prediction by an adaptive agent
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
MIST: distributed indexing and querying in sensor networks using statistical models
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Modeling interleaved hidden processes
Proceedings of the 25th international conference on Machine learning
Anticipatory Behavior in Adaptive Learning Systems
Force deployment analysis with generalized grammar
Information Fusion
Hierarchical group process representation in multi-agent activity recognition
Image Communication
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Non-stationary policy learning in 2-player zero sum games
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
VOGUE: A variable order hidden Markov model with duration based on frequent sequence mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
Product of Gaussians for speech recognition
Computer Speech and Language
Feature Fusion Applied to Missing Data ASR with the Combination of Recognizers
Journal of Signal Processing Systems
Burst detection from multiple data streams: a network-based approach
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Maximum likelihood estimation of feature-based distributions
SIGMORPHON '10 Proceedings of the 11th Meeting of the ACL Special Interest Group on Computational Morphology and Phonology
A generative score space for statistical dialog characterization in social signalling
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Bottom-up generative modeling of tree-structured data
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Statistical modelling in continuous speech recognition (CSR)
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
VOGUE: a novel variable order-gap state machine for modeling sequences
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Deconvolutive clustering of markov states
ECML'06 Proceedings of the 17th European conference on Machine Learning
Symbolic generalization for on-line planning
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Event prediction in a hybrid camera network
ACM Transactions on Sensor Networks (TOSN)
Detecting DDoS attacks based on multi-stream fused HMM in source-end network
CANS'06 Proceedings of the 5th international conference on Cryptology and Network Security
State aggregation in higher order markov chains for finding online communities
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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We study Markov models whose state spaces arise from the Cartesian product of two or more discrete random variables. We show how to parameterize the transition matrices of these models as a convex combination—or mixture—of simpler dynamical models. The parameters in these models admit a simple probabilistic interpretation and can be fitted iteratively by an Expectation-Maximization (EM) procedure. We derive a set of generalized Baum-Welch updates for factorial hidden Markov models that make use of this parameterization. We also describe a simple iterative procedure for approximately computing the statistics of the hidden states. Throughout, we give examples where mixed memory models provide a useful representation of complex stochastic processes.