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GECCO
2008
Springer
163views Optimization» more  GECCO 2008»
15 years 5 months ago
Embedded evolutionary multi-objective optimization for worst case robustness
In Multi-Objective Problems (MOPs) involving uncertainty, each solution might be associated with a cluster of performances in the objective space depending on the possible scenari...
Gideon Avigad, Jürgen Branke
CORR
2010
Springer
114views Education» more  CORR 2010»
15 years 4 months ago
Settling the Polynomial Learnability of Mixtures of Gaussians
Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We give an algorithm for this problem that has running ...
Ankur Moitra, Gregory Valiant
JCB
2007
198views more  JCB 2007»
15 years 3 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
CVPR
2009
IEEE
16 years 11 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
CVPR
2006
IEEE
16 years 6 months ago
Shape Guided Object Segmentation
We construct a Bayesian model that integrates topdown with bottom-up criteria, capitalizing on their relative merits to obtain figure-ground segmentation that is shape-specific an...
Eran Borenstein, Jitendra Malik