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COLT
1999
Springer
15 years 11 months ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon
CORR
2006
Springer
99views Education» more  CORR 2006»
15 years 6 months ago
Rational stochastic languages
In probabilistic grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. The estimate of P stands in some cl...
François Denis, Yann Esposito
PAMI
2008
145views more  PAMI 2008»
15 years 6 months ago
Latent-Space Variational Bayes
Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...
JaeMo Sung, Zoubin Ghahramani, Sung Yang Bang
GLOBECOM
2007
IEEE
16 years 1 months ago
Opportunistic Relaying in Cellular Network for Capacity and Fairness Improvement
— In this paper, we study how the cooperative relaying can improve both capacity and fairness in cellular network. The capacity and fairness have a trade-off relationship, so inc...
Seungho Song, Kyuho Son, Hyang-Won Lee, Song Chong
ACIVS
2007
Springer
16 years 1 months ago
Shape Extraction Via Heat Flow Analogy
Abstract. In this paper, we introduce a novel evolution-based segmentation algorithm by using the heat flow analogy, to gain practical advantage. The proposed algorithm consists of...
Cem Direkoglu, Mark S. Nixon