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» Iterative Learning Control - Monotonicity and Optimization
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CVPR
2011
IEEE
14 years 6 months ago
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Sudheendra Vijayanarasimhan, Kristen Grauman
SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
15 years 4 months ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
ICML
2007
IEEE
15 years 10 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro
ICML
2003
IEEE
15 years 10 months ago
SimpleSVM
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...
PIMRC
2010
IEEE
14 years 7 months ago
Statistical Learning-based Automated Healing: Application to mobility in 3G LTE networks
Abstract--Troubleshooting of wireless networks is a challenging network management task. We have developed, in a previous work, a new troubleshooting methodology, which we named St...
Moazzam Islam Tiwana, Berna Sayraç, Zwi Alt...