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ICML
2005
IEEE
16 years 5 months ago
Using additive expert ensembles to cope with concept drift
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Jeremy Z. Kolter, Marcus A. Maloof
ICML
2004
IEEE
16 years 5 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
STOC
2009
ACM
133views Algorithms» more  STOC 2009»
16 years 5 months ago
Near-perfect load balancing by randomized rounding
We consider and analyze a new algorithm for balancing indivisible loads on a distributed network with n processors. The aim is minimizing the discrepancy between the maximum and m...
Tobias Friedrich, Thomas Sauerwald
KDD
2006
ACM
177views Data Mining» more  KDD 2006»
16 years 4 months ago
Topics over time: a non-Markov continuous-time model of topical trends
This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...
Xuerui Wang, Andrew McCallum
EDBT
2006
ACM
194views Database» more  EDBT 2006»
16 years 4 months ago
Hermes - A Framework for Location-Based Data Management
The aim of this paper is to demonstrate Hermes, a robust framework capable of aiding a spatio-temporal database developer in modeling, constructing and querying a database with dyn...
Nikos Pelekis, Yannis Theodoridis, Spyros Vosinaki...