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ML
2000
ACM
244views Machine Learning» more  ML 2000»
13 years 8 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski
GLOBECOM
2007
IEEE
13 years 10 months ago
A Novel False Congestion Detection Scheme for TCP over OBS Networks
– This paper introduces a novel congestion control scheme for TCP over OBS networks, called Statistical Additive Increase Multiplicative Decrease (SAIMD), which aims to improve t...
Basem Shihada, Pin-Han Ho, Qiong Zhang
NIPS
2007
13 years 10 months ago
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
Ruslan Salakhutdinov, Geoffrey E. Hinton
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
14 years 3 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
HICSS
2007
IEEE
134views Biometrics» more  HICSS 2007»
14 years 3 months ago
Modeling Enablers for Successful KM Implementation
Knowledge is recognized as a critical resource to gain and sustain competitive advantage in business. While many organizations are employing knowledge management (KM) initiatives,...
Vittal S. Anantatmula, Shivraj Kanungo