This paper studies —from the perspective of efficient computation— a type of competition that is widespread throughout the plant and animal kingdoms, higher education, politic...
Leslie Ann Goldberg, Paul W. Goldberg, Piotr Kryst...
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
In many information networks, data items – such as updates in social networks, news flowing through interconnected RSS feeds and blogs, measurements in sensor networks, route u...
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
This paper presents an approach to shadow removal that preserves texture consistency between the original shadow and lit area. Illumination reduction in the shadow area not only da...