We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
In this paper, we propose a novel framework for extractive summarization. Our framework allows the summarizer to adapt and improve itself. Experimental results show that our summa...
Learning a good ranking function plays a key role for many applications including the task of (multimedia) information retrieval. While there are a few rank learning methods availa...
We study the properties of the agnostic learning framework of Haussler [Hau92] and Kearns, Schapire and Sellie [KSS94]. In particular, we address the question: is there any situat...
Given an image, we propose a hierarchical generative
model that classifies the overall scene, recognizes and segments
each object component, as well as annotates the image
with ...