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» An algorithm for minimizing the Mumford-Shah functional
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IR
2010
13 years 7 months ago
Gradient descent optimization of smoothed information retrieval metrics
Abstract Most ranking algorithms are based on the optimization of some loss functions, such as the pairwise loss. However, these loss functions are often different from the criter...
Olivier Chapelle, Mingrui Wu
ICRA
2007
IEEE
171views Robotics» more  ICRA 2007»
14 years 3 months ago
Visual Servoing by Optimization of a 2D/3D Hybrid Objective Function
— In this paper, we present a new hybrid visual servoing algorithm for robot arm positioning task. Hybrid methods in visual servoing partially combine the 2D and 3D visual inform...
A. H. Abdul Hafez, C. V. Jawahar
ICML
2003
IEEE
14 years 9 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
INFOCOM
2000
IEEE
14 years 1 months ago
Broadcast Disks with Polynomial Cost Functions
— In broadcast disk systems, information is broadcasted in a shared medium. When a client needs an item from the disk, it waits until that item is broadcasted. The fundamental al...
Amotz Bar-Noy, Boaz Patt-Shamir, Igor Ziper
CORR
2006
Springer
113views Education» more  CORR 2006»
13 years 8 months ago
A Unified View of TD Algorithms; Introducing Full-Gradient TD and Equi-Gradient Descent TD
This paper addresses the issue of policy evaluation in Markov Decision Processes, using linear function approximation. It provides a unified view of algorithms such as TD(), LSTD()...
Manuel Loth, Philippe Preux