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» Approximation algorithms for budgeted learning problems
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STOC
1993
ACM
141views Algorithms» more  STOC 1993»
15 years 1 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
TON
2008
139views more  TON 2008»
14 years 9 months ago
Stochastic learning solution for distributed discrete power control game in wireless data networks
Distributed power control is an important issue in wireless networks. Recently, noncooperative game theory has been applied to investigate interesting solutions to this problem. Th...
Yiping Xing, Rajarathnam Chandramouli
COCO
2005
Springer
99views Algorithms» more  COCO 2005»
15 years 3 months ago
On the Complexity of Succinct Zero-Sum Games
We study the complexity of solving succinct zero-sum games, i.e., the games whose payoff matrix M is given implicitly by a Boolean circuit C such that M(i, j) = C(i, j). We comple...
Lance Fortnow, Russell Impagliazzo, Valentine Kaba...
GECCO
2009
Springer
134views Optimization» more  GECCO 2009»
15 years 2 months ago
Estimating the distribution and propagation of genetic programming building blocks through tree compression
Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Progr...
Robert I. McKay, Xuan Hoai Nguyen, James R. Cheney...
VLDB
2007
ACM
137views Database» more  VLDB 2007»
15 years 3 months ago
Detecting Attribute Dependencies from Query Feedback
Real-world datasets exhibit a complex dependency structure among the data attributes. Learning this structure is a key task in automatic statistics configuration for query optimi...
Peter J. Haas, Fabian Hueske, Volker Markl