We study online learnability of a wide class of problems, extending the results of [26] to general notions of performance measure well beyond external regret. Our framework simult...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
Artificial Intelligence algorithms can be divided into two groups according to the type of problems they solve. Knowledge-intensive domains contain explicit knowledge, whereas know...
Testing with random inputs can give surprisingly good results if the distribution of inputs is spread out evenly over the input domain; this is the intuition behind Adaptive Rando...
Ilinca Ciupa, Andreas Leitner, Manuel Oriol, Bertr...
Finite element solvers are a basic component of simulation applications; they are common in computer graphics, engineering, and medical simulations. Although adaptive solvers can ...
Controlling the quality of collaborative multimedia sessions, that deploy multiple media streams, is a challenging problem. In this paper, we present a framework for achieving qua...