Technical Reports - Michael Jordan

A Million Cancer Genome Warehouse (EECS-2012-211)
David Haussler, David A. Patterson, Mark Diekhans, Armando Fox, Michael Jordan, Anthony D. Joseph, Singer Ma, Benedict Paten, Scott Shenker, Taylor Sittler and Ion Stoica

Beta processes, stick-breaking, and power laws (EECS-2011-125)
Tamara Broderick, Michael Jordan and Jim Pitman

Probabilistic Models of Evolution and Language Change (EECS-2010-153)
Alexandre Bouchard-Cote, Michael Jordan, Daniel Klein, Thomas L. Griffiths and Yun S. Song

On the Consistency of Ranking Algorithms (EECS-2010-56)
John Duchi, Lester Mackey and Michael Jordan

Large-Scale System Problems Detection by Mining Console Logs (EECS-2009-103)
Wei Xu, Ling Huang, Armando Fox, David A. Patterson and Michael Jordan

Fast Approximate Spectral Clustering (EECS-2009-45)
Donghui Yan, Ling Huang and Michael Jordan

A Graphical Modeling Viewpoint on Queueing Networks (EECS-2009-21)
Charles Sutton and Michael Jordan

A Case For Adaptive Datacenters To Conserve Energy and Improve Reliability (EECS-2008-127)
Peter Bodik, Michael Paul Armbrust, Kevin Canini, Armando Fox, Michael Jordan and David A. Patterson

In-Network PCA and Anomaly Detection (EECS-2007-10)
Ling Huang, Xuanlong Nguyen, Minos Garofalakis, Michael Jordan, Anthony D. Joseph and Nina Taft

Distributed PCA and Network Anomaly Detection (EECS-2006-99)
Ling Huang, Xuanlong Nguyen, Minos Garofalakis, Michael Jordan, Anthony D. Joseph and Nina Taft

A Direct Formulation for Sparse PCA Using Semidefinite Programming (CSD-04-1330)
Alexandre d'Aspremont, Laurent El Ghaoui, Michael I. Jordan and Gert R. G. Lanckriet

A Kernel-based Learning Approach to Ad Hoc Sensor Network Localization (CSD-04-1319)
XuanLong Nguyen, Michael I. Jordan and Bruno Sinopoli

Fast Kernel Learning using Sequential Minimal Optimization (CSD-04-1307)
Francis R. Bach, Gert R. G. Lanckriet and Michael I. Jordan

Bayesian Haplotype Inference via the Dirichlet Process (CSD-03-1275)
Eric P. Xing, Roded Sharan and Michael I. Jordan

Graph Partition Strategies for Generalized Mean Field Inference (CSD-03-1274)
Eric P. Xing and Michael I. Jordan

A Framework for Genomic Data Fusion and its Application to Membrane Protein Prediction (CSD-03-1273)
Gert R. G. Lanckriet, Tijl De Bie, Nello Cristianini, Michael I. Jordan and William Stafford Noble

On Semidefinite Relaxation for Normalized k-cut and Connections to Spectral Clustering (CSD-03-1265)
Eric P. Xing and Michael I. Jordan

Learning Spectral Clustering (CSD-03-1249)
Francis R. Bach and Michael I. Jordan

Semidefinite Relaxations for Approximate Inference on Graphs with Cycles (CSD-03-1226)
Martin J. Wainwright and Michael I. Jordan

Kalman Filtering with Intermittent Observations (M03/15)
B. Sinopoli, L. Schenato, M. Franceschetti, Kameshwar Poolla, Michael Jordan and S. Shankar Sastry

A Robust Minimax Approach to Classification (CSD-02-1218)
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib Bhattacharyya and Michael I. Jordan

Finding Clusters in Independent Component Analysis (CSD-02-1209)
Francis R. Bach and Michael I. Jordan

Learning the Kernel Matrix with Semi-Definite Programming (CSD-02-1206)
Gert R. G. Lanckriet, Nello Cristianini, Peter Bartlett, Laurent El Ghaoui and Michael I. Jordan

Kernel Independent Component Analysis (CSD-01-1166)
Francis R. Bach and Michael I. Jordan

An Introduction to Variational Methods for Graphical Models (CSD-98-980)
Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola and Lawrence K. Saul