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137
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JMLR
2012
13 years 5 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
97
Voted
IJCNN
2006
IEEE
15 years 8 months ago
Rao-Blackwellized Particle Filtering for Sequential Speech Enhancement
— In this paper we present a method of sequential speech enhancement, where we infer clean speech signal using a Rao-Blackwellized particle filter (RBPF), given a noisecontamina...
Sunho Park, Seungjin Choi
IJCNN
2006
IEEE
15 years 8 months ago
Automated Model Selection (AMS) on Finite Mixtures: A Theoretical Analysis
— From the Bayesian Ying-Yang (BYY) harmony learning theory, a harmony function has been developed for finite mixtures with a novel property that its maximization can make model...
Jinwen Ma
ML
2006
ACM
110views Machine Learning» more  ML 2006»
15 years 2 months ago
Classification-based objective functions
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Michael Rimer, Tony Martinez
134
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CIKM
2011
Springer
14 years 2 months ago
Towards feature selection in network
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Quanquan Gu, Jiawei Han