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KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 4 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
215
Voted
SDM
2012
SIAM
285views Data Mining» more  SDM 2012»
13 years 5 months ago
A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets
Given the ubiquity of time series data, the data mining community has spent significant time investigating the best time series similarity measure to use for various tasks and dom...
Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thana...
95
Voted
ICDM
2003
IEEE
100views Data Mining» more  ICDM 2003»
15 years 8 months ago
Tractable Group Detection on Large Link Data Sets
Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, hu...
Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider
PKDD
2009
Springer
117views Data Mining» more  PKDD 2009»
15 years 10 months ago
New Regularized Algorithms for Transductive Learning
Abstract. We propose a new graph-based label propagation algorithm for transductive learning. Each example is associated with a vertex in an undirected graph and a weighted edge be...
Partha Pratim Talukdar, Koby Crammer
PKDD
2009
Springer
169views Data Mining» more  PKDD 2009»
15 years 10 months ago
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation
The goal of approximate policy evaluation is to “best” represent a target value function according to a specific criterion. Temporal difference methods and Bellman residual m...
Jeffrey Johns, Marek Petrik, Sridhar Mahadevan