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» Introduction to Randomized Algorithms
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126
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TSMC
2002
110views more  TSMC 2002»
15 years 3 months ago
Complexity reduction for "large image" processing
We present a method for sampling feature vectors in large (e.g., 2000 5000 16 bit) images that finds subsets of pixel locations which represent "regions" in the image. Sa...
Nikhil R. Pal, James C. Bezdek
198
Voted
CVPR
2009
IEEE
16 years 9 months ago
D - Clutter: Building object model library from unsupervised segmentation of cluttered scenes
Autonomous systems which learn and utilize a limited visual vocabulary have wide spread applications. Enabling such systems to segment a set of cluttered scenes into objects is ...
Chandra Kambhamettu, Dimitris N. Metaxas, Gowri So...
CORR
2010
Springer
123views Education» more  CORR 2010»
15 years 2 months ago
Feature Construction for Relational Sequence Learning
Abstract. We tackle the problem of multi-class relational sequence learning using relevant patterns discovered from a set of labelled sequences. To deal with this problem, firstly...
Nicola Di Mauro, Teresa Maria Altomare Basile, Ste...
101
Voted
ICRA
2010
IEEE
142views Robotics» more  ICRA 2010»
15 years 2 months ago
A quadratic regulator-based heuristic for rapidly exploring state space
Abstract— Kinodynamic planning algorithms like RapidlyExploring Randomized Trees (RRTs) hold the promise of finding feasible trajectories for rich dynamical systems with complex...
Elena Leah Glassman, Russ Tedrake
163
Voted
ISI
2010
Springer
15 years 1 months ago
Measuring behavioral trust in social networks
Abstract—Trust is an important yet complex and little understood dyadic relation among actors in a social network. There are many dimensions to trust; trust plays an important ro...
Sibel Adali, Robert Escriva, Mark K. Goldberg, Myk...