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AAAI
2008
14 years 2 months ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen
AAAI
2008
14 years 2 months ago
Automatic Semantic Relation Extraction with Multiple Boundary Generation
This paper addresses the task of automatic classification of semantic relations between nouns. We present an improved WordNet-based learning model which relies on the semantic inf...
Brandon Beamer, Alla Rozovskaya, Roxana Girju
AAAI
2008
14 years 2 months ago
Using AI for Olympic Equestrian Event Preparation
This paper describes our experience in using modern Web 2.0 architecture, lightweight Python frameworks, and rapid prototyping to create an AI rostering and workforce management s...
Andy Hon Wai Chun
AAAI
2008
14 years 2 months ago
Using Clustering Methods for Discovering Event Structures
Cosmin Adrian Bejan, Sanda M. Harabagiu
AAAI
2008
14 years 2 months ago
Active Learning for Pipeline Models
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
Dan Roth, Kevin Small
AAAI
2008
14 years 2 months ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...
AAAI
2008
14 years 2 months ago
Lexical and Grammatical Inference
Children are facile at both discovering word boundaries and using those words to build higher-level structures in tandem. Current research treats lexical acquisition and grammar i...
Tom Armstrong, Tim Oates
AAAI
2008
14 years 2 months ago
Adapting ADtrees for High Arity Features
ADtrees, a data structure useful for caching sufficient statistics, have been successfully adapted to grow lazily when memory is limited and to update sequentially with an increme...
Robert Van Dam, Irene Langkilde-Geary, Dan Ventura