We consider the problem of revenue-optimal dynamic mechanism design in settings where agents' types evolve over time as a function of their (both public and private) experien...
This paper introduces an innovative approach for automated negotiating using the gender of human opponents. Our approach segments the information acquired from previous opponents,...
Multi-task learning aims at combining information across tasks to boost prediction performance, especially when the number of training samples is small and the number of predictor...
The objective of query optimizers is to select a good execution plan for a given query. In a distributed system, it is crucial for a query optimizer to have effective remote cost e...
Satisfiability algorithms have become one of the most practical and successful approaches for solving a variety of real-world problems, including hardware verification, experime...