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ASUNAM
2010
IEEE
15 years 6 months ago
Semi-Supervised Classification of Network Data Using Very Few Labels
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
Frank Lin, William W. Cohen
NIPS
2001
15 years 5 months ago
Algorithmic Luckiness
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Ralf Herbrich, Robert C. Williamson
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
14 years 7 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
JUCS
2010
176views more  JUCS 2010»
15 years 2 months ago
An Approach to Generation of Decision Rules
: Classical classification and clustering based on equivalence relations are very important tools in decision-making. An equivalence relation is usually determined by properties of...
Zhang Mingyi, Danning Li, Zhang Ying
140
Voted
ICML
2007
IEEE
16 years 5 months ago
An integrated approach to feature invention and model construction for drug activity prediction
We present a new machine learning approach for 3D-QSAR, the task of predicting binding affinities of molecules to target proteins based on 3D structure. Our approach predicts bind...
David Page, Jesse Davis, Soumya Ray, Vítor ...