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» On Learning Boolean Functions
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SIGECOM
2004
ACM
135views ECommerce» more  SIGECOM 2004»
16 years 3 days ago
Applying learning algorithms to preference elicitation
We consider the parallels between the preference elicitation problem in combinatorial auctions and the problem of learning an unknown function from learning theory. We show that l...
Sébastien Lahaie, David C. Parkes
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
15 years 10 months ago
Spectral Regression: A Unified Approach for Sparse Subspace Learning
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
Deng Cai, Xiaofei He, Jiawei Han
GECCO
2009
Springer
16 years 1 months ago
Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change
In this paper, we rigorously analyse how the magnitude and frequency of change may affect the performance of the algorithm (1+1) EAdyn on a set of artificially designed pseudo-Bo...
Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao
COCO
2005
Springer
150views Algorithms» more  COCO 2005»
16 years 7 days ago
The Quantum Adversary Method and Classical Formula Size Lower Bounds
We introduce two new complexity measures for Boolean functions, which we name sumPI and maxPI. The quantity sumPI has been emerging through a line of research on quantum query com...
Sophie Laplante, Troy Lee, Mario Szegedy
GLOBECOM
2009
IEEE
15 years 10 months ago
Fair Energy-Efficient Resource Allocation over Fading TDMA Channels
In this paper, we consider the energy-efficient resource allocation that minimizes a general cost function of average user powers in wireless networks. A class of so-called -fair c...
Xin Wang, Di Wang, Hanqi Zhuang, Salvatore D. Morg...