Papers authored by Michael Jordan
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Alan S. Willsky
Bayesian Nonparametric Methods for Learning Markov Switching Processes
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Dan Klein
Learning Programs: A Hierarchical Bayesian Approach
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On the Consistency of Ranking Algorithms
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Multiple Non-Redundant Spectral Clustering Views
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Regularized Discriminant Analysis, Ridge Regression and Beyond.
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Mixed Membership Matrix Factorization
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Sufficient Dimension Reduction for Visual Sequence Classification
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Kimmen Sjölander
Active site prediction using evolutionary and structural information
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Variational Inference over Combinatorial Spaces.
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David A. Patterson
Characterizing, modeling, and generating workload spikes for stateful services
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Bayesian Generalized Kernel Models.
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Matrix-Variate Dirichlet Process Mixture Models.
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Unsupervised Kernel Dimension Reduction
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Random Conic Pursuit for Semidefinite Programming
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David Baker
Feature Space Resampling for Protein Conformational Search
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Heavy-Tailed Process Priors for Selective Shrinkage.
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Detecting Large-Scale System Problems by Mining Console Logs.
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