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NIPS
2001
13 years 11 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
CORR
2004
Springer
103views Education» more  CORR 2004»
13 years 10 months ago
Online convex optimization in the bandit setting: gradient descent without a gradient
We study a general online convex optimization problem. We have a convex set S and an unknown sequence of cost functions c1, c2, . . . , and in each period, we choose a feasible po...
Abraham Flaxman, Adam Tauman Kalai, H. Brendan McM...
SIGECOM
2006
ACM
106views ECommerce» more  SIGECOM 2006»
14 years 4 months ago
Approximation algorithms and online mechanisms for item pricing
We present approximation and online algorithms for a number of problems of pricing items for sale so as to maximize seller’s revenue in an unlimited supply setting. Our first r...
Maria-Florina Balcan, Avrim Blum
CODES
2008
IEEE
14 years 4 months ago
Online adaptive utilization control for real-time embedded multiprocessor systems
To provide Quality of Service (QoS) guarantees in open and unpredictable environments, the utilization control problem is defined to keep the processor utilization at the schedula...
Jianguo Yao, Xue Liu, Mingxuan Yuan, Zonghua Gu
AAAI
2010
13 years 11 months ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos