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» Using Machine Learning to Focus Iterative Optimization
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GECCO
2004
Springer
144views Optimization» more  GECCO 2004»
15 years 7 months ago
Feature Subset Selection, Class Separability, and Genetic Algorithms
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Erick Cantú-Paz
NIPS
1998
15 years 3 months ago
Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
Michael J. Kearns, Satinder P. Singh
122
Voted
MM
2010
ACM
177views Multimedia» more  MM 2010»
15 years 2 months ago
Image tag refinement towards low-rank, content-tag prior and error sparsity
The vast user-provided image tags on the popular photo sharing websites may greatly facilitate image retrieval and management. However, these tags are often imprecise and/or incom...
Guangyu Zhu, Shuicheng Yan, Yi Ma
AIEDAM
2011
14 years 9 months ago
Discovering implicit constraints in design
In familiar design domains, expert designers are able to quickly focus on “good designs”, based on constraints they have learned while exploring the design space. This ability ...
Madan Mohan Dabbeeru, Amitabha Mukerjee
JSS
2010
198views more  JSS 2010»
14 years 9 months ago
Accelerated collection of sensor data by mobility-enabled topology ranks
We study the problem of fast and energy-efficient data collection of sensory data using a mobile sink, in wireless sensor networks in which both the sensors and the sink move. Mot...
Constantinos Marios Angelopoulos, Sotiris E. Nikol...