| Time | Talk |
|---|---|
| 10:00 - 11:00 | Tutorial: Christos Faloutsos Graph mining: laws, generators and tools |
| 11:00 - 11:30 | Deepak Agarwal Predictive discrete latent models for large incomplete dyadic data |
| 11:30 - 12:00 | Chandrika Kamath Scientific data mining: why is it difficult? |
| 2:00 - 3:00 | Tutorial: Edward Chang Challenges in mining large-scale social networks |
| 3:00 - 3:30 | Sharad Goel Predictive indexing for fast search |
| 3:30 - 4:00 | James Demmel Avoiding communication in linear algebra algorithms |
| 4:30 - 5:00 | Jun Liu Bayesian inference of interactions and associations |
| 5:00 - 5:30 | Fan Chung Four graph partitioning algorithms |
| 5:30 - 6:00 | Ronald Coifman Diffusion geometries and harmonic analysis on data sets |
| Time | Talk |
|---|---|
| 9:00 - 10:00 | Tutorial: Milena Mihail Models and algorithms for complex networks, with network elements maintaining characteristic profiles |
| 10:00 - 10:30 | Reid Andersen An algorithm for improving graph partitions |
| 11:00 - 11:30 | Michael W. Mahoney Community structure in large social and information networks |
| 11:30 - 12:00 | Nikhil Srivastava and Daniel Spielman Graph sparsification by effective resistances |
| 12:00 - 12:30 | Amin Saberi Sequential algorithms for generating random graphs |
| 2:00 - 3:00 | Tutorial: Pankaj K. Agarwal Modeling and analyzing massive terrain data sets |
| 3:00 - 3:30 | Leonidas Guibas Detection of symmetries and repeated patterns in 3D point cloud data |
| 3:30 - 4:00 | Yuan Yao Topological methods for exploring pathway analysis in complex biomolecular folding |
| 4:30 - 5:00 | Piotr Indyk Sparse recovery using sparse random matrices |
| 5:00 - 5:30 | Ping Li Algorithms for matrix column selection |
| 5:30 - 6:00 | Joel Tropp Compressed counting and stable random projections |
| Time | Talk |
|---|---|
| 9:00 - 10:00 | Tutorial: Jerome H. Friedman Fast sparse regression and classification |
| 10:00 - 10:30 | Tong Zhang An adaptive forward/backward greedy algorithm for learning sparse representations |
| 11:00 - 11:30 | Jitendra Malik Classification using intersection kernel SVMs is efficient |
| 11:30 - 12:00 | Elad Hazan Efficient online routing with limited feedback and optimization in the dark |
| 12:00 - 12:30 | T.S. Jayram Cascaded aggregates on data streams |
| 2:30 - 3:30 | Tutorial: Gunnar Carlsson Topology and data |
| 3:30 - 4:00 | Partha Niyogi Manifold regularization and semi-supervised learning |
| 4:30 - 5:00 | Sanjoy Dasgupta Random projection trees and low dimensional manifolds |
| 5:00 - 5:30 | Kenneth Clarkson Tighter bounds for random projections of manifolds |
| 5:30 - 6:00 | Yoram Singer Efficient projection algorithms for learning sparse representations from high dimensional data |
| 6:00 - 6:30 | Arindam Banerjee Bayesian co-clustering for dyadic data analysis |
| Time | Talk |
|---|---|
| 9:00 - 10:00 | Tutorial: Michael I. Jordan Sufficient dimension reduction |
| 10:00 - 10:30 | Nathan Srebro More data less work: SVM training in time decreasing with larger data sets |
| 11:00 - 11:30 | Inderjit S. Dhillon Rank minimization via online learning |
| 11:30 - 12:00 | Nir Ailon Efficient dimension reduction |
| 2:30 - 3:00 | Ravi Kannan Spectral algorithms |
| 3:00 - 3:30 | Chris Wiggins Inferring and encoding graph partitions |
| 3:30 - 4:00 | Anna Gilbert Combinatorial group testing in signal recovery |
| 4:30 - 5:00 | Lars Kai Hansen Generalization in high-dimensional matrix factorization |
| 5:00 - 5:30 | Holly Jin Exploring sparse nonnegative matrix factorization |
| 5:30 - 6:00 | Elizabeth Purdom Data analysis with graphs |
| 6:00 - 6:30 | Lek-Heng Lim Ranking via Hodge decompositions of graphs and skew-symmetric matrices |
The 2008 Workshop on Algorithms for Modern Massive Data Sets (MMDS 2008) will address algorithmic, mathematical, and statistical challenges in modern large-scale data analysis. The goals of MMDS 2008 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 cross-fertilization of ideas.
Michael Mahoney, Stanford University
Lek-Heng Lim, University of California, Berkeley
Petros Drineas, Rensselaer Polytechnic Institute
Gunnar Carlsson, Stanford University
| Deepak Agarwal | Yahoo! Research, Silicon Valley |
| Pankaj Agarwal | Duke University |
| Nir Ailon | Google Research, New York |
| Reid Andersen | Microsoft Research, Redmond |
| Arindam Banerjee | University of Minnesota, Twin Cities |
| Edward Chang | Google Research, Mountain View |
| Fan Chung | University of California, San Diego |
| Kenneth Clarkson | IBM Almaden Research Center |
| Ronald Coifman | Yale University |
| Sanjoy Dasgupta | University of California, San Diego |
| James Demmel | University of California, Berkeley |
| Inderjit Dhillon | University of Texas, Austin |
| Christos Faloutsos | Carnegie Mellon University |
| Jerome Friedman | Stanford University |
| Anna Gilbert | University of Michigan, Ann Arbor |
| Sharad Goel | Yahoo! Research, New York |
| Leonidas Guibas | Stanford University |
| Lars Kai Hansen | Technical University of Denmark |
| Elad Hazan | IBM Almaden Research Center |
| Piotr Indyk | Massachusetts Institute of Technology |
| T.S. Jayram | IBM Almaden Research Center |
| Holly Jin | |
| Michael Jordan | University of California, Berkeley |
| Satyen Kale | Microsoft Research, Redmond |
| Chandrika Kamath | Lawrence Livermore National Laboratory |
| Ravi Kannan | Microsoft Research, India |
| Ping Li | Cornell University |
| Jun Liu | Harvard University |
| Jitendra Malik | University of California, Berkeley |
| Milena Mihail | Georgia Institute of Technology |
| Partha Niyogi | University of Chicago |
| Elizabeth Purdom | University of California, Berkeley |
| Amin Saberi | Stanford University |
| Yoram Singer | Google Research, Mountain View |
| Daniel Spielman | Yale University |
| Nathan Srebro | University of Chicago |
| Nikhil Srivastava | Yale University |
| Joel Tropp | California Institute of Technology |
| Chris Wiggins | Columbia University |
| Yuan Yao | Stanford University |
| Tong Zhang | Rutgers University |
| Petros Drineas | Rensselaer Polytechnic Institute |
| Art Owen | Stanford University |
| Haesun Park | Georgia Institute of Technology |
| Tomaso Poggio | Massachusetts Institute of Technology |
| Sam Roweis | University of Toronto |
| Eugene Tyrtyshnikov | Russian Academy of Science |
| Chris Volinsky | AT&T Research |
|
|
|
|
|
 |
 |