- Mixture Models for Co-occurrence and Histogram Data Thomas Hofmann1
- Probabilistic Latent Semantic Analysis To appear in: Uncertainity in Arti cial Intelligence, UAI'99, Stockholm
- Non-Redundant Data Clustering David Gondek Thomas Hofmann
- Learning with Taxonomies: Classifying Documents and Words
- MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY
- Support Vector Machine Learning for Interdependent and Structured Output Spaces
- Discrete Mixture Models for Unsupervised Image Segmentation?
- Gaussian Process Classification for Segmenting and Annotating Sequences
- Unsupervised Texture Segmentation in a Deterministic Annealing Framework
- The Cluster Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data
- The Cluster--Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data
- Learning Probabilistic Models of the Web Thomas Hofmann
- Hidden Markov Support Vector Machines Yasemin Altun altun@cs.brown.edu
- Probabilistic Latent Semantic Indexing Proceedings of the TwentySecond Annual International SIGIR Conference on Research and Development in Information Retrieval
- Text Categorization by Boosting Automatically Extracted Concepts
- in Advances in Neural Information Processing Systems 12 S.A. Solla, T.K. Leen and K.-R. Muller (eds.), pp. 914{920, MIT Press (2000)
- Conditional Information Bottleneck Clustering David Gondek
- IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 19, NO. 1, JANUARY 1997 1 Pairwise Data Clustering
- Support Vector Machines for Polycategorical Classification
- Probabilistic Latent Semantic Analysis To appear in: Uncertainity in Artificial Intelligence, UAI'99, Stockholm
- Hierarchical Semantic Classification: Word Sense Disambiguation with World Knowledge
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- Active Data Clustering Thomas Hofmann
- The Missing Link -A Probabilistic Model of Document Content and Hypertext Connectivity
- Hierarchical Document Categorization with Support Vector Machines
- A Joint Framework for Collaborative and Content Filtering Justin Basilico
- Multiple Instance Learning via Disjunctive Programming Boosting
- Collaborative Filtering via Gaussian Probabilistic Latent Semantic Analysis
- Multiple Instance Learning with Generalized Support Vector Machines Stuart Andrews, Thomas Hofmann and Ioannis Tsochantaridis
- Probabilistic Latent Semantic Indexing Proceedings of the Twenty-Second Annual International SIGIR Conference on Research and Development in Information Retrieval
- Latent Class Models for Collaborative Filtering to appear in Proceedings of IJCAI'99
- Histogram Clustering for Unsupervised Image Segmentation
- Competitive Learning Algorithms for Robust Vector Quantization
- Deterministic Annealing for Unsupervised Texture Segmentation
- An Optimization Approach to Unsupervised Hierarchical Texture Segmentation
- The Mobile Robot RHINO Joachim Buhmann, Wolfram Burgard, Armin B. Cremers, Dieter Fox,
