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NIPS
1994
15 years 5 months ago
Learning Stochastic Perceptrons Under k-Blocking Distributions
We present a statistical method that PAC learns the class of stochastic perceptrons with arbitrary monotonic activation function and weights wi {-1, 0, +1} when the probability d...
Mario Marchand, Saeed Hadjifaradji
CORR
2011
Springer
183views Education» more  CORR 2011»
14 years 8 months ago
Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction
For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the tra...
Foster J. Provost, Gary M. Weiss
ATAL
2007
Springer
15 years 8 months ago
A reinforcement learning based distributed search algorithm for hierarchical peer-to-peer information retrieval systems
The dominant existing routing strategies employed in peerto-peer(P2P) based information retrieval(IR) systems are similarity-based approaches. In these approaches, agents depend o...
Haizheng Zhang, Victor R. Lesser
MOBIHOC
2012
ACM
13 years 7 months ago
Spatial spectrum access game: nash equilibria and distributed learning
A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mecha...
Xu Chen, Jianwei Huang
CVPR
2001
IEEE
16 years 6 months ago
Learning Probabilistic Distribution Model for Multi-View Face Detection
Modeling subspaces of a distribution of interest in high dimensional spaces is a challenging problem in pattern analysis. In this paper, we present a novel framework for pose inva...
Lie Gu, Stan Z. Li, HongJiang Zhang