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STOC
1993
ACM
141views Algorithms» more  STOC 1993»
15 years 10 months ago
Bounds for the computational power and learning complexity of analog neural nets
Abstract. It is shown that high-order feedforward neural nets of constant depth with piecewisepolynomial activation functions and arbitrary real weights can be simulated for Boolea...
Wolfgang Maass
AAAI
1994
15 years 8 months ago
High Dimension Action Spaces in Robot Skill Learning
Table lookup with interpolation is used for many learning and adaptation tasks. Redundant mappings capture the important concept of \motor skill," which is important in real,...
Jeff G. Schneider
CVPR
2010
IEEE
15 years 6 months ago
High performance object detection by collaborative learning of Joint Ranking of Granules features
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...
Chang Huang, Ramakant Nevatia
JCNS
2000
78views more  JCNS 2000»
15 years 6 months ago
Computational Consequences of Temporally Asymmetric Learning Rules: II. Sensory Image Cancellation
Abstract. The electrosensory lateral line lobe (ELL) of mormyridelectric sh is a cerebellum-likestructure that receives primarya erent input from electroreceptors in the skin. Purk...
Patrick D. Roberts, Curtis C. Bell
NCA
2002
IEEE
15 years 6 months ago
Comparison of Algorithmic and Machine Learning Approaches for the Automatic Fitting of Gaussian Peaks
Fitting gaussian peaks to experimental data is important in many disciplines, including nuclear spectroscopy. Nonlinear least squares fitting methods have been in use for a long t...
Radwan E. Abdel-Aal