Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A model for reasoning about persistence and causation
Computational Intelligence
Learning and relearning in Boltzmann machines
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Elements of information theory
Elements of information theory
Connectionist learning of belief networks
Artificial Intelligence
Neural networks and the bias/variance dilemma
Neural Computation
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Probabilistic independence networks for hidden Markov probability models
Neural Computation
Proceedings of the 1997 conference on Advances in neural information processing systems 10
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Hidden Markov Model} Induction by Bayesian Model Merging
Advances in Neural Information Processing Systems 5, [NIPS Conference]
A minimum description length framework for unsupervised learning
A minimum description length framework for unsupervised learning
Mean field theory for sigmoid belief networks
Journal of Artificial Intelligence Research
Stochastic simulation algorithms for dynamic probabilistic networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Adaptive Probabilistic Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Structured representation of complex stochastic systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Speech recognition with dynamic Bayesian networks
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Neural Computation
The Hierarchical Hidden Markov Model: Analysis and Applications
Machine Learning
An Introduction to Variational Methods for Graphical Models
Machine Learning
ACM Computing Surveys (CSUR)
An introduction to hidden Markov models and Bayesian networks
Hidden Markov models
Shape tracking and production using hidden Markov models
Hidden Markov models
Hidden Markov Models with Spectral Features for 2D Shape Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ensemble of Independent Factor Analyzers with Application to Natural Image Analysis
Neural Processing Letters
Factorial hidden Markov models and the generalized backfitting algorithm
Neural Computation
On Learning the Shape of Complex Actions
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Self-Similar Layered Hidden Markov Models
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Baum-Welch Learning in Discrete Hidden Markov Models with Linear Factorial Constraints
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Self-Similarity for Data Mining and Predictive Modeling - A Case Study for Network Data
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm
EMMCVPR '99 Proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Hidden Markov Modeling for Multi-agent Systems
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Bidirectional Dynamics for Protein Secondary Structure Prediction
Sequence Learning - Paradigms, Algorithms, and Applications
Simplified Training Algorithms for Hierarchical Hidden Markov Models
DS '01 Proceedings of the 4th International Conference on Discovery Science
Temporal Pattern Generation Using Hidden Markov Model Based Unsupervised Classification
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
A Discrete Probabilistic Memory Model for Discovering Dependencies in Time
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Modeling drivers' speech under stress
Speech Communication - Special issue on speech and emotion
Relational Markov models and their application to adaptive web navigation
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Unsupervised learning for speech motion editing
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Learning kernel-based HMMs for dynamic sequence synthesis
Graphical Models - Special issue on Pacific graphics 2002
A Generative Probabilistic Oriented Wavelet Model for Texture Segmentation
Neural Processing Letters
Robust Visual Tracking by Integrating Multiple Cues Based on Co-Inference Learning
International Journal of Computer Vision - Special Issue on Computer Vision Research at the Beckman Institute of Advanced Science and Technology
Bayesian Unsupervised Learning for Source Separation with Mixture of Gaussians Prior
Journal of VLSI Signal Processing Systems
ICML '04 Proceedings of the twenty-first international conference on Machine learning
The Journal of Machine Learning Research
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Graph partition strategies for generalized mean field inference
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Automatic extraction of titles from general documents using machine learning
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Kernel-based, ellipsoidal conditions in the real-valued XCS classifier system
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Data association for topic intensity tracking
ICML '06 Proceedings of the 23rd international conference on Machine learning
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
ICML '06 Proceedings of the 23rd international conference on Machine learning
Automatic extraction of titles from general documents using machine learning
Information Processing and Management: an International Journal
Privacy intrusion detection using dynamic Bayesian networks
ICEC '06 Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
Discovering Shape Classes using Tree Edit-Distance and Pairwise Clustering
International Journal of Computer Vision
Conditional models for contextual human motion recognition
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
A Bayesian approach for structural learning with hidden Markov models
Scientific Programming - Hidden Markov Models
Noisy-OR Component Analysis and its Application to Link Analysis
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Robust speech recognition using factorial HMMs for home environments
EURASIP Journal on Applied Signal Processing
Combining object and feature dynamics in probabilistic tracking
Computer Vision and Image Understanding
Bayesian spiking neurons i: Inference
Neural Computation
International Journal of Robotics Research
Modeling interleaved hidden processes
