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JMLR
2010
154views more  JMLR 2010»
15 years 1 months ago
MOA: Massive Online Analysis
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collecti...
Albert Bifet, Geoff Holmes, Richard Kirkby, Bernha...

Publication
335views
13 years 9 months ago
Person Re-Identification: What Features are Important?
State-of-the-art person re-identi cation methods seek robust person matching through combining various feature types. Often, these features are implicitly assigned with a single ve...
Chunxiao Liu, Shaogang Gong, Chen Change Loy, Xing...
ICPR
2004
IEEE
16 years 7 months ago
Relaxation Labeling Processes for Protein Secondary Structure Prediction
The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
Giacomo Colle, Marcello Pelillo
ICML
2009
IEEE
16 years 7 months ago
Partially supervised feature selection with regularized linear models
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
Thibault Helleputte, Pierre Dupont
ICML
2004
IEEE
16 years 7 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu