Geometric optimization methods for adaptive filtering
Geometric optimization methods for adaptive filtering
WebACE: a Web agent for document categorization and exploration
AGENTS '98 Proceedings of the second international conference on Autonomous agents
The Geometry of Algorithms with Orthogonality Constraints
SIAM Journal on Matrix Analysis and Applications
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 1998 conference on Advances in neural information processing systems II
Document clustering based on non-negative matrix factorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
Information-theoretic co-clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Relation between PLSA and NMF and implications
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Co-clustering by block value decomposition
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Orthogonal nonnegative matrix t-factorizations for clustering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The Relationships Among Various Nonnegative Matrix Factorization Methods for Clustering
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Computational Statistics & Data Analysis
Computational Intelligence and Neuroscience - Advances in Nonnegative Matrix and Tensor Factorization
Document clustering using nonnegative matrix factorization
Information Processing and Management: an International Journal
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Co-clustering under nonnegative matrix tri-factorization
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Matrix co-factorization on compressed sensing
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
A sparsity-inducing formulation for evolutionary co-clustering
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Subtractive clustering for seeding non-negative matrix factorizations
Information Sciences: an International Journal
A convergent algorithm for orthogonal nonnegative matrix factorization
Journal of Computational and Applied Mathematics
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Matrix factorization-based methods become popular in dyadic data analysis, where a fundamental problem, for example, is to perform document clustering or co-clustering words and documents given a term-document matrix. Nonnegative matrix tri-factorization (NMTF) emerges as a promising tool for co-clustering, seeking a 3-factor decomposition X~USV^@? with all factor matrices restricted to be nonnegative, i.e., U=0,S=0,V=0. In this paper we develop multiplicative updates for orthogonal NMTF where X~USV^@? is pursued with orthogonality constraints, U^@?U=I, and V^@?V=I, exploiting true gradients on Stiefel manifolds. Experiments on various document data sets demonstrate that our method works well for document clustering and is useful in revealing polysemous words via co-clustering words and documents.