The Workshops on Algorithms for Modern Massive Data Sets (MMDS 2010) addressed algorithmic and statistical challenges in modern large-scale data analysis. The goals of this series of workshops are to explore novel techniques for modeling and analyzing massive, high-dimensional, and nonlinearly-structured scientific and internet data sets; and to bring together computer scientists, statisticians, mathematicians, and data analysis practitioners to promote the cross-fertilization of ideas.
| Time | Talk |
|---|---|
| 8:00 - 10:00 | Breakfast and Registration -- outside Cubberley Auditorium (at the Stanford School of Education, just off the Main Quad) |
| 9:45 - 10:00 | Welcome and Opening Remarks -- in Cubberley Auditorium |
| 10:00 - 11:00 | Tutorial: Peter Norvig Internet-Scale Data Analysis |
| 11:00 - 11:30 | Ashok Srivastava Virtual Sensors and Large-Scale Gaussian Processes |
| 11:30 - 12:00 | John Langford A Method for Parallel Online Learning |
| 2:00 - 3:00 | Tutorial: John Gilbert Combinatorial Scientific Computing: Experience and Challenges |
| 3:00 - 3:30 | Deepak Agarwal Recommender Probems for Content Optimization |
| 3:30 - 4:00 | James Demmel Minimizing Communication in Linear Algebra |
| 4:30 - 5:00 | Dmitri Krioukov Hyperbolic Mapping of Complex Networks |
| 5:00 - 5:30 | Mehryar Mohri Matrix Approximation for Large-Scale Learning |
| 5:30 - 6:00 | David Bader Massive-Scale Analytics of Streaming Social Networks |
| 6:00 - 6:30 | Ely Porat Fast Pseudo-Random Fingerprints |
| Time | Talk |
|---|---|
| 9:00 - 10:00 | Tutorial: Peter Bickel Statistical Inference for Networks |
| 10:00 - 10:30 | Jure Leskovec Inferring Networks of Diffusion and Influence |
| 11:00 - 11:30 | Michael W. Mahoney Geometric Network Analysis Tools |
| 11:30 - 12:00 | Edward Chang AdHEat - A New Influence-based Social Ads Model and its Tera-Scale Algorithms |
| 12:00 - 12:30 | Mauro Maggioni Intrinsic Dimensionality Estimation and Multiscale Geometry of Data Sets |
| 2:30 - 3:00 | Guillermo Sapiro Collaborative Hierarchical Sparse Models |
| 3:00 - 3:30 | Alekh Agarwal and Peter Bartlett Information-theoretic Lower Bounds on the Oracle Complexity of Convex Optimization |
| 3:30 - 4:00 | John Duchi and Yoram Singer Composite Objective Optimization and Learning for Massive Datasets |
| 4:30 - 5:00 | Steven Hillion MAD Analytics in Practice |
| 5:00 - 5:30 | Matthew Harding Outlier Detection in Financial Trading Networks |
| 5:30 - 6:00 | Neel Sundrahan Large Dataset Problems at the Long Tail |
| Time | Talk |
|---|---|
| 9:00 - 10:00 | Tutorial: Sebastiano Vigna Spectral Ranking |
| 10:00 - 10:30 | Robert Stine Streaming Feature Selection |
| 11:00 - 11:30 | Konstantin Mischaikow A Combinatorial Framework for Nonlinear Dynamics |
| 11:30 - 12:00 | Alfred Hero Sparse Correlation Screening in High Dimension |
| 12:00 - 12:30 | Susan Holmes Heterogeneous Data Challenge Combining Complex Data |
| 2:30 - 3:30 | Tutorial: Piotr Indyk Sparse Recovery Using Sparse Matrices |
| 3:30 - 4:00 | Sayan Mukherjee Efficient Dimension Reduction on Massive Data |
| 4:30 - 5:00 | Padhraic Smyth Statistical Modeling of Large-Scale Sensor Count Data |
| 5:00 - 5:30 | Ping Li Compressed Counting and Application in Estimating Entropy of Data Steams |
| 5:30 - 6:00 | Edo Liberty Scaleable Correlation Clustering Algorithms |
| Time | Talk |
|---|---|
| 9:00 - 10:00 | Tutorial: Petros Drineas Randomized Algorithms in Linear Algebra and Large Data Applications |
| 10:00 - 10:30 | Gunnar Martinsson Randomized methods for Computing the SVD/PCA of Very Large Matrices |
| 11:00 - 11:30 | Ilse Ipsen Numerical Reliability of Randomized Algorithms |
| 11:30 - 12:00 | Philippe Rigollet Optimal Rates of Sparse Esimation and Universal Aggregation |
| 12:00 - 12:30 | Alexandre d'Aspremont Subsampling, Spectral Methods & Semidefinite Programming |
| 2:30 - 3:00 | Gary Miller Specialized System Solvers for very large Systems: Theory and Practice |
| 3:00 - 3:30 | John Wright and Emmanuel Candes Robust Principal Component Analysis? |
| 3:30 - 4:00 | Alon Orlitsky Estimation, Prediction, and Classification over Large Alphabets |
| 4:30 - 5:00 | Ken Clarkson Numerical Linear Algebra in the Streaming Model |
| 5:00 - 5:30 | David Woodruff Fast Lp Regression in Data Streams |
| Alekh Agarwal | University of California, Berkeley |
| Deepak Agarwal | Yahoo! Research |
| Alexandre d'Aspremont | Princeton University |
| David Bader | Georgia Tech College of Computing |
| Peter Bickel | University of California, Berkeley |
| Emmanuel Candes | Stanford University |
| Edward Chang | Google Research |
| Ken Clarkson | IBM Almaden Research Center |
| Jim Demmel | University of California, Berkeley |
| John Duchi | University of California, Berkeley |
| John Gilbert | University of California, Santa Barbara |
| Matthew Harding | Stanford University |
| Alfred Hero | University of Michigan, Ann Arbor |
| Steven Hillion | Greenplum |
| Susan Holmes | Stanford University |
| Peter Indyk | Massachusetts Institute of Technology |
| Ilse Ipsen | North Carolina State University |
| Dmitri Krioukov | Cooperative Association for Internet Data Analysis |
| John Langford | Yahoo! Research |
| Jure Leskovec | Stanford University |
| Ping Li | Cornell University |
| Edo Liberty | Yahoo! Research |
| Mauro Maggioni | Duke University |
| Gunnar Martinsson | University of Colorado, Boulder |
| Gary Miller | Carnegie Mellon University |
| Konstantin Mischaikow | Rutgers University |
| Mehryar Mohri | New York University |
| Sayan Mukherjee | Duke University |
| Peter Norvig | Google Research |
| Alon Orlitsky | University of California, San Diego |
| Ely Porat | Bar-Ilan University |
| Guillermo Sapiro | University of Minnesota |
| Padhraic Smyth | University of California, Irvine |
| Ashok Srivastava | National Aeronautics and Space Administration |
| Neel Sundaresan | eBay Research |
| Robert Stine | University of Pennsylvania |
| Sebastiano Vigna | Università Degli Studi Di Milano |
| David Woodruff | IBM Almaden Research Center |
| John Wright | Microsoft Research Asia |
| Peter Bartlett | University of California, Berkeley |
| Robert Calderbank | Princeton University |
| Fan Chung | University of California, San Diego |
| Yoram Singer | Google Research |
| Patrick Wolfe | Harvard University |
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MMDS 2008. Workshop on Algorithms for Modern Massive Data Sets, Stanford, CA, June 25–28, 2008.
MMDS 2006. Workshop on Algorithms for Modern Massive Data Sets, Stanford, CA, June 21–24, 2006.