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KDD
2010
ACM
274views Data Mining» more  KDD 2010»
14 years 1 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICDM
2007
IEEE
148views Data Mining» more  ICDM 2007»
14 years 1 months ago
Sample Selection for Maximal Diversity
The problem of selecting a sample subset sufficient to preserve diversity arises in many applications. One example is in the design of recombinant inbred lines (RIL) for genetic a...
Feng Pan, Adam Roberts, Leonard McMillan, David Th...
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
13 years 11 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang
ICDM
2010
IEEE
146views Data Mining» more  ICDM 2010»
13 years 7 months ago
One-Class Matrix Completion with Low-Density Factorizations
Consider a typical recommendation problem. A company has historical records of products sold to a large customer base. These records may be compactly represented as a sparse custom...
Vikas Sindhwani, Serhat Selcuk Bucak, Jianying Hu,...
ICDM
2010
IEEE
111views Data Mining» more  ICDM 2010»
13 years 7 months ago
ValuePick: Towards a Value-Oriented Dual-Goal Recommender System
Given a user in a social network, which new friends should we recommend, the dual goal being to achieve user satisfaction and good network connectivity? Similarly, which new produc...
Leman Akoglu, Christos Faloutsos