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ICCV
2009
IEEE
13 years 5 months ago
Learning with dynamic group sparsity
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
FGR
2004
IEEE
133views Biometrics» more  FGR 2004»
13 years 11 months ago
Finding Temporal Patterns by Data Decomposition
We present a new unsupervised learning technique for the discovery of temporal clusters in large data sets. Our method performs hierarchical decomposition of the data to find stru...
David C. Minnen, Christopher Richard Wren
ICML
2003
IEEE
14 years 8 months ago
Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution
Feature selection, as a preprocessing step to machine learning, has been effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improvin...
Lei Yu, Huan Liu
CG
2000
Springer
13 years 11 months ago
Lambda-Search in Game Trees - with Application to Go
This paper proposes a new method for searching two-valued (binary) game trees in games like chess or Go. Lambda-search uses null-moves together with different orders of threat-sequ...
Thomas Thomsen
ACL
2006
13 years 8 months ago
A Comparison of Alternative Parse Tree Paths for Labeling Semantic Roles
The integration of sophisticated inference-based techniques into natural language processing applications first requires a reliable method of encoding the predicate-argument struc...
Reid Swanson, Andrew S. Gordon