Statistical analysis with missing data
Statistical analysis with missing data
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Maximum likelihood competitive learning
Advances in neural information processing systems 2
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Probabilistic independence networks for hidden Markov probability models
Neural Computation
Exponentiated gradient versus gradient descent for linear predictors
Information and Computation
GTM: the generative topographic mapping
Neural Computation
Regression with input-dependent noise: a Gaussian process treatment
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
EM algorithms for PCA and SPCA
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Modeling acoustic correlations by factor analysis
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
A view of the EM algorithm that justifies incremental, sparse, and other variants
Learning in graphical models
Mixtures of probabilistic principal component analyzers
Neural Computation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Update rules for parameter estimation in Bayesian networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Modeling the manifolds of images of handwritten digits
IEEE Transactions on Neural Networks
Neural Computation
SQLEM: fast clustering in SQL using the EM algorithm
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to hidden Markov models and Bayesian networks
Hidden Markov models
FREM: fast and robust EM clustering for large data sets
Proceedings of the eleventh international conference on Information and knowledge management
Dynamic Learning with the EM Algorithm for Neural Networks
Journal of VLSI Signal Processing Systems
Maximum a Posteriori Estimation of Coupled Hidden Markov Models
Journal of VLSI Signal Processing Systems
The Problem of Sparse Image Coding
Journal of Mathematical Imaging and Vision
Unsupervised learning in neural computation
Theoretical Computer Science - Natural computing
Modeling Visual Patterns by Integrating Descriptive and Generative Methods
International Journal of Computer Vision
EM-Based Radial Basis Function Training with Partial Information
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Estimating a state-space model from point process observations
Neural Computation
Clustering binary data streams with K-means
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Regularized principal manifolds
The Journal of Machine Learning Research
Adaptation in Statistical Pattern Recognition Using Tangent Vectors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Horizontal aggregations for building tabular data sets
Proceedings of the 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Efficient Disk-Based K-Means Clustering for Relational Databases
IEEE Transactions on Knowledge and Data Engineering
Sequential EM learning for subspace analysis
Pattern Recognition Letters
Principal components analysis competitive learning
Neural Computation
A Bayesian method for identifying independent sources of non-random spatial patterns
Statistics and Computing
Integrating K-Means Clustering with a Relational DBMS Using SQL
IEEE Transactions on Knowledge and Data Engineering
Online Model Selection Based on the Variational Bayes
Neural Computation
An Expectation-Maximization Approach to Nonlinear Component Analysis
Neural Computation
Resolution-Based Complexity Control for Gaussian Mixture Models
Neural Computation
Ontological inference for image and video analysis
Machine Vision and Applications
A datamining approach to cell population deconvolution from gene expressions using particle filters
Proceedings of the 5th international workshop on Bioinformatics
Supervised probabilistic principal component analysis
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A Maximum-Likelihood Interpretation for Slow Feature Analysis
Neural Computation
State-Space Models: From the EM Algorithm to a Gradient Approach
Neural Computation
Building statistical models and scoring with UDFs
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems
The Journal of Machine Learning Research
Linear State-Space Models for Blind Source Separation
The Journal of Machine Learning Research
Temporal causal modeling with graphical granger methods
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Generalized component analysis for text with heterogeneous attributes
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Factoring Gaussian precision matrices for linear dynamic models
Pattern Recognition Letters
Learning and Inferring Motion Patterns using Parametric Segmental Switching Linear Dynamic Systems
International Journal of Computer Vision
Distributed Bayesian fault diagnosis of jump Markov systems in wireless sensor networks
International Journal of Sensor Networks
Feature Selection Based on the Rough Set Theory and Expectation-Maximization Clustering Algorithm
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
International Journal of Computer Vision
Models for association rules based on clustering and correlation
Intelligent Data Analysis
Detection of unique temporal segments by information theoretic meta-clustering
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
When is 'nearest neighbour' meaningful: A converse theorem and implications
Journal of Complexity
An Inductive Logic Programming Approach to Statistical Relational Learning
Proceedings of the 2005 conference on An Inductive Logic Programming Approach to Statistical Relational Learning
Fast nonparametric matrix factorization for large-scale collaborative filtering
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Two-way analysis of high-dimensional collinear data
Data Mining and Knowledge Discovery
Product of Gaussians for speech recognition
Computer Speech and Language
PPCA-based missing data imputation for traffic flow volume: a systematical approach
IEEE Transactions on Intelligent Transportation Systems
Sequential non-stationary dynamic classification with sparse feedback
Pattern Recognition
State-space algorithms for estimating spike rate functions
Computational Intelligence and Neuroscience - Special issue on signal processing for neural spike trains
Fast learning algorithm for Gaussian models to analyze video objects with parameter size
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Optimization procedure for predicting nonlinear time series based on a non-Gaussian noise model
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Accounting for non-genetic factors improves the power of eQTL studies
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
A new look at state-space models for neural data
Journal of Computational Neuroscience
Journal of Computational Neuroscience
Matrix-variate and higher-order probabilistic projections
Data Mining and Knowledge Discovery
The Indian Buffet Process: An Introduction and Review
The Journal of Machine Learning Research
Blind source separation with time series variational Bayes expectation maximization algorithm
Digital Signal Processing
Statistical modelling in continuous speech recognition (CSR)
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Intrinsic dimensionality maps with the PCASOM
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Incremental anomaly detection approach for characterizing unusual profiles
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
Structural shape characterization via exploratory factor analysis
Artificial Intelligence in Medicine
Lifted relational Kalman filtering
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Aggregating web offers to determine product prices
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
RainMon: an integrated approach to mining bursty timeseries monitoring data
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Distributed static linear Gaussian models using consensus
Neural Networks
Journal of Network and Computer Applications
Dynamic texture synthesis in the YUV color-space
ICEC'07 Proceedings of the 6th international conference on Entertainment Computing
Dynamic probabilistic CCA for analysis of affective behaviour
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
The Journal of Machine Learning Research
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