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IJCAI
1997
15 years 1 months ago
Object Identification in a Bayesian Context
Object identification—the task of deciding that two observed objects are in fact one and the same object—is a fundamental requirement for any situated agent that reasons about...
Timothy Huang, Stuart J. Russell
ICCV
1995
IEEE
15 years 3 months ago
Fast Object Recognition in Noisy Images Using Simulated Annealing
A fast simulatedannealingalgorithmis developed for automatic object recognition. The object recognition problem is addressed as the problem of best describing a match between a hy...
Margrit Betke, Nicholas C. Makris
MA
1999
Springer
87views Communications» more  MA 1999»
15 years 4 months ago
Communicating Neural Network Knowledge between Agents in a Simulated Aerial Reconnaissance System
In order to maintain their performance in a dynamic environment, agents may be required to modify their learning behavior during run-time. If an agent utilizes a rule-based system...
Stephen Quirolgico, K. Canfield, Timothy W. Finin,...
JMLR
2012
13 years 2 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
ICASSP
2009
IEEE
15 years 6 months ago
Connecting spectral and spring methods for manifold learning
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
Shannon M. Hughes, Peter J. Ramadge