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JMLR
2012
12 years 24 days ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
ISQED
2005
IEEE
81views Hardware» more  ISQED 2005»
14 years 4 months ago
Exact Algorithms for Coupling Capacitance Minimization by Adding One Metal Layer
Due to the rapid development of manufacturing process technology and tight marketing schedule, the chip design and manufacturing always work toward an integrated solution to achie...
Hua Xiang, Kai-Yuan Chao, Martin D. F. Wong
ESWA
2007
100views more  ESWA 2007»
13 years 10 months ago
Using memetic algorithms with guided local search to solve assembly sequence planning
The goal of assembly planning consists in generating feasible sequences to assemble a product and selecting an efficient assembly sequence from which related constraint factors su...
Hwai-En Tseng, Wen-Pai Wang, Hsun-Yi Shih
ML
2002
ACM
167views Machine Learning» more  ML 2002»
13 years 10 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...
ICML
2005
IEEE
14 years 11 months ago
Fast inference and learning in large-state-space HMMs
For Hidden Markov Models (HMMs) with fully connected transition models, the three fundamental problems of evaluating the likelihood of an observation sequence, estimating an optim...
Sajid M. Siddiqi, Andrew W. Moore