We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
In this paper, we present a proof of concept application of a technique that is designed explicitly for face to face collaboration software architectures. The objective is to minim...
We present a statistical method that PAC learns the class of stochastic perceptrons with arbitrary monotonic activation function and weights wi {-1, 0, +1} when the probability d...
This paper describes the integration of the grid topic within a Computer Architecture engineering course. Students are engaged in a project of design and evaluation of computing s...
Guillermo Vega-Gorgojo, Yannis A. Dimitriadis, Edu...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...