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ICIP
2003
IEEE
16 years 5 months ago
Image compression with on-line and off-line learning
Images typically contain smooth regions, which are easily compressed by linear transforms, and high activity regions (edges, textures), which are harder to compress. To compress t...
Patrice Y. Simard, Christopher J. C. Burges, David...
IJCNN
2000
IEEE
15 years 8 months ago
Recursive Non Linear Models for On Line Traffic Prediction of VBR MPEG Coded Video Sources
Any performance evaluation of broadband networks requires modeling of the actual network traffic. Since multimedia services and especially MPEG coded video streams are expected to...
Anastasios D. Doulamis, Nikolaos D. Doulamis, Stef...
TEC
2008
165views more  TEC 2008»
15 years 3 months ago
Population-Based Incremental Learning With Associative Memory for Dynamic Environments
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its importance in real-world applications. Several app...
Shengxiang Yang, Xin Yao
135
Voted
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 3 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
134
Voted
IJCNN
2006
IEEE
15 years 9 months ago
Reinforcement Learning for Parameterized Motor Primitives
Abstract— One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement genera...
Jan Peters, Stefan Schaal