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Sparse modeling: some unifying theory and “topic-imaging”
Published on 2011-05-064818 Views
Information technology has enabled collection of massive amounts of data in science, engineering, social science, finance and beyond. Extracting useful information from massive and high-dimensional d
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Presentation
Some Unifying Theory and Topic Imaging00:00
David Blackwell (1919-2010)00:09
IT revolution --> data revolution01:09
Spectrum of Media Reporting03:31
Improves News Media Analysis, Improves News Media, Improves How the World Works04:10
Our Approach to Media Analysis: Topic-Imaging05:29
Case Study: Topic Image of Business Section of NYT06:16
Case Study (cont)07:15
Solving a modern data problem09:11
Today’s Talk10:06
Occam’s Razor10:48
Occam’s Razor via Model Selection in Linear Regression11:39
Sparse Modeling in the 70’s: Model Selection12:34
Model Selection for Topic-Imaging Problem15:00
Lasso: L1-norm as a Penalty17:11
Lasso: Computation and Evaluation18:15
Lasso: Theoretical Work19:54
Regularized M-estimation including Lasso23:05
Example 1: Lasso (sparse linear model)24:21
Example 2: Structured (inverse) Cov. Estimation25:49
Example 3: Low-rank matrix approximation26:11
Unified Analysis27:37
Why can we estimate parameters?29:25
In high-dim and when r corresponds to true structure (e.g. sparsity), why estimation is still possible30:33
Main Result for Regularized M-estimation33:44
Examples of decomposable regularizers34:38
Recovering Existing Result in Bickel et al 0834:58
Obtaining New Result (Robustness of Lasso)35:55
Summary of unified analysis36:50
Partial Summary37:21
Topic Imaging: Subject-Specific Summarization of Document Corpus37:59
Our approach: predictive sparse methods + human experiment38:26
Sample Result from Our Approach (Document-S^3)39:10
Document Corpus40:19
Pre-processing40:56
Matrix Set-up and Labeling41:18
List of Generation Methods41:38
Flow Chart of Our Automatic Summarization42:00
How to Select from 120 Possible Lists for One Topic?42:10
Prediction Is Not the Goal43:17
A Human Experiment44:26
Running Human Experiment45:18
Human Experiment Results in a Glance46:35
Qualitative Summary of Human Exp. Results47:25
Summary of talk48:12
Future Directions: Richer Data/Subejct Applications49:36
Future Directions: Research Topics50:00
Acknowledgements50:54
Stat-news project (El Ghaoui and Yu)51:21