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IJRR
2010
162views more  IJRR 2010»
13 years 6 months ago
Planning under Uncertainty for Robotic Tasks with Mixed Observability
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
FOCS
2000
IEEE
13 years 12 months ago
Stable Distributions, Pseudorandom Generators, Embeddings and Data Stream Computation
In this article, we show several results obtained by combining the use of stable distributions with pseudorandom generators for bounded space. In particular: —We show that, for a...
Piotr Indyk
GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
14 years 1 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
CVPR
2000
IEEE
14 years 9 months ago
Fluid Structure and Motion Analysis from Multi-spectrum 2D Cloud Image Sequences
In this paper we present a novel approach to estimate and analyze 3D uid structure and motion of clouds from multi-spectrum 2D cloud image sequences. Accurate cloud-top structure ...
Lin Zhou, Chandra Kambhamettu, Dmitry B. Goldgof
ECCV
2010
Springer
13 years 7 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof