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DATE
2000
IEEE
169views Hardware» more  DATE 2000»
15 years 10 months ago
Transformational Placement and Synthesis
Novel methodology and algorithms to seamlessly integrate logic synthesis and physical placement through a transformational approach are presented. Contrary to most placement algor...
Wilm E. Donath, Prabhakar Kudva, Leon Stok, Paul V...
KDD
1999
ACM
199views Data Mining» more  KDD 1999»
15 years 10 months ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang
ICDM
2005
IEEE
153views Data Mining» more  ICDM 2005»
15 years 12 months ago
Speculative Markov Blanket Discovery for Optimal Feature Selection
In this paper we address the problem of learning the Markov blanket of a quantity from data in an efficient manner. Markov blanket discovery can be used in the feature selection ...
Sandeep Yaramakala, Dimitris Margaritis
ILP
2003
Springer
15 years 11 months ago
A Multi-relational Decision Tree Learning Algorithm - Implementation and Experiments
We describe an efficient implementation (MRDTL-2) of the Multi-relational decision tree learning (MRDTL) algorithm [23] which in turn was based on a proposal by Knobbe et al. [19] ...
Anna Atramentov, Hector Leiva, Vasant Honavar
ICDM
2007
IEEE
131views Data Mining» more  ICDM 2007»
15 years 10 months ago
Predicting and Optimizing Classifier Utility with the Power Law
When data collection is costly and/or takes a significant amount of time, an early prediction of the classifier performance is extremely important for the design of the data minin...
Mark Last