Automatically acquiring control-knowledge for planning, as it is the case for Machine Learning in general, strongly depends on the training examples. In the case of planning, examp...
We present a simple, agnostic active learning algorithm that works for any hypothesis class of bounded VC dimension, and any data distribution. Our algorithm extends a scheme of C...
This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...
Concept learning in content-based image retrieval (CBIR) systems is a challenging task. This paper presents an active concept learning approach based on mixture model to deal with...
In this paper, we will propose a novel semi-automatic annotation scheme for video semantic classification. It is well known that the large gap between high-level semantics and low...