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ICML
2005
IEEE
16 years 5 months ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
146
Voted
ICANN
2009
Springer
15 years 11 months ago
Selective Attention Improves Learning
Abstract. We demonstrate that selective attention can improve learning. Considerably fewer samples are needed to learn a source separation problem when the inputs are pre-segmented...
Antti Yli-Krekola, Jaakko Särelä, Harri ...
ICRA
2008
IEEE
156views Robotics» more  ICRA 2008»
15 years 11 months ago
Consensus learning for distributed coverage control
— A decentralized controller is presented that causes a network of robots to converge to a near optimal sensing configuration, while simultaneously learning the distribution of ...
Mac Schwager, Jean-Jacques E. Slotine, Daniela Rus
IWANN
2007
Springer
15 years 11 months ago
Non-parametric Residual Variance Estimation in Supervised Learning
The residual variance estimation problem is well-known in statistics and machine learning with many applications for example in the field of nonlinear modelling. In this paper, we...
Elia Liitiäinen, Amaury Lendasse, Francesco C...
117
Voted
WMTE
2006
IEEE
15 years 11 months ago
JAMIOLAS: Supporting Japanese Mimicry and Onomatopoeia Learning with Sensors
  This  paper  proposes  a  computer  supported  ubiquitous  learning  environment  for  language  learning.  Especially,  this  paper  describes  context­  awar...
Hiroaki Ogata, Chengjiu Yin, Yoneo Yano