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KDD
2005
ACM
160views Data Mining» more  KDD 2005»
10 years 4 months ago
Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering
Heterogeneous data co-clustering has attracted more and more attention in recent years due to its high impact on various applications. While the co-clustering algorithms for two t...
Bin Gao, Tie-Yan Liu, Xin Zheng, QianSheng Cheng, ...
KDD
2006
ACM
253views Data Mining» more  KDD 2006»
10 years 4 months ago
Adaptive Website Design Using Caching Algorithms
Visitors enter a website through a variety of means, including web searches, links from other sites, and personal bookmarks. In some cases the first page loaded satisfies the visi...
Justin Brickell, Inderjit S. Dhillon, Dharmendra S...
KDD
2007
ACM
244views Data Mining» more  KDD 2007»
10 years 4 months ago
A Recommender System Based on Local Random Walks and Spectral Methods
In this paper, we design recommender systems for weblogs based on the link structure among them. We propose algorithms based on refined random walks and spectral methods. First, w...
Zeinab Abbassi, Vahab S. Mirrokni
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
10 years 4 months ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen
KDD
2007
ACM
220views Data Mining» more  KDD 2007»
10 years 4 months ago
SCAN: a structural clustering algorithm for networks
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
10 years 4 months ago
GraphScope: parameter-free mining of large time-evolving graphs
How can we find communities in dynamic networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity timepoints in ...
Jimeng Sun, Christos Faloutsos, Spiros Papadimitri...
KDD
2007
ACM
132views Data Mining» more  KDD 2007»
10 years 4 months ago
A scalable modular convex solver for regularized risk minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and different r...
Choon Hui Teo, Alex J. Smola, S. V. N. Vishwanatha...
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
10 years 4 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
KDD
2009
ACM
216views Data Mining» more  KDD 2009»
10 years 4 months ago
Finding a team of experts in social networks
Given a task T , a pool of individuals X with different skills, and a social network G that captures the compatibility among these individuals, we study the problem of finding X ,...
Theodoros Lappas, Kun Liu, Evimaria Terzi
STOC
2009
ACM
99views Algorithms» more  STOC 2009»
10 years 4 months ago
Testing juntas nearly optimally
A function on n variables is called a k-junta if it depends on at most k of its variables. In this article, we show that it is possible to test whether a function is a k-junta or ...
Eric Blais
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