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ATAL
2010
Springer
15 years 5 months ago
Risk-sensitive planning in partially observable environments
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
Janusz Marecki, Pradeep Varakantham
CORR
2010
Springer
119views Education» more  CORR 2010»
15 years 4 months ago
Dynamic Policy Programming
In this paper, we consider the problem of planning and learning in the infinite-horizon discounted-reward Markov decision problems. We propose a novel iterative direct policysearc...
Mohammad Gheshlaghi Azar, Hilbert J. Kappen
IJON
2002
85views more  IJON 2002»
15 years 3 months ago
Learning statistically efficient features for speaker recognition
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...
Gil-Jin Jang, Te-Won Lee, Yung-Hwan Oh
COLT
2010
Springer
15 years 2 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
CVPR
2011
IEEE
14 years 7 months ago
Entropy Rate Superpixel Segmentation
We propose a new objective function for superpixel segmentation. This objective function consists of two components: entropy rate of a random walk on a graph and a balancing term....
Ming-Yu Liu, Oncel Tuzel, Srikumar Ramalingam, Ram...