The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...
Abstract. We describe a new method for unsupervised structure learning of a hierarchical compositional model (HCM) for deformable objects. The learning is unsupervised in the sense...
Long Zhu, Chenxi Lin, Haoda Huang, Yuanhao Chen, A...
We cast the problem of recognizing related categories as a unified learning and structured prediction problem with shared body plans. When provided with detailed annotations of o...
Ian Endres, Vivek Srikumar, Ming-Wei Chang, Derek ...
This paper is concerned with a new task of ranking, referred to as "supplementary data assisted ranking", or "supplementary ranking" for short. Different from c...
Recent research in object recognition has demonstrated the advantages of representing objects and scenes through localized patterns such as small image templates. In this paper we...