A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
We prove logarithmic regret bounds that depend on the loss L∗ T of the competitor rather than on the number T of time steps. In the general online convex optimization setting, o...
Fusing partial estimates is a critical and common problem
in many computer vision tasks such as part-based detection
and tracking. It generally becomes complicated and
intractab...
In this paper, we propose an original approach for content-based video indexing and retrieval. It relies on the tracking of entities of interest and the analysis of their apparent...