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CIB
2004
57views more  CIB 2004»
15 years 3 months ago
Identifying Global Exceptional Patterns in Multi-database Mining
In multi-database mining, there can be many local patterns (frequent itemsets or association rules) in each database. At the end of multi-database mining, it is necessary to analyz...
Chengqi Zhang, Meiling Liu, Wenlong Nie, Shichao Z...
121
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NIPS
2008
15 years 5 months ago
Linear Classification and Selective Sampling Under Low Noise Conditions
We provide a new analysis of an efficient margin-based algorithm for selective sampling in classification problems. Using the so-called Tsybakov low noise condition to parametrize...
Giovanni Cavallanti, Nicolò Cesa-Bianchi, C...
120
Voted
CORR
2000
Springer
84views Education» more  CORR 2000»
15 years 3 months ago
Robust Classification for Imprecise Environments
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building ro...
Foster J. Provost, Tom Fawcett
163
Voted
USS
2010
15 years 1 months ago
P4P: Practical Large-Scale Privacy-Preserving Distributed Computation Robust against Malicious Users
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
140
Voted
SDM
2008
SIAM
147views Data Mining» more  SDM 2008»
15 years 5 months ago
The Asymmetric Approximate Anytime Join: A New Primitive with Applications to Data Mining
It has long been noted that many data mining algorithms can be built on top of join algorithms. This has lead to a wealth of recent work on efficiently supporting such joins with ...
Lexiang Ye, Xiaoyue Wang, Dragomir Yankov, Eamonn ...