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» A Generalization of Automatic Sequences
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KDD
2003
ACM
194views Data Mining» more  KDD 2003»
16 years 5 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 5 months ago
Sequential cost-sensitive decision making with reinforcement learning
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Edwin P. D. Pednault, Naoki Abe, Bianca Zadrozny
RECOMB
2004
Springer
16 years 4 months ago
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...
171
Voted
STOC
2007
ACM
142views Algorithms» more  STOC 2007»
16 years 4 months ago
Lower bounds for randomized read/write stream algorithms
Motivated by the capabilities of modern storage architectures, we consider the following generalization of the data stream model where the algorithm has sequential access to multi...
Paul Beame, T. S. Jayram, Atri Rudra
STOC
2007
ACM
146views Algorithms» more  STOC 2007»
16 years 4 months ago
Playing games with approximation algorithms
In an online linear optimization problem, on each period t, an online algorithm chooses st S from a fixed (possibly infinite) set S of feasible decisions. Nature (who may be adve...
Sham M. Kakade, Adam Tauman Kalai, Katrina Ligett
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