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» Evaluating algorithms that learn from data streams
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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
15 years 4 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
TMM
2002
158views more  TMM 2002»
15 years 6 months ago
Foveated video quality assessment
Most image and video compression algorithms that have been proposed to improve picture quality relative to compression efficiency have either been designed based on objective crite...
Sanghoon Lee, Marios S. Pattichis, Alan C. Bovik
ICMAS
2000
15 years 8 months ago
Assessing Usage Patterns to Improve Data Allocation via Auctions
The data allocation problem in incomplete information environments consisting of self-motivated servers responding to users' queries is considered. Periodically, the servers ...
Rina Azoulay-Schwartz, Sarit Kraus
MCS
2010
Springer
15 years 11 months ago
Online Non-stationary Boosting
Abstract. Oza’s Online Boosting algorithm provides a version of AdaBoost which can be trained in an online way for stationary problems. One perspective is that this enables the p...
Adam Pocock, Paraskevas Yiapanis, Jeremy Singer, M...
ICIP
2003
IEEE
16 years 8 months ago
Evaluation strategies for automatic linguistic indexing of pictures
With the rapid technological advances in machine learning and data mining, it is now possible to train computers with hundreds of semantic concepts for the purpose of annotating i...
James Ze Wang, Jia Li, Sui Ching Lin