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ICML
1994
IEEE
15 years 1 months ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak
AI
2002
Springer
14 years 9 months ago
Learning cost-sensitive active classifiers
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
Russell Greiner, Adam J. Grove, Dan Roth
COLT
2010
Springer
14 years 7 months ago
Robust Selective Sampling from Single and Multiple Teachers
We present a new online learning algorithm in the selective sampling framework, where labels must be actively queried before they are revealed. We prove bounds on the regret of ou...
Ofer Dekel, Claudio Gentile, Karthik Sridharan
ICARIS
2010
Springer
14 years 6 months ago
An Information-Theoretic Approach for Clonal Selection Algorithms
In this research work a large set of the classical numerical functions were taken into account in order to understand both the search capability and the ability to escape from a lo...
Vincenzo Cutello, Giuseppe Nicosia, Mario Pavone, ...
ATMOS
2010
162views Optimization» more  ATMOS 2010»
14 years 7 months ago
Heuristics for the Traveling Repairman Problem with Profits
In the traveling repairman problem with profits, a repairman (also known as the server) visits a subset of nodes in order to collect time-dependent profits. The objective consists...
Thijs Dewilde, Dirk Cattrysse, Sofie Coene, Frits ...