The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
In this paper, we consider the open problem of the complexity of the LLL algorithm in the case when the approximation parameter of the algorithm has its extreme value
In this paper, we formulate a class of colored range query problems to model the multi-dimensional range queries in the presence of categorical information. By applying appropriate...
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
The data migration problem is to compute an efficient plan for moving data stored on devices in a network from one configuration to another. It is modeled by a transfer graph, wher...