Making large-scale support vector machine learning practical
Advances in kernel methods
EM algorithms for PCA and SPCA
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Probabilistic latent semantic indexing
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Independent component analysis: algorithms and applications
Neural Networks
Modern Information Retrieval
Pairwise Data Clustering by Deterministic Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Topic Identification in Dynamical Text by Complexity Pursuit
Neural Processing Letters
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Variational Extensions to EM and Multinomial PCA
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Investigating the relationship between language model perplexity and IR precision-recall measures
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
GaP: a factor model for discrete data
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Applying discrete PCA in data analysis
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Relation between PLSA and NMF and implications
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Group and topic discovery from relations and text
Proceedings of the 3rd international workshop on Link discovery
Expectation-propagation for the generative aspect model
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Statistical models for partial membership
Proceedings of the 25th international conference on Machine learning
A Unified View of Matrix Factorization Models
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Mixed Membership Stochastic Blockmodels
The Journal of Machine Learning Research
Latent grouping models for user preference prediction
Machine Learning
Two-Way Grouping by One-Way Topic Models
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
Estimating Likelihoods for Topic Models
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
On smoothing and inference for topic models
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
From frequency to meaning: vector space models of semantics
Journal of Artificial Intelligence Research
Conditional topical coding: an efficient topic model conditioned on rich features
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Sampling table configurations for the hierarchical poisson-dirichlet process
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Image similarity: from syntax to weak semantics
Multimedia Tools and Applications
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Data Mining and Knowledge Discovery
Group sparse topical coding: from code to topic
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This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-negative matrix factorisation and latent Dirichlet allocation. The main families of algorithms discussed are a variational approximation, Gibbs sampling, and Rao-Blackwellised Gibbs sampling. Applications are presented for voting records from the United States Senate for 2003, and for the Reuters-21578 newswire collection.