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GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
15 years 6 months ago
A novel generative encoding for exploiting neural network sensor and output geometry
A significant problem for evolving artificial neural networks is that the physical arrangement of sensors and effectors is invisible to the evolutionary algorithm. For example,...
David B. D'Ambrosio, Kenneth O. Stanley
CEAS
2008
Springer
15 years 1 months ago
Exploiting Transport-Level Characteristics of Spam
We present a novel spam detection technique that relies on neither content nor reputation analysis. This work investigates the discriminatory power of email transport-layer charac...
Robert Beverly, Karen R. Sollins
CVPR
2011
IEEE
14 years 3 months ago
Exploiting Phonological Constraints for Handshape Inference in ASL Video
Handshape is a key linguistic component of signs, and thus, handshape recognition is essential to algorithms for sign language recognition and retrieval. In this work, linguistic ...
Ashwin Thangali, Stan Sclaroff, Carol Neidle, Joan...
IJON
2011
169views more  IJON 2011»
14 years 6 months ago
Exploiting local structure in Boltzmann machines
Restricted Boltzmann Machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image ...
Hannes Schulz, Andreas Müller 0004, Sven Behn...
ICML
2005
IEEE
16 years 17 days ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...