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SIGIR
2011
ACM
14 years 10 days ago
Learning to rank from a noisy crowd
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...
Abhimanu Kumar, Matthew Lease
ECTEL
2006
Springer
15 years 1 months ago
Peer-to-peer Face-to-face Collaboration
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...
Delfina Malandrino, Ilaria Manno
NIPS
1994
14 years 10 months ago
Learning Stochastic Perceptrons Under k-Blocking Distributions
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...
Mario Marchand, Saeed Hadjifaradji
CCGRID
2004
IEEE
15 years 1 months ago
Learning Grid technologies in a project-based computer architecture course
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...
91
Voted
KDD
2005
ACM
149views Data Mining» more  KDD 2005»
15 years 3 months ago
A distributed learning framework for heterogeneous data sources
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...
Srujana Merugu, Joydeep Ghosh