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ICCBR
2010
Springer
13 years 11 months ago
Imitating Inscrutable Enemies: Learning from Stochastic Policy Observation, Retrieval and Reuse
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
CCS
2009
ACM
14 years 2 months ago
Learning your identity and disease from research papers: information leaks in genome wide association study
Genome-wide association studies (GWAS) aim at discovering the association between genetic variations, particularly single-nucleotide polymorphism (SNP), and common diseases, which...
Rui Wang, Yong Fuga Li, XiaoFeng Wang, Haixu Tang,...
IROS
2006
IEEE
132views Robotics» more  IROS 2006»
14 years 1 months ago
Supervised Learning of Topological Maps using Semantic Information Extracted from Range Data
Abstract— This paper presents an approach to create topological maps from geometric maps obtained with a mobile robot in an indoor-environment using range data. Our approach util...
Óscar Martínez Mozos, Wolfram Burgar...
COGSCI
2002
99views more  COGSCI 2002»
13 years 7 months ago
Learning words from sights and sounds: a computational model
This paper presents an implemented computational model of word acquisition which learns directly from raw multimodal sensory input. Set in an information theoretic framework, the ...
Deb Roy, Alex Pentland
DAC
2003
ACM
14 years 8 months ago
Learning from BDDs in SAT-based bounded model checking
Bounded Model Checking (BMC) based on Boolean Satisfiability (SAT) procedures has recently gained popularity as an alternative to BDD-based model checking techniques for finding b...
Aarti Gupta, Malay K. Ganai, Chao Wang, Zijiang Ya...