Proceedings of the 25th international conference on Machine learning
Extension of higher-order HMC modeling with application to image segmentation
Digital Signal Processing
Structured Hidden Markov Model: A General Framework for Modeling Complex Sequences
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
Applying Space State Models in Human Action Recognition: A Comparative Study
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
Cluster Selection Based on Coupling for Gaussian Mean Fields
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Academic conference homepage understanding using constrained hierarchical conditional random fields
Proceedings of the 17th ACM conference on Information and knowledge management
Multi-channel segmental hidden markov models for sports video mining
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Graphical Models, Exponential Families, and Variational Inference
Foundations and Trends® in Machine Learning
Imputation-Based Local Ancestry Inference in Admixed Populations
ISBRA '09 Proceedings of the 5th International Symposium on Bioinformatics Research and Applications
Component-based discriminative classification for hidden Markov models
Pattern Recognition
An Inductive Logic Programming Approach to Statistical Relational Learning
Proceedings of the 2005 conference on An Inductive Logic Programming Approach to Statistical Relational Learning
Learning partially observable action models: efficient algorithms
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Clustering-Based Construction of Hidden Markov Models for Generative Kernels
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
A variational learning algorithm for the abstract hidden Markov model
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Learning partially observable deterministic action models
Journal of Artificial Intelligence Research
Monitoring teams by overhearing: a multi-agent plan-recognition approach
Journal of Artificial Intelligence Research
Policy recognition in the abstract hidden Markov model
Journal of Artificial Intelligence Research
A primitive based generative model to infer timing information in unpartitioned handwriting data
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Structure inference for Bayesian multisensory perception and tracking
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Jointly labeling multiple sequences: a factorial HMM approach
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Review: The use of pervasive sensing for behaviour profiling - a survey
Pervasive and Mobile Computing
Imitation learning of team-play in multiagent system based on hidden Markov modeling
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Learning partially observable deterministic action models
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Product of Gaussians for speech recognition
Computer Speech and Language
Acoustic factor analysis for streamed hidden Markov modeling
IEEE Transactions on Audio, Speech, and Language Processing
Anomaly detection via feature-aided tracking and hidden Markov models
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Dynamic multiple fault diagnosis: mathematical formulations and solution techniques
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
A factorial hidden Markov model (FHMM)-based reasoner for diagnosing multiple intermittent faults
CASE'09 Proceedings of the fifth annual IEEE international conference on Automation science and engineering
Distributional representations for handling sparsity in supervised sequence-labeling
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Probabilistic situation recognition for vehicular traffic scenarios
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Incremental clustering of gesture patterns based on a self organizing incremental neural network
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A Study on Smoothing for Particle-Filtered 3D Human Body Tracking
International Journal of Computer Vision
Discriminative input stream combination for conditional random field phone recognition
IEEE Transactions on Audio, Speech, and Language Processing
Dynamic multiple-fault diagnosis with imperfect tests
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A hidden Markov modelwith binned duration algorithm
IEEE Transactions on Signal Processing
On supervision and statistical learning for semantic multimedia analysis
Journal of Visual Communication and Image Representation
Hidden Markov models with factored Gaussian mixtures densities
Pattern Recognition
Variational upper bounds for probabilistic phylogenetic models
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
Products of Hidden Markov Models: it takes N1 to tango
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
The Infinite Latent Events Model
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
A combined expression-interaction model for inferring the temporal activity of transcription factors
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Conformation-based hidden Markov models: application to human face identification
IEEE Transactions on Neural Networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Social action tracking via noise tolerant time-varying factor graphs
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Benchmarking dynamic time warping for music retrieval
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
A Combination Approach to Web User Profiling
ACM Transactions on Knowledge Discovery from Data (TKDD)
IEEE Transactions on Image Processing
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
Exploring representation-learning approaches to domain adaptation
DANLP 2010 Proceedings of the 2010 Workshop on Domain Adaptation for Natural Language Processing
Modelling patterns of evidence in Bayesian networks: a case-study in classical swine fever
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Machine learning approaches for time-series data based on self-organizing incremental neural network
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part III
