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ECCC
2010
80views more  ECCC 2010»
13 years 5 months ago
Regret Minimization for Online Buffering Problems Using the Weighted Majority Algorithm
Suppose a decision maker has to purchase a commodity over time with varying prices and demands. In particular, the price per unit might depend on the amount purchased and this pri...
Melanie Winkler, Berthold Vöcking, Sascha Geu...
MASCOTS
2003
13 years 6 months ago
Minimizing Packet Loss by Optimizing OSPF Weights Using Online Simulation
In this paper, we present a scheme for minimizing packet loss in OSPF networks by optimizing link weights using Online Simulation. We have chosen packet loss rate in the network a...
Hema Tahilramani Kaur, Tao Ye, Shivkumar Kalyanara...
COLT
2010
Springer
13 years 3 months ago
Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback
Bandit convex optimization is a special case of online convex optimization with partial information. In this setting, a player attempts to minimize a sequence of adversarially gen...
Alekh Agarwal, Ofer Dekel, Lin Xiao
ICML
2009
IEEE
14 years 6 months ago
Efficient learning algorithms for changing environments
We study online learning in an oblivious changing environment. The standard measure of regret bounds the difference between the cost of the online learner and the best decision in...
Elad Hazan, C. Seshadhri
ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
13 years 10 months ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof