A family of algorithms for approximate bayesian inference
A family of algorithms for approximate bayesian inference
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
On an equivalence between PLSI and LDA
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
Applying discrete PCA in data analysis
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
The rate adapting poisson model for information retrieval and object recognition
ICML '06 Proceedings of the 23rd international conference on Machine learning
Bayesian Gaussian Process Classification with the EM-EP Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized component analysis for text with heterogeneous attributes
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining business topics in source code using latent dirichlet allocation
ISEC '08 Proceedings of the 1st India software engineering conference
Proceedings of the 17th international conference on World Wide Web
Modeling online reviews with multi-grain topic models
Proceedings of the 17th international conference on World Wide Web
Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models
Neural Information Processing
Mixed Membership Stochastic Blockmodels
The Journal of Machine Learning Research
Latent dirichlet allocation in web spam filtering
AIRWeb '08 Proceedings of the 4th international workshop on Adversarial information retrieval on the web
Statistical Language Models for Information Retrieval A Critical Review
Foundations and Trends in Information Retrieval
PLDA: Parallel Latent Dirichlet Allocation for Large-Scale Applications
AAIM '09 Proceedings of the 5th International Conference on Algorithmic Aspects in Information and Management
Using LDA to detect semantically incoherent documents
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
HTM: a topic model for hypertexts
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Latent Dirichlet Allocation for Automatic Document Categorization
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
A Generic Approach to Topic Models
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Topic and role discovery in social networks with experiments on enron and academic email
Journal of Artificial Intelligence Research
Topic modeling for spoken document retrieval using word- and syllable-level information
SSCS '09 Proceedings of the third workshop on Searching spontaneous conversational speech
Learning author-topic models from text corpora
ACM Transactions on Information Systems (TOIS)
Data mining for web personalization
The adaptive web
Community-based ranking of the social web
Proceedings of the 21st ACM conference on Hypertext and hypermedia
Modeling the evolution of associated data
Data & Knowledge Engineering
The topic-perspective model for social tagging systems
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Expectation propagation for Bayesian multi-task feature selection
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Learning aspect models with partially labeled data
Pattern Recognition Letters
Post-based collaborative filtering for personalized tag recommendation
Proceedings of the 2011 iConference
Topic-based user segmentation for online advertising with latent dirichlet allocation
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
A temporal latent topic model for facial expression recognition
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Text segmentation: A topic modeling perspective
Information Processing and Management: an International Journal
Dimensionality reduction for blog tag mining
International Journal of Web Engineering and Technology
Latent topic feedback for information retrieval
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Latent topic models of surface syntactic information
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
What is the basic semantic unit of Chinese language? a computational approach based on topic models
MOL'11 Proceedings of the 12th biennial conference on The mathematics of language
Blind source separation with time series variational Bayes expectation maximization algorithm
Digital Signal Processing
Robust Gaussian Process Regression with a Student-t Likelihood
The Journal of Machine Learning Research
Applying latent dirichlet allocation to automatic essay grading
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Analyzing entities and topics in news articles using statistical topic models
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
News thread extraction based on topical n-gram model with a background distribution
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Measuring the complexity of a collection of documents
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
Large scale microblog mining using distributed MB-LDA
Proceedings of the 21st international conference companion on World Wide Web
Topic analysis for online reviews with an author-experience-object-topic model
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Author-conference topic-connection model for academic network search
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Pervasive and Mobile Computing
Topic model for analyzing purchase data with price information
Data Mining and Knowledge Discovery
Detecting Probabilistic Community with Topic Modeling on Sampling SubGraphs
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Latent Business Networks Mining: A Probabilistic Generative Model
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Automatic classification of documents in cold-start scenarios
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Academic network analysis: a joint topic modeling approach
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Commonsense-based topic modeling
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Nested expectation propagation for Gaussian process classification
The Journal of Machine Learning Research
Stochastic variational inference
The Journal of Machine Learning Research
ATT: analyzing temporal dynamics of topics and authors in social media
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Infinite Dirichlet mixture models learning via expectation propagation
Advances in Data Analysis and Classification
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Generalized spike-and-slab priors for Bayesian group feature selection using expectation propagation
The Journal of Machine Learning Research
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The generative aspect model is an extension of the multinomial model for text that allows word probabilities to vary stochastically across documents. Previous results with aspect models have been promising, but hindered by the computational difficulty of carrying out inference and learning. This paper demonstrates that the simple variational methods of Blei et al. (2001) can lead to inaccurate inferences and biased learning for the generative aspect model. We develop an alternative approach that leads to higher accuracy at comparable cost. An extension of Expectation-Propagation is used for inference and then embedded in an EM algorithm for learning. Experimental results are presented for both synthetic and real data sets.