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» Building Relational World Models for Reinforcement Learning
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AI
2004
Springer
14 years 1 months ago
Intrinsic Representation: Bootstrapping Symbols from Experience
If we are to understand human-level intelligence, we need to understand how meanings can be learned without explicit instruction. I take a step toward that understanding by showing...
Stephen David Larson
ECAI
2000
Springer
14 years 2 days ago
Learning Classification taxonomies from a classification knowledge based system
Knowledge-based systems (KBS) are not necessarily based on well-defined ontologies. In particular it is possible to build KBS for classification problems, where there is little con...
Hendra Suryanto, Paul Compton
EMNLP
2007
13 years 9 months ago
What is the Jeopardy Model? A Quasi-Synchronous Grammar for QA
This paper presents a syntax-driven approach to question answering, specifically the answer-sentence selection problem for short-answer questions. Rather than using syntactic fea...
Mengqiu Wang, Noah A. Smith, Teruko Mitamura
ACL
2010
13 years 5 months ago
Open-Domain Semantic Role Labeling by Modeling Word Spans
Most supervised language processing systems show a significant drop-off in performance when they are tested on text that comes from a domain significantly different from the domai...
Fei Huang, Alexander Yates
SDM
2004
SIAM
144views Data Mining» more  SDM 2004»
13 years 9 months ago
RBA: An Integrated Framework for Regression based on Association Rules
This paper explores a novel framework for building regression models using association rules. The model consists of an ordered set of IF-THEN rules, where the rule consequent is t...
Aysel Ozgur, Pang-Ning Tan, Vipin Kumar