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101
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IUI
2000
ACM
15 years 7 months ago
Creating an empirical basis for adaptation decisions
CT How can an adaptive intelligent interface decide what particular action to perform in a given situation, as a function of perceived properties of the user and the situation? Ide...
Anthony Jameson, Barbara Großmann-Hutter, Le...
131
Voted
ICADL
2007
Springer
147views Education» more  ICADL 2007»
15 years 9 months ago
Feature Reinforcement Approach to Poly-lingual Text Categorization
With the rapid emergence and proliferation of Internet and the trend of globalization, a tremendous amount of textual documents written in different languages are electronically ac...
Chih-Ping Wei, Huihua Shi, Christopher C. Yang
141
Voted
AIPS
2007
15 years 5 months ago
Learning to Plan Using Harmonic Analysis of Diffusion Models
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
118
Voted
ICML
1994
IEEE
15 years 6 months ago
A Modular Q-Learning Architecture for Manipulator Task Decomposition
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Chen K. Tham, Richard W. Prager
111
Voted
ICASSP
2008
IEEE
15 years 9 months ago
Contextually adaptive signal representation using conditional principal component analysis
The conventional method of generating a basis that is optimally adapted (in MSE) for representation of an ensemble of signals is Principal Component Analysis (PCA). A more ambitio...
Rosa M. Figueras i Ventura, Umesh Rajashekar, Zhou...