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PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
15 years 2 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...
TEC
2010
126views more  TEC 2010»
14 years 11 months ago
Learning the Large-Scale Structure of the MAX-SAT Landscape Using Populations
A new algorithm for solving MAX-SAT problems is introduced which clusters good solutions, and restarts the search from the closest feasible solution to the centroid of each cluster...
Mohamed Qasem, Adam Prügel-Bennett
145
Voted
CVPR
2001
IEEE
16 years 6 months ago
Small Sample Learning during Multimedia Retrieval using BiasMap
All positive examples are alike; each negative example is negative in its own way. During interactive multimedia information retrieval, the number of training samples fed-back by ...
Xiang Sean Zhou, Thomas S. Huang
ICPR
2008
IEEE
16 years 5 months ago
Component-wise parameter smoothing for learning mixture models
In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
Bala Rajaratnam, Chandan K. Reddy
HICSS
2009
IEEE
147views Biometrics» more  HICSS 2009»
15 years 11 months ago
Determining a Firm's Optimal Outsourcing Rate: A Learning Model Perspective
We present a decision model of a firm’s optimal outsourcing rate as an extension of Cha et. al [1]’s previous work on the economic risk of knowledge loss and deskilling in the...
Hoon S. Cha, David E. Pingry, Matt E. Thatcher