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COLT
2007
Springer
15 years 5 months ago
Resource-Bounded Information Gathering for Correlation Clustering
We present a new class of problems, called resource-bounded information gathering for correlation clustering. Our goal is to perform correlation clustering under circumstances in w...
Pallika Kanani, Andrew McCallum
STOC
2009
ACM
181views Algorithms» more  STOC 2009»
16 years 9 days ago
The detectability lemma and quantum gap amplification
The quantum analog of a constraint satisfaction problem is a sum of local Hamiltonians - each (term of the) Hamiltonian specifies a local constraint whose violation contributes to...
Dorit Aharonov, Itai Arad, Zeph Landau, Umesh V. V...
ICDM
2010
IEEE
135views Data Mining» more  ICDM 2010»
14 years 9 months ago
Learning a Bi-Stochastic Data Similarity Matrix
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
Fei Wang, Ping Li, Arnd Christian König
ICDE
2007
IEEE
182views Database» more  ICDE 2007»
16 years 1 months ago
Discriminative Frequent Pattern Analysis for Effective Classification
The application of frequent patterns in classification appeared in sporadic studies and achieved initial success in the classification of relational data, text documents and graph...
Hong Cheng, Xifeng Yan, Jiawei Han, Chih-Wei Hsu
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 3 days ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis