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...
Image segmentation plays an important role in many medical imaging systems, yet in complex circumstances it is still a challenging problem. Among many difficulties, problem caused ...
The discovery of complex patterns such as clusters, outliers, and associations from huge volumes of streaming data has been recognized as critical for many domains. However, patte...
This paper investigates assignment strategies (load balancing algorithms) for process farms which solve the problem of online placement of a constant number of independent tasks w...
Based on the framework of parameterized complexity theory, we derive tight lower bounds on the computational complexity for a number of well-known NP-hard problems. We start by pr...
Jianer Chen, Benny Chor, Mike Fellows, Xiuzhen Hua...