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» Superset Learning Based on Generalized Loss Minimization
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TSP
2010
14 years 11 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
15 years 5 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 11 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
16 years 1 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 10 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