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PAMI
2011
14 years 7 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
PKDD
2009
Springer
174views Data Mining» more  PKDD 2009»
15 years 7 months ago
Active and Semi-supervised Data Domain Description
Data domain description techniques aim at deriving concise descriptions of objects belonging to a category of interest. For instance, the support vector domain description (SVDD) l...
Nico Görnitz, Marius Kloft, Ulf Brefeld
117
Voted
ICML
2010
IEEE
15 years 1 months ago
From Transformation-Based Dimensionality Reduction to Feature Selection
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
Mahdokht Masaeli, Glenn Fung, Jennifer G. Dy
ETS
2002
IEEE
121views Hardware» more  ETS 2002»
15 years 15 days ago
Establishing Connections: Interactivity Factors for a Distance Education Course
Both academic institutions and businesses are exploring a shift from face-to-face instruction to distance learning. However, without the foundation of a systematic instructional d...
Diane Berger Ehrlich
ML
2000
ACM
150views Machine Learning» more  ML 2000»
15 years 15 days ago
Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Filippo Menczer, Richard K. Belew