While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...
We introduce a novel model of routing security that incorporates the ordinarily overlooked variations in trust that users have for different parts of the network. We focus on ano...
Aaron Johnson, Paul F. Syverson, Roger Dingledine,...
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on CHiLasso, a convex collaborative hierarchical s...
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
The paper considers a stylized model of a dynamic assortment optimization problem, where given a limited capacity constraint, we must decide the assortment of products to offer to...
Paat Rusmevichientong, Zuo-Jun Max Shen, David B. ...