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AAAI
2004
13 years 11 months ago
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...
Zhihua Zhang, Kap Luk Chan, James T. Kwok, Dit-Yan...
AAAI
2004
13 years 11 months ago
High-Level Goal Recognition in a Wireless LAN
Plan recognition has traditionally been developed for logically encoded application domains with a focus on logical reasoning. In this paper, we present an integrated plan-recogni...
Jie Yin, Xiaoyong Chai, Qiang Yang
AAAI
2006
13 years 11 months ago
Bayesian Calibration for Monte Carlo Localization
Localization is a fundamental challenge for autonomous robotics. Although accurate and efficient techniques now exist for solving this problem, they require explicit probabilistic...
Armita Kaboli, Michael H. Bowling, Petr Musí...
AAAI
2004
13 years 11 months ago
Distributed Representation of Syntactic Structure by Tensor Product Representation and Non-Linear Compression
Representing lexicons and sentences with the subsymbolic approach (using techniques such as Self Organizing Map (SOM) or Artificial Neural Network (ANN)) is a relatively new but i...
Heidi H. T. Yeung, Peter W. M. Tsang
AAAI
2006
13 years 11 months ago
An End-to-End Supervised Target-Word Sense Disambiguation System
We present an extensible supervised Target-Word Sense Disambiguation system that leverages upon GATE (General Architecture for Text Engineering), NSP (Ngram Statistics Package) an...
Mahesh Joshi, Serguei V. S. Pakhomov, Ted Pedersen...
AAAI
2006
13 years 11 months ago
Kernel Methods for Word Sense Disambiguation and Acronym Expansion
The scarcity of manually labeled data for supervised machine learning methods presents a significant limitation on their ability to acquire knowledge. The use of kernels in Suppor...
Mahesh Joshi, Ted Pedersen, Richard Maclin, Sergue...
AAAI
2004
13 years 11 months ago
Solving Generalized Semi-Markov Decision Processes Using Continuous Phase-Type Distributions
We introduce the generalized semi-Markov decision process (GSMDP) as an extension of continuous-time MDPs and semi-Markov decision processes (SMDPs) for modeling stochastic decisi...
Håkan L. S. Younes, Reid G. Simmons
AAAI
2006
13 years 11 months ago
A Dynamic Mixture Model to Detect Student Motivation and Proficiency
Unmotivated students do not reap the full rewards of using a computer-based intelligent tutoring system. Detection of improper behavior is thus an important component of an online...
Jeffrey Johns, Beverly Park Woolf
AAAI
2004
13 years 11 months ago
Automatic Generation of Artistic Chinese Calligraphy
We introduce a novel intelligent system which can generate new Chinese calligraphic artwork that meets certain aesthetic requirements automatically. In the machine learning phase,...
Songhua Xu, Francis C. M. Lau, Kwok-Wai Cheung, Yu...