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FLAIRS
2004
15 years 8 months ago
Invariance of MLP Training to Input Feature De-correlation
In the neural network literature, input feature de-correlation is often referred as one pre-processing technique used to improve the MLP training speed. However, in this paper, we...
Changhua Yu, Michael T. Manry, Jiang Li
EUROIMSA
2006
299views Multimedia» more  EUROIMSA 2006»
15 years 8 months ago
Behavior Modeling using Bigram Frequencies for Client-Side Link Prefetching
The perceived latency for a user surfing the Internet is the target of a transparent and speculative algorithm that relies on a user behavior model. The model is based on past use...
Apostolos Georgakis, Haibo Li, Mihaela Gordan
ECCV
2010
Springer
15 years 8 months ago
Fast Optimization for Mixture Prior Models
Abstract. We consider the minimization of a smooth convex function regularized by the mixture of prior models. This problem is generally difficult to solve even each simpler regula...
Junzhou Huang, Shaoting Zhang, Dimitris N. Metaxas
AAMAS
2007
Springer
15 years 7 months ago
Parallel Reinforcement Learning with Linear Function Approximation
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Matthew Grounds, Daniel Kudenko
CORR
2006
Springer
99views Education» more  CORR 2006»
15 years 7 months ago
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
Jon Feldman, Ryan O'Donnell, Rocco A. Servedio