Reinforcement learning addresses the problem of learning to select actions in order to maximize one's performance inunknownenvironments. Toscale reinforcement learning to com...
This paper studies the problem of learning from ambiguous supervision, focusing on the task of learning semantic correspondences. A learning problem is said to be ambiguously supe...
We present and evaluate various content-based recommendation models that make use of user and item profiles defined in terms of weighted lists of social tags. The studied approach...
We study the convergence behavior of the Active Mask (AM) framework, originally designed for segmenting punctate image patterns. AM combines the flexibility of traditional active...
Doru-Cristian Balcan, Gowri Srinivasa, Matthew C. ...
Interorganizational Systems (IOS) adoption requires cooperation and collaboration between trading partners and, therefore, is reliant on the nature of their relationships. There h...