Lecture Notes in Computer Science - Advances in Machine Learning
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Published By Springer Berlin Heidelberg

9783642052231, 9783642052248

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Estimating Likelihoods for Topic Models

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_6 ◽

2009 ◽

pp. 51-64 ◽

Cited By ~ 19

Author(s):

Wray Buntine

Keyword(s):

Topic Models

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Injecting Structured Data to Generative Topic Model in Enterprise Settings

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_29 ◽

2009 ◽

pp. 382-395 ◽

Cited By ~ 3

Author(s):

Han Xiao ◽

Xiaojie Wang ◽

Chao Du

Keyword(s):

Topic Model ◽

Structured Data

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Query Selection via Weighted Entropy in Graph-Based Semi-supervised Classification

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_22 ◽

2009 ◽

pp. 278-292 ◽

Cited By ~ 1

Author(s):

Krikamol Muandet ◽

Sanparith Marukatat ◽

Cholwich Nattee

Keyword(s):

Supervised Classification ◽

Query Selection ◽

Weighted Entropy

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Cost-Sensitive Boosting: Fitting an Additive Asymmetric Logistic Regression Model

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_19 ◽

2009 ◽

pp. 234-247 ◽

Cited By ~ 1

Author(s):

Qiu-jie Li ◽

Yao-bin Mao ◽

Zhi-quan Wang ◽

Wen-bo Xiang

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model

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Accurate Probabilistic Error Bound for Eigenvalues of Kernel Matrix

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_14 ◽

2009 ◽

pp. 162-175 ◽

Cited By ~ 2

Author(s):

Lei Jia ◽

Shizhong Liao

Keyword(s):

Error Bound ◽

Kernel Matrix ◽

Probabilistic Error

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Feature Selection via Maximizing Neighborhood Soft Margin

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_13 ◽

2009 ◽

pp. 150-161

Author(s):

Qinghua Hu ◽

Xunjian Che ◽

Jinfu Liu

Keyword(s):

Feature Selection ◽

Soft Margin

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Weighted Nonnegative Matrix Co-Tri-Factorization for Collaborative Prediction

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_30 ◽

2009 ◽

pp. 396-411 ◽

Cited By ~ 11

Author(s):

Jiho Yoo ◽

Seungjin Choi

Keyword(s):

Nonnegative Matrix ◽

Collaborative Prediction

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Building a Decision Cluster Forest Model to Classify High Dimensional Data with Multi-classes

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_21 ◽

2009 ◽

pp. 263-277 ◽

Cited By ~ 3

Author(s):

Yan Li ◽

Edward Hung

Keyword(s):

High Dimensional Data ◽

High Dimensional ◽

Forest Model

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A Reformulation of Support Vector Machines for General Confidence Functions

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_10 ◽

2009 ◽

pp. 109-119 ◽

Cited By ~ 1

Author(s):

Yuhong Guo ◽

Dale Schuurmans

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines ◽

Confidence Functions

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Conditional Density Estimation with Class Probability Estimators

Lecture Notes in Computer Science - Advances in Machine Learning ◽

10.1007/978-3-642-05224-8_7 ◽

2009 ◽

pp. 65-81 ◽

Cited By ~ 14

Author(s):

Eibe Frank ◽

Remco R. Bouckaert

Keyword(s):

Density Estimation ◽

Conditional Density ◽

Conditional Density Estimation ◽

Class Probability

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Lecture Notes in Computer Science - Advances in Machine LearningLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Estimating Likelihoods for Topic Models

Injecting Structured Data to Generative Topic Model in Enterprise Settings

Query Selection via Weighted Entropy in Graph-Based Semi-supervised Classification

Cost-Sensitive Boosting: Fitting an Additive Asymmetric Logistic Regression Model

Accurate Probabilistic Error Bound for Eigenvalues of Kernel Matrix

Feature Selection via Maximizing Neighborhood Soft Margin

Weighted Nonnegative Matrix Co-Tri-Factorization for Collaborative Prediction

Building a Decision Cluster Forest Model to Classify High Dimensional Data with Multi-classes

A Reformulation of Support Vector Machines for General Confidence Functions

Conditional Density Estimation with Class Probability Estimators

Lecture Notes in Computer Science - Advances in Machine Learning
Latest Publications