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» Extracting Propositions from Trained Neural Networks
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IJCAI
2007
14 years 11 months ago
Integration of Hybrid Bio-Ontologies using Bayesian Networks for Knowledge Discovery
This paper describes how high level biological knowledge obtained from ontologies such as the Gene Ontology (GO) can be integrated with low level information extracted from a Baye...
Kenneth McGarry, Sheila Garfield, Nick Morris, Ste...
CVPR
2010
IEEE
15 years 6 months ago
Supervised Translation-Invariant Sparse Coding
In this paper, we propose a novel supervised hierarchical sparse coding model based on local image descriptors for classification tasks. The supervised dictionary training is perf...
Jianchao Yang, Kai Yu, Thomas Huang
IEAAIE
2005
Springer
15 years 3 months ago
Movement Prediction from Real-World Images Using a Liquid State Machine
Prediction is an important task in robot motor control where it is used to gain feedback for a controller. With such a self-generated feedback, which is available before sensor rea...
Harald Burgsteiner, Mark Kröll, Alexander Leo...
APIN
2002
90views more  APIN 2002»
14 years 9 months ago
Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning
Abstract: Locally weighted learning (LWL) is a class of techniques from nonparametric statistics that provides useful representations and training algorithms for learning about com...
Stefan Schaal, Christopher G. Atkeson, Sethu Vijay...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
15 years 10 months ago
Complete This Puzzle: A Connectionist Approach to Accurate Web Recommendations Based on a Committee of Predictors
Abstract. We present a Context Ultra-Sensitive Approach based on two-step Recommender systems (CUSA-2step-Rec). Our approach relies on a committee of profile-specific neural networ...
Olfa Nasraoui, Mrudula Pavuluri