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ICDM
2007
IEEE
106views Data Mining» more  ICDM 2007»
13 years 11 months ago
High-Speed Function Approximation
We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on mod...
Biswanath Panda, Mirek Riedewald, Johannes Gehrke,...
ICDM
2007
IEEE
157views Data Mining» more  ICDM 2007»
13 years 11 months ago
Failure Prediction in IBM BlueGene/L Event Logs
Frequent failures are becoming a serious concern to the community of high-end computing, especially when the applications and the underlying systems rapidly grow in size and compl...
Yinglung Liang, Yanyong Zhang, Hui Xiong, Ramendra...
ICDM
2007
IEEE
182views Data Mining» more  ICDM 2007»
13 years 11 months ago
Co-ranking Authors and Documents in a Heterogeneous Network
The problem of evaluating scientific publications and their authors is important, and as such has attracted increasing attention. Recent graph-theoretic ranking approaches have d...
Ding Zhou, Sergey A. Orshanskiy, Hongyuan Zha, C. ...
ICDM
2007
IEEE
119views Data Mining» more  ICDM 2007»
13 years 11 months ago
Detecting Fractures in Classifier Performance
David A. Cieslak, Nitesh V. Chawla
ICDM
2007
IEEE
124views Data Mining» more  ICDM 2007»
13 years 11 months ago
Community Learning by Graph Approximation
Learning communities from a graph is an important problem in many domains. Different types of communities can be generalized as link-pattern based communities. In this paper, we p...
Bo Long, Xiaoyun Xu, Zhongfei (Mark) Zhang, Philip...
ICDM
2007
IEEE
184views Data Mining» more  ICDM 2007»
13 years 11 months ago
Bayesian Folding-In with Dirichlet Kernels for PLSI
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
13 years 11 months ago
Incremental Subspace Clustering over Multiple Data Streams
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Qi Zhang, Jinze Liu, Wei Wang 0010
ICDM
2007
IEEE
122views Data Mining» more  ICDM 2007»
13 years 11 months ago
Zonal Co-location Pattern Discovery with Dynamic Parameters
Zonal co-location patterns represent subsets of featuretypes that are frequently located in a subset of space (i.e., zone). Discovering zonal spatial co-location patterns is an im...
Mete Celik, James M. Kang, Shashi Shekhar
ICDM
2007
IEEE
140views Data Mining» more  ICDM 2007»
13 years 11 months ago
Finding Cohesive Clusters for Analyzing Knowledge Communities
Documents and authors can be clustered into “knowledge communities” based on the overlap in the papers they cite. We introduce a new clustering algorithm, Streemer, which fin...
Vasileios Kandylas, S. Phineas Upham, Lyle H. Unga...
ICDM
2007
IEEE
137views Data Mining» more  ICDM 2007»
13 years 11 months ago
Locally Constrained Support Vector Clustering
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan