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» Learning classifiers from only positive and unlabeled data
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ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 7 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
KDD
2009
ACM
266views Data Mining» more  KDD 2009»
14 years 2 months ago
OpinionMiner: a novel machine learning system for web opinion mining and extraction
Merchants selling products on the Web often ask their customers to share their opinions and hands-on experiences on products they have purchased. Unfortunately, reading through al...
Wei Jin, Hung Hay Ho, Rohini K. Srihari
PKDD
2010
Springer
158views Data Mining» more  PKDD 2010»
13 years 5 months ago
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Katya Scheinberg, Irina Rish
NIPS
2007
13 years 9 months ago
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
KDD
2007
ACM
198views Data Mining» more  KDD 2007»
14 years 8 months ago
Applying Link-Based Classification to Label Blogs
In analyzing data from social and communication networks, we encounter the problem of classifying objects where there is an explicit link structure amongst the objects. We study t...
Smriti Bhagat, Graham Cormode, Irina Rozenbaum