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153
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ALT
2002
Springer
15 years 11 months ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky
IROS
2009
IEEE
132views Robotics» more  IROS 2009»
15 years 9 months ago
Segregation in swarms of mobile robots based on the Brazil nut effect
— We study a simple algorithm inspired by the Brazil nut effect for achieving segregation in a swarm of mobile robots. The algorithm lets each robot mimic a particle of a certain...
Roderich Groß, Stéphane Magnenat, Fra...
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
15 years 9 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
CF
2009
ACM
15 years 9 months ago
Quantitative analysis of sequence alignment applications on multiprocessor architectures
The exponential growth of databases that contains biological information (such as protein and DNA data) demands great efforts to improve the performance of computational platforms...
Friman Sánchez, Alex Ramírez, Mateo ...
128
Voted
CVPR
2008
IEEE
15 years 9 months ago
Scene understanding with discriminative structured prediction
Spatial priors play crucial roles in many high-level vision tasks, e.g. scene understanding. Usually, learning spatial priors relies on training a structured output model. In this...
Jinhui Yuan, Jianmin Li, Bo Zhang