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» New Algorithms for Optimal Online Checkpointing
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TIP
1998
129views more  TIP 1998»
13 years 7 months ago
Minimax partial distortion competitive learning for optimal codebook design
— The design of the optimal codebook for a given codebook size and input source is a challenging puzzle that remains to be solved. The key problem in optimal codebook design is h...
Ce Zhu, Lai-Man Po
CIKM
2010
Springer
13 years 5 months ago
Online stratified sampling: evaluating classifiers at web-scale
Deploying a classifier to large-scale systems such as the web requires careful feature design and performance evaluation. Evaluation is particularly challenging because these larg...
Paul N. Bennett, Vitor R. Carvalho
JMLR
2010
195views more  JMLR 2010»
13 years 5 months ago
Online Learning for Matrix Factorization and Sparse Coding
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
SODA
2008
ACM
185views Algorithms» more  SODA 2008»
13 years 8 months ago
Better bounds for online load balancing on unrelated machines
We study the problem of scheduling permanent jobs on unrelated machines when the objective is to minimize the Lp norm of the machine loads. The problem is known as load balancing ...
Ioannis Caragiannis
FOCS
2006
IEEE
14 years 1 months ago
Improved Bounds for Online Routing and Packing Via a Primal-Dual Approach
In this work we study a wide range of online and offline routing and packing problems with various objectives. We provide a unified approach, based on a clean primal-dual method...
Niv Buchbinder, Joseph Naor