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ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 6 days ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
13 years 12 months ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya
WWW
2008
ACM
14 years 6 months ago
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
We discover communities from social network data, and analyze the community evolution. These communities are inherent characteristics of human interaction in online social network...
Yu-Ru Lin, Yun Chi, Shenghuo Zhu, Hari Sundaram, B...
DATAMINE
2006
89views more  DATAMINE 2006»
13 years 5 months ago
Scalable Clustering Algorithms with Balancing Constraints
Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...
Arindam Banerjee, Joydeep Ghosh
LION
2007
Springer
192views Optimization» more  LION 2007»
13 years 12 months ago
Learning While Optimizing an Unknown Fitness Surface
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Roberto Battiti, Mauro Brunato, Paolo Campigotto