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Thought this was cool: MMDS2012 Videos are out ! Workshop on Algorithms for Modern Massive Data Sets

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Back in August, the MMDS 2012 Slides were out. Now it’s time for the videos, woohoo! Enjoy:

10:00 – 11:00 Tutorial: Jiawei Han 
A Meta Path-Based Approach for Similarity Search and Mining of Heterogeneous Information Networks
Show Video
11:00 – 11:30 Alexander Gray 
Faster Learning for Massive Datasets
Show Video
11:30 – 12:00 Christopher Re 
Hazy: Making Data-driven Statistical Applications Easier to Build and Maintain
Show Video
2:00 – 3:00 Tutorial: Peter Bartlett 
Model Selection and Recent Results for Large Scale Problems
Show Video
3:00 – 3:30 Noureddine El Karoui 
On Robust Regression Estimators in High-dimension
Show Video
3:30 – 4:00 Jure Leskovec 
Affiliation Network Models for Densely Overlapping Communities in Networks
Show Video
4:30 – 5:00 Haesun Park 
Nonnegative Matrix Factorizations for Clustering
Show Video
5:00 – 5:30 Fan Chung Graham 
Vectorized Laplacians for Dealing with High-dimensional Data Sets
Show Video
5:30 – 6:00 Joydeep Ghosh 
Actionable Mining of Large, Multi-relational Data using Localized Predictive Models
Show Video
9:00 – 10:00 Tutorial: DJ Patil 
When Algorithms Go Wrong: How Product Design Can Save Algorithmic Limitations
Book PDFs: Building Data Science Teams, Data Jujitsu
Show Video
10:00 – 10:30 Sean Fahey 
Big Data and Analytics for National Security
Show Video
11:00 – 11:30 Petros Drineas 
Leverage Scores, the Column Subset Selection Problem, and Least-squares Problems
Show Video
11:30 – 12:00 David Woodruff 
Low Rank Approximation and Regression in Input Sparsity Time
Show Video
12:00 – 12:30 Michael W. Mahoney 
Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments
Show Video
2:30 – 3:30 Tutorial: Rick Stevens 
The Biological, Algorithmic and Computational Challenges of Systems Biology
Show Video
3:30 – 4:00 Tiankai Tu 
Fault-Tolerant Parallel Analysis of Millisecond-Scale Molecular Dynamics Trajectories
4:30 – 5:00 Alexander Szalay 
Current Statistical Challenges in Large Astronomical Surveys
Show Video
5:00 – 5:30 Joseph Richards 
Astronomical Time Series Analysis for the Synoptic Survey Era
Show Video
5:30 – 6:00 Tony Cass 
Data Handling for LHC: Plans and Reality
Show Video
9:00 – 10:00 Tutorial: Michael Mitzenmacher 
Peeling Arguments: Invertible Bloom Lookup Tables and Biff Codes
Show Video
10:00 – 10:30 Frederic Chazal 
Detection and Approximation of Linear Structures in Metric Spaces
Show Video
11:00 – 11:30 Ping Li 
Probabilistic Hashing for Efficient Search and Learning on Massive Data
Show Video
11:30 – 12:00 Ashish Goel 
Real Time Social Search and Related Problems
Show Video
12:00 – 12:30 Andrew Goldberg 
Hub Labels in Databases: Shortest Paths for the Masses
Show Video
2:30 – 3:00 Theodore Johnson 
Data Stream Warehousing
Show Video
3:00 – 3:30 Josh Wills 
Experimenting at Scale
Show Video
3:30 – 4:00 Hang Li 
Large Scale Machine Learning for Query Document Matching in Web Search
Show Video
4:30 – 4:50 Blair Sullivan 
Branching Out: Quantifying Tree-like Structure in Complex Networks
Show Video
4:50 – 5:10 Mahdi Soltanolkotabi 
A Geometric Analysis of Subspace Clustering with Outliers
Show Video
5:10 – 5:30 Bahman Bahmani 
Scalable K-Means++
Show Video
5:30 – 6:00 Steve Bartel 
Analytics at Dropbox
9:00 – 10:00 Tutorial: Yi Ma 
The Pursuit of Low-dimensional Structures in High-dimensional Data
Show Video
10:00 – 10:30 Edoardo Airoldi 
Graphlets Decomposition of a Weighted Network
Show Video
11:00 – 11:30 Yiannis Koutis 
SDD Solvers: Bridging the Gap Between Theory and Practice
Show Video
11:30 – 12:00 Art Owen 
Bootstrapping r-fold Tensor Data
Show Video
12:00 – 12:30 Kamesh Madduri 
Algorithms and Tools for Scalable Graph Analytics
Show Video
2:30 – 3:00 Shaowei Lin 
Studying Model Asymptotics with Singular Learning Theory
Show Video
3:00 – 3:30 David Bindel 
Communities, Spectral Clustering, and Random Walks
Show Video
3:30 – 4:00 Ali Pinar 
The Block Two-Level Erdos-Renyi (BTER) Graph Model
Show Video
4:30 – 5:00 Xiao-Li Meng (presented by Alexander Blocker) 
Preprocessing, Multiphase Inference, and Massive Data in Theory and Practice
Show Video
5:00 – 5:30 Alfred Hero 
Hub Discovery in Large Correlation Networks
Show Video
5:30 – 6:00 Dan Feldman 
Google Your Life: Learning Sensors Data
Show Video

Thanks to Michael Mahoney (chair), Alex Shkolnik, Gunnar Carlsson, Petros Drineas for making these videos available.

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Written by cwyalpha

十二月 15, 2012 在 12:08 下午

发表在 Uncategorized


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