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ICIAP
2005
ACM
16 years 3 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
120
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BIBM
2007
IEEE
15 years 9 months ago
A Semi-supervised Learning Approach to Disease Gene Prediction
Discovering human disease-causing genes (disease genes in short) is one of the most challenging problems in bioinformatics and biomedicine, as most diseases are related in some wa...
Thanh Phuong Nguyen, Tu Bao Ho
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
15 years 1 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
ICANN
2011
Springer
14 years 6 months ago
Semi-supervised Learning for WLAN Positioning
Currently the most accurate WLAN positioning systems are based on the fingerprinting approach, where a “radio map” is constructed by modeling how the signal strength measureme...
Teemu Pulkkinen, Teemu Roos, Petri Myllymäki
ICML
2000
IEEE
16 years 4 months ago
On-line Learning for Humanoid Robot Systems
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system s...
Gaurav Tevatia, Jörg Conradt, Sethu Vijayakum...