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ICML
1996
IEEE
16 years 5 months ago
Learning Evaluation Functions for Large Acyclic Domains
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Justin A. Boyan, Andrew W. Moore
CVPR
2009
IEEE
15 years 11 months ago
Optimal scanning for faster object detection
Recent years have seen the development of fast and accurate algorithms for detecting objects in images. However, as the size of the scene grows, so do the running-times of these a...
Nicholas J. Butko, Javier R. Movellan
GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
15 years 10 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
GRAPHITE
2003
ACM
15 years 9 months ago
Varying rendering fidelity by exploiting human change blindness
The complexity of most virtual environments prevents them being rendered in real time even on modern graphics hardware. Knowledge of the visual system of the user viewing the envi...
Kirsten Cater, Alan Chalmers, Colin Dalton
158
Voted
ICDCS
2010
IEEE
15 years 8 months ago
Stochastic Steepest-Descent Optimization of Multiple-Objective Mobile Sensor Coverage
—We propose a steepest descent method to compute optimal control parameters for balancing between multiple performance objectives in stateless stochastic scheduling, wherein the ...
Chris Y. T. Ma, David K. Y. Yau, Nung Kwan Yip, Na...