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» Building Relational World Models for Reinforcement Learning
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AI
2004
Springer
15 years 3 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
15 years 2 months 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
79
Voted
EMNLP
2007
14 years 11 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
14 years 7 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
97
Voted
SDM
2004
SIAM
144views Data Mining» more  SDM 2004»
14 years 11 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