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ICML
2010
IEEE
15 years 5 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
AIED
2009
Springer
15 years 10 months ago
Knowledge Co-construction and Initiative in Peer Learning Interactions
The aim of the project we discuss in this paper is to develop a computational model of peer learning. We present an extensive analysis of peer learning dialogues, analysis on which...
Cynthia Kersey, Barbara Di Eugenio, Pamela W. Jord...
ISCIS
2003
Springer
15 years 9 months ago
A New Continuous Action-Set Learning Automaton for Function Optimization
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...
Hamid Beigy, Mohammad Reza Meybodi
BIRTHDAY
1997
Springer
15 years 8 months ago
The Job Assignment Problem: A Study in Parallel and Distributed Machine Learning
This article describes a parallel and distributed machine learning approach to a basic variant of the job assignment problem. The approach is in the line of the multiagent learning...
Gerhard Weiß
ESANN
2008
15 years 5 months ago
A Regularized Learning Method for Neural Networks Based on Sensitivity Analysis
The Sensitivity-Based Linear Learning Method (SBLLM) is a learning method for two-layer feedforward neural networks, based on sensitivity analysis, that calculates the weights by s...
Bertha Guijarro-Berdiñas, Oscar Fontenla-Ro...