NumS: Scalable Array Programming for the Cloud (EECS-2022-115)
Huseyin Elibol, Michael Jordan and Ion Stoica

Perturbed Iterate Analysis for Asynchronous Stochastic Optimization (EECS-2019-12)
Horia Mania, Xinghao Pan, Dimitris Papailiopoulos, Benjamin Recht, Kannan Ramchandran and Michael Jordan

A deep generative model for gene expression profiles from single-cell RNA sequencing (EECS-2018-21)
Nir Yosef, Michael Jordan and Romain Lopez

A Berkeley View of Systems Challenges for AI (EECS-2017-159)
Ion Stoica, Dawn Song, Raluca Ada Popa, David A. Patterson, Michael W. Mahoney, Randy H. Katz, Anthony D. Joseph, Michael Jordan, Joseph M. Hellerstein, Joseph Gonzalez, Ken Goldberg, Ali Ghodsi, David E. Culler and Pieter Abbeel

Safety, Risk Awareness and Exploration in Reinforcement Learning (EECS-2016-20)
Teodor Moldovan

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