Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sens...
JSTOR is a not-for-profit online library containing a full back-run of digitized versions of a large number of academic journals. In order to help defray costs for maintaining the...
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in...
Martin Godec, Christian Leistner, Amir Saffari, Ho...
We present a family of margin based online learning algorithms for various prediction tasks. In particular we derive and analyze algorithms for binary and multiclass categorizatio...