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ICML
2009
IEEE
16 years 7 months ago
Robust bounds for classification via selective sampling
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Nicolò Cesa-Bianchi, Claudio Gentile, Franc...
151
Voted
KDD
2006
ACM
107views Data Mining» more  KDD 2006»
16 years 6 months ago
Out-of-core frequent pattern mining on a commodity PC
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
Gregory Buehrer, Srinivasan Parthasarathy, Amol Gh...
KDD
2005
ACM
92views Data Mining» more  KDD 2005»
16 years 6 months ago
Summarizing itemset patterns: a profile-based approach
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
Xifeng Yan, Hong Cheng, Jiawei Han, Dong Xin
RECOMB
2006
Springer
16 years 6 months ago
Simple and Fast Inverse Alignment
For as long as biologists have been computing alignments of sequences, the question of what values to use for scoring substitutions and gaps has persisted. While some choices for s...
John D. Kececioglu, Eagu Kim
ICCAD
2004
IEEE
180views Hardware» more  ICCAD 2004»
16 years 3 months ago
Physical placement driven by sequential timing analysis
Traditional timing-driven placement considers only combinational delays and does not take into account the potential of subsequent sequential optimization steps. As a result, the ...
Aaron P. Hurst, Philip Chong, Andreas Kuehlmann