In previous papers [SC05, SBC+07], some of us predicted the end of "one size fits all" as a commercial relational DBMS paradigm. These papers presented reasons and exper...
Michael Stonebraker, Samuel Madden, Daniel J. Abad...
Abstract— Feature Selection (FS) is a technique for dimensionality reduction. Its aims are to select a subset of the original features of a dataset which are rich in the most use...
Eligibility traces have been shown to speed reinforcement learning, to make it more robust to hidden states, and to provide a link between Monte Carlo and temporal-difference meth...
Doina Precup, Richard S. Sutton, Satinder P. Singh
— In this paper, we propose a new supervised learning method whereby information is controlled by the associated cost in an intermediate layer, and in an output layer, errors bet...
Abstract—Active measurements on network paths provide endto-end network health status in terms of metrics such as bandwidth, delay, jitter and loss. Hence, they are increasingly ...