CS: Full set of presentations made at the 2010 Modern Massive Data Sets (MMDS 2010)

I mentioned an incomplete set of presentations last time, but it looks like the MMDS 2010 conference organizers have followed through and have gotten all of them and published it on their website, here is the list. Enjoy:

Tuesday, June 15, 2010. Theme: Large-scale Data and Large-scale Computation

Time	Talk
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

Wednesday, June 16, 2010. Theme: Networked Data and Algorithmic Tools

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

Thursday, June 17, 2010. Theme: Spectral Methods and Sparse Matrix Methods

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

Friday, June 18, 2010. Theme: Randomized Algorithms for Data

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

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