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COLT
2010
Springer
13 years 5 months ago
Convex Games in Banach Spaces
We study the regret of an online learner playing a multi-round game in a Banach space B against an adversary that plays a convex function at each round. We characterize the minima...
Karthik Sridharan, Ambuj Tewari
NIPS
1998
13 years 8 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
VLSID
1998
IEEE
116views VLSI» more  VLSID 1998»
13 years 11 months ago
Synthesis of Testable RTL Designs
With several commercial tools becoming available, the high-level synthesis of applicationspeci c integrated circuits is nding wide spread acceptance in VLSI industry today. Existi...
C. P. Ravikumar, Sumit Gupta, Akshay Jajoo
ICONIP
2009
13 years 5 months ago
Tracking in Reinforcement Learning
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
ICIP
2002
IEEE
14 years 9 months ago
Learning similarity space
In this study, we suggest a method to adapt an image retrieval system into a configurable one. Basically, original feature space of a content-based retrieval system is nonlinearly...
Abdurrahman Çarkacioglu, Fatos T. Yarman-Vu...