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AROBOTS
2002
126views more  AROBOTS 2002»
14 years 11 months ago
Selecting Landmarks for Localization in Natural Terrain
We describe techniques to optimally select landmarks for performing mobile robot localization by matching terrain maps. The method is based upon a maximum-likelihood robot localiza...
Clark F. Olson
115
Voted
JMLR
2012
13 years 2 months ago
Krylov Subspace Descent for Deep Learning
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
Oriol Vinyals, Daniel Povey
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
14 years 9 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim
CEC
2007
IEEE
15 years 3 months ago
Mobile robot global localization using differential evolution and particle swarm optimization
For a mobile robot to move in a known environment and operate successfully, first it needs to robustly determine its initial position and orientation relative to the map, and then ...
Ali R. Vahdat, Naser NourAshrafoddin, Saeed Shiry ...
114
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ECCV
2010
Springer
15 years 5 months ago
Face Liveness Detection from A Single Image with Sparse Low Rank Bilinear Discriminative Model
Spoofing with photograph or video is one of the most common manner to circumvent a face recognition system. In this paper, we present a real-time and non-intrusive method to addre...