We obtain a characterization of feasible, Bayesian, multi-item multi-bidder mechanisms with independent, additive bidders as distributions over hierarchical mechanisms. Combined w...
Yang Cai, Constantinos Daskalakis, S. Matthew Wein...
In the Stochastic Orienteering problem, we are given a metric, where each node also has a job located there with some deterministic reward and a random size. (Think of the jobs as...
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
We present PICPA, a new algorithm for tackling constrained continuous multi-objective problems. The algorithm combines constraint propagation techniques and evolutionary concepts. ...
An ensemble is a group of learners that work together as a committee to solve a problem. However, the existing ensemble training algorithms sometimes generate unnecessary large en...