A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Matrix computations (3rd ed.)
The handbook of brain theory and neural networks
Discrete-time, Discrete-valued Observable Operator Models: a Tutorial
Discrete-time, Discrete-valued Observable Operator Models: a Tutorial
Machine Learning
RoboCup 2000: Robot Soccer World Cup IV
Learning and discovery of predictive state representations in dynamical systems with reset
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Learning low dimensional predictive representations
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Blind construction of optimal nonlinear recursive predictors for discrete sequences
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Learning predictive representations from a history
ICML '05 Proceedings of the 22nd international conference on Machine learning
On-line discovery of temporal-difference networks
Proceedings of the 25th international conference on Machine learning
Active Learning of Group-Structured Environments
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
Proto-predictive representation of states with simple recurrent temporal-difference networks
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Improving approximate value iteration using memories and predictive state representations
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Learning subjective representations for planning
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Characterization of ergodic hidden Markov sources
IEEE Transactions on Information Theory
The computational structure of spike trains
Neural Computation
Models of active learning in group-structured state spaces
Information and Computation
Norm-observable operator models
Neural Computation
Closing the learning-planning loop with predictive state representations
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Closing the learning-planning loop with predictive state representations
International Journal of Robotics Research
A spectral learning algorithm for finite state transducers
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part I
A spectral algorithm for learning Hidden Markov Models
Journal of Computer and System Sciences
Spectral learning of latent-variable PCFGs
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Picking up the pieces: Causal states in noisy data, and how to recover them
Pattern Recognition Letters
Using regression for spectral estimation of HMMs
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
Better generalization with forecasts
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Perceptual systems routinely separate “content” from “style,” classifying familiar words spoken in an unfamiliar accent, identifying a font or handwriting style across letters, or recognizing a familiar face or object seen under ...