Traditional performance analysis of approximation algorithms considers overall performance, while economic fairness analysis focuses on the individual performance each user receiv...
In this paper, we address the matrix completion problem and propose a novel algorithm based on a smoothed rank function (SRF) approximation. Among available algorithms like FPCA a...
We consider the problem of approximating sliding window joins over data streams in a data stream processing system with limited resources. In our model, we deal with resource cons...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Control systems are usually modeled by differential equations describing how physical phenomena can be influenced by certain control parameters or inputs. Although these models ar...