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» Unsupervised Learning of Relations
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133
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NIPS
1994
15 years 6 months ago
From Data Distributions to Regularization in Invariant Learning
Ideally pattern recognition machines provide constant output when the inputs are transformed under a group G of desired invariances. These invariances can be achieved by enhancing...
Todd K. Leen
137
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CCR
2010
156views more  CCR 2010»
15 years 5 months ago
Evolvable network architectures: what can we learn from biology?
There is significant research interest recently to understand the evolution of the current Internet, as well as to design clean-slate Future Internet architectures. Clearly, even ...
Constantine Dovrolis, J. Todd Streelman
149
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TEC
2002
133views more  TEC 2002»
15 years 4 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben
TSE
2010
140views more  TSE 2010»
15 years 3 months ago
Learning a Metric for Code Readability
—In this paper, we explore the concept of code readability and investigate its relation to software quality. With data collected from 120 human annotators, we derive associations...
Raymond P. L. Buse, Westley Weimer
163
Voted
BMVC
2010
15 years 3 months ago
Manifold Learning for ToF-based Human Body Tracking and Activity Recognition
In this paper, we propose a method for simultaneous human full-body pose tracking and activity recognition from time-of-flight (ToF) camera images. Simple and sparse depth cues ar...
Loren Arthur Schwarz, Diana Mateus, Victor Castane...