In many situations, a set of hard constraints encodes the feasible configurations of some system or product over which multiple users have distinct preferences. However, making su...
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Studying the relationship between natural language and affective information as well as assessing the underpinned affective qualities of natural language are becoming crucial for ...
Shaikh Mostafa Al Masum, Helmut Prendinger, Mitsur...
Abstract. We present a method for constructing a teleological model of a drawing of a physical device through analogical transfer of the teleological model of the same device in an...