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CVPR
2012
IEEE
13 years 8 months ago
An online learned CRF model for multi-target tracking
We introduce an online learning approach for multitarget tracking. Detection responses are gradually associated into tracklets in multiple levels to produce final tracks. Unlike ...
Bo Yang, Ram Nevatia
ICML
2009
IEEE
16 years 7 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
STOC
2009
ACM
139views Algorithms» more  STOC 2009»
16 years 7 months ago
Online and stochastic survivable network design
Consider the edge-connectivity survivable network design problem: given a graph G = (V, E) with edge-costs, and edgeconnectivity requirements rij Z0 for every pair of vertices i,...
Anupam Gupta, Ravishankar Krishnaswamy, R. Ravi
AAAI
2007
15 years 8 months ago
Restart Schedules for Ensembles of Problem Instances
The mean running time of a Las Vegas algorithm can often be dramatically reduced by periodically restarting it with a fresh random seed. The optimal restart schedule depends on th...
Matthew J. Streeter, Daniel Golovin, Stephen F. Sm...
COLT
2008
Springer
15 years 8 months ago
Extracting Certainty from Uncertainty: Regret Bounded by Variation in Costs
Prediction from expert advice is a fundamental problem in machine learning. A major pillar of the field is the existence of learning algorithms whose average loss approaches that ...
Elad Hazan, Satyen Kale