Based on scaling laws describing the statistical structure
of turbulent motion across scales, we propose a multiscale
and non-parametric regularizer for optic-flow estimation.
R...
Patrick H´eas, Etienne M´emin, Dominique Heitz, ...
— A novel approach is presented which aims at building autonomously visual models of unknown objects, using a humanoid robot. Although good methods have been proposed for the spe...
Topic-based text summaries promise to help average users quickly understand a text collection and derive insights. Recent research has shown that the Latent Dirichlet Allocation (...
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
This paper studies adaptive bilateral negotiation between software agents in e-commerce environments. Specifically, we assume that the agents are self-interested, the environment...