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ECCV
2010
Springer
15 years 4 months ago
Learning What and How of Contextual Models for Scene Labeling
We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...
JMLR
2011
137views more  JMLR 2011»
14 years 6 months ago
Online Learning in Case of Unbounded Losses Using Follow the Perturbed Leader Algorithm
In this paper the sequential prediction problem with expert advice is considered for the case where losses of experts suffered at each step cannot be bounded in advance. We presen...
Vladimir V. V'yugin
RECOMB
2007
Springer
15 years 11 months ago
Minimizing and Learning Energy Functions for Side-Chain Prediction
Abstract. Side-chain prediction is an important subproblem of the general protein folding problem. Despite much progress in side-chain prediction, performance is far from satisfact...
Chen Yanover, Ora Schueler-Furman, Yair Weiss
JMLR
2006
389views more  JMLR 2006»
14 years 11 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
CIKM
2010
Springer
14 years 10 months ago
Who should I cite: learning literature search models from citation behavior
Scientists depend on literature search to find prior work that is relevant to their research ideas. We introduce a retrieval model for literature search that incorporates a wide ...
Steven Bethard, Dan Jurafsky