Artificial Intelligence
Non-negative hidden Markov modeling of audio with application to source separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
EURASIP Journal on Advances in Signal Processing - Special issue on genomic signal processing
Tracking appearances with occlusions
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Domain adaptation by constraining inter-domain variability of latent feature representation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A pronoun anaphora resolution system based on factorial hidden Markov models
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Language models as representations for weakly-supervised NLP tasks
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Automating the calibration of a neonatal condition monitoring system
AIME'11 Proceedings of the 13th conference on Artificial intelligence in medicine
Inferring parameters and structure of latent variable models by variational bayes
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Variational learning in mixed-state dynamic graphical models
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Expectation propagation for approximate inference in dynamic bayesian networks
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Rao-blackwellised particle filtering for dynamic Bayesian networks
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Probabilistic state-dependent grammars for plan recognition
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Variational approximations between mean field theory and the junction tree algorithm
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
The factored frontier algorithm for approximate inference in DBNs
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Learning the structure of dynamic probabilistic networks
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Probabilistic de novo peptide sequencing with doubly charged ions
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Extracting motion primitives from natural handwriting data
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
A generalized mean field algorithm for variational inference in exponential families
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Tree-structured conditional random fields for semantic annotation
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Simultaneous localization and surveying with multiple agents
Switching and Learning in Feedback Systems
iASA: learning to annotate the semantic web
Journal on Data Semantics IV
From factorial and hierarchical HMM to bayesian network: a representation change algorithm
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Review: learning bayesian networks: Approaches and issues
The Knowledge Engineering Review
Principles of non-stationary hidden markov model and its applications to sequence labeling task
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Ancestry inference in complex admixtures via variable-length markov chain linkage models
RECOMB'12 Proceedings of the 16th Annual international conference on Research in Computational Molecular Biology
Content classification of development emails
Proceedings of the 34th International Conference on Software Engineering
A review on speaker diarization systems and approaches
Speech Communication
Mixed membership Markov models for unsupervised conversation modeling
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Biased representation learning for domain adaptation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Dynamic probabilistic CCA for analysis of affective behaviour
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
A survey of query-by-humming similarity methods
Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments
RECOMB'13 Proceedings of the 17th international conference on Research in Computational Molecular Biology
Environmental Modelling & Software
Bayesian nonparametric hidden semi-Markov models
The Journal of Machine Learning Research
Variational inference in nonconjugate models
The Journal of Machine Learning Research
Stochastic variational inference
The Journal of Machine Learning Research
Video content categorization using the double decomposition
Multimedia Tools and Applications
A context aware sound classifier applied to prawn feed monitoring and energy disaggregation
Knowledge-Based Systems
An autonomous and intelligent expert system for residential water end-use classification
Expert Systems with Applications: An International Journal
Training energy-based models for time-series imputation
The Journal of Machine Learning Research
PEFAC - A Pitch Estimation Algorithm Robust to High Levels of Noise
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Hi-index | 0.01 |
Hidden Markov models (HMMs) have proven to be one of the most widelyused tools for learning probabilistic models of time series data. Inan HMM, information about the past is conveyedthrough a single discrete variable—the hidden state. We discuss ageneralization of HMMs in which this state is factored into multiplestate variables and is therefore represented in a distributed manner.We describe an exact algorithm for inferring the posteriorprobabilities of the hidden state variables given the observations,and relate it to the forward–backward algorithm for HMMs and toalgorithms for more general graphical models. Due to the combinatorialnature of the hidden state representation, this exact algorithm isintractable. As in other intractable systems, approximate inferencecan be carried out using Gibbs sampling or variational methods. Within the variational framework, wepresent a structured approximation in which the the statevariables are decoupled, yielding a tractablealgorithm for learning the parameters of the model. Empiricalcomparisons suggest that these approximations are efficient andprovide accurate alternatives to the exact methods. Finally, we use thestructured approximation to model Bach‘s chorales and show thatfactorial HMMs can capture statistical structure in this data setwhich an unconstrained HMM cannot.