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» Superset Learning Based on Generalized Loss Minimization
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TSP
2010
14 years 4 months ago
Universal randomized switching
Abstract--In this paper, we consider a competitive approach to sequential decision problems, suitable for a variety of signal processing applications where at each of a succession ...
Suleyman Serdar Kozat, Andrew C. Singer
ACL
1996
14 years 11 months ago
Fast Parsing Using Pruning and Grammar Specialization
We show how a general grammar may be automatically adapted for fast parsing of utterances from a specific domain by means of constituent pruning and grammar specialization based o...
Manny Rayner, David M. Carter
ICDM
2009
IEEE
149views Data Mining» more  ICDM 2009»
15 years 4 months ago
Accelerated Gradient Method for Multi-task Sparse Learning Problem
—Many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than...
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbon...
SOFSEM
2010
Springer
15 years 6 months ago
Regret Minimization and Job Scheduling
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
Yishay Mansour
COLT
2007
Springer
15 years 4 months ago
Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking
We describe and analyze a new approach for feature ranking in the presence of categorical features with a large number of possible values. It is shown that popular ranking criteria...
Sivan Sabato, Shai Shalev-Shwartz