We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
We consider the total weighted completion time scheduling problem for parallel identical machines and precedence constraints, P jprecj PwiCi. This important and broad class of pro...
Ivan D. Baev, Waleed Meleis, Alexandre E. Eichenbe...
The bounded diameter minimum spanning tree problem is an NP-hard combinatorial optimization problem arising, for example, in network design when quality of service is of concern. ...
Abstract--This paper tackles a fundamental problem of network planning and dimensioning under EPON-WiMAX integration for next-generation wireless metropolitan-area broadband access...
Bin Lin, Pin-Han Ho, Xuemin Shen, Frank Chih-Wei S...