We consider the problem of computing information theoretic functions such as entropy on a data stream, using sublinear space. Our first result deals with a measure we call the &quo...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Program slicing identifies parts of a program that potentially affect a chosen computation. It has many applications in software engineering, including maintenance, evolution and ...
It is commonly accepted that in concentrated solutions or melts high-molecular weight polymers display randomwalk conformational properties without long-range correlations between...
Joachim Paul Jakob Wittmer, Philippe Beckrich, F. ...
The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact s...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun