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» Measuring and Predicting Object Importance
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WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
12 years 4 months ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle
GLOBECOM
2007
IEEE
13 years 10 months ago
Exploiting Single SISO Impulse Responses to Predict the Capacity of Correlated MIMO Channels
—A novel strategy of precalculating potential MIMO spectral efficiencies of correlated channels based on both, measured as well as appropriately modeled SISO channel impulse res...
Andreas Knopp, Christian A. Hofmann, Mohamed Choua...
EMO
2006
Springer
158views Optimization» more  EMO 2006»
14 years 5 days ago
The Hypervolume Indicator Revisited: On the Design of Pareto-compliant Indicators Via Weighted Integration
The design of quality measures for approximations of the Pareto-optimal set is of high importance not only for the performance assessment, but also for the construction of multiobj...
Eckart Zitzler, Dimo Brockhoff, Lothar Thiele
LREC
2008
145views Education» more  LREC 2008»
13 years 10 months ago
Borrowing Language Resources for Development of Automatic Speech Recognition for Low- and Middle-Density Languages
In this paper we describe an approach that both creates crosslingual acoustic monophone model sets for speech recognition tasks and objectively predicts their performance without ...
Lynette Melnar, Chen Liu
ECAI
2006
Springer
13 years 10 months ago
Calibrating Probability Density Forecasts with Multi-Objective Search
Abstract. In this paper, we show that the optimization of density forecasting models for regression in machine learning can be formulated as a multi-objective problem. We describe ...
Michael Carney, Padraig Cunningham