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AAAI
2007
15 years 5 months ago
Combining Multiple Heuristics Online
We present black-box techniques for learning how to interleave the execution of multiple heuristics in order to improve average-case performance. In our model, a user is given a s...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
107
Voted
ICML
2010
IEEE
15 years 4 months ago
Active Learning for Multi-Task Adaptive Filtering
In this paper, we propose an Active Learning (AL) framework for the Multi-Task Adaptive Filtering (MTAF) problem. Specifically, we explore AL approaches to rapidly improve an MTAF...
Abhay Harpale, Yiming Yang
ICDE
2012
IEEE
252views Database» more  ICDE 2012»
13 years 5 months ago
Approximate String Membership Checking: A Multiple Filter, Optimization-Based Approach
— We consider the approximate string membership checking (ASMC) problem of extracting all the strings or substrings in a document that approximately match some string in a given ...
Chong Sun, Jeffrey F. Naughton, Siddharth Barman
117
Voted
EUROCRYPT
2009
Springer
16 years 3 months ago
Realizing Hash-and-Sign Signatures under Standard Assumptions
Currently, there are relatively few instances of "hash-and-sign" signatures in the standard model. Moreover, most current instances rely on strong and less studied assum...
Susan Hohenberger, Brent Waters
125
Voted
CEC
2007
IEEE
15 years 9 months ago
Parameter calibration using meta-algorithms
— Calibrating an evolutionary algorithm (EA) means finding the right values of algorithm parameters for a given problem. This issue is highly relevant, because it has a high imp...
W. A. de Landgraaf, A. E. Eiben, Volker Nannen