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» Incremental learning with temporary memory
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PEPM
2009
ACM
14 years 4 months ago
Self-adjusting computation: (an overview)
Many applications need to respond to incremental modifications to data. Being incremental, such modification often require incremental modifications to the output, making it po...
Umut A. Acar
IPPS
2007
IEEE
14 years 1 months ago
Programming Distributed Memory Sytems Using OpenMP
OpenMP has emerged as an important model and language extension for shared-memory parallel programming. On shared-memory platforms, OpenMP offers an intuitive, incremental approac...
Ayon Basumallik, Seung-Jai Min, Rudolf Eigenmann
ICML
2005
IEEE
14 years 8 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
KDD
1999
ACM
199views Data Mining» more  KDD 1999»
13 years 11 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
ICMCS
2009
IEEE
97views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Some new directions in graph-based semi-supervised learning
In this position paper, we first review the state-of-the-art in graph-based semi-supervised learning, and point out three limitations that are particularly relevant to multimedia ...
Xiaojin Zhu, Andrew B. Goldberg, Tushar Khot