Browsing by Author "Lugosi, Gábor"

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  • Horvath, Marta; Lugosi, Gábor (1996-12-01)
    The classical binary classification problem is investigated when it is known in advance that the posterior probability function (or regression function) belongs to some class of functions. We introduce and analyze a method ...
  • Devroye, Luc; Györfi, László; Lugosi, Gábor (2000-08-01)
  • Boucheron, Stéphane; Lugosi, Gábor; Massart, Pascal (1999-04-01)
    We present a new general concentration-of-measure inequality and illustrate its power by applications in random combinatorics. The results find direct applications in some problems of learning theory.
  • Györfi, László; Lugosi, Gábor; Morvai, Gusztáv (1998-04-01)
    We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if the sequence ...
  • Linder, Tamás; Lugosi, Gábor (2000-02-01)
    We consider adaptive sequential lossy coding of bounded individual sequences when the performance is measured by the sequentially accumulated mean squared distortion. The encoder and the decoder are connected via a ...
  • Lugosi, Gábor; Nobel, Andrew B. (1998-06-01)
  • Devroye, Luc; Lugosi, Gábor (1999-04-01)
    Let a class $\F$ of densities be given. We draw an i.i.d.\ sample from a density $f$ which may or may not be in $\F$. After every $n$, one must make a guess whether $f \in \F$ or not. A class is almost surely testable if ...
  • Bartlett, Peter; Lugosi, Gábor (1998-02-01)
    We derive a new inequality for uniform deviations of averages from their means. The inequality is a common generalization of previous results of Vapnik and Chervonenkis (1974) and Pollard (1986). Using the new inequality ...
  • Broutin, Nicolas; Devroye, Luc; Lugosi, Gábor (The Institute of Mathematical Statistics and the Bernoulli Society, 2015)
    Consider a random geometric graph defined on n vertices uniformly distributedin the d-dimensional unit torus. Two vertices are connected if their distance is less than a "visibility radius" rn. We consider Bluetooth networks ...
  • Delicado, Pedro; Hernández, Adolfo; Lugosi, Gábor (Institute of Mathematical Statistics, 2014)
    Given n independent, identically distributed random vectors in Rd, drawn from a common density f, one wishes to find out whether the support of f is convex or not. In this paper we describe a decision rule which decides ...
  • Gudmundsson, Gudmundur Stefan (Universitat Pompeu Fabra, 2018-07-11)
    This thesis consists of two chapters on time series modelling. The first chapter introduces a class of vector autoregressive (VAR) models with a community structure for large panels of time series. In the model, the series ...
  • Germano, Fabrizio; Lugosi, Gábor (2005-10-01)
    We show that every finite N-player normal form game possesses a correlated equilibrium with a precise lower bound on the number of outcomes to which it assigns zero probability. In particular, the largest games with a ...
  • Lugosi, Gábor; Pereira, Alan S. (The Institute of Mathematical Statistics and the Bernoulli Society, 2019)
    A uniform attachment tree is a random tree that is generated dynamically. Starting from a fixed “seed” tree, vertices are added sequentially by attaching each vertex to an existing vertex chosen uniformly at random. Upon ...
  • Germano, Fabrizio; Lugosi, Gábor (2004-10-01)
    We construct an uncoupled randomized strategy of repeated play such that, if every player follows such a strategy, then the joint mixed strategy profiles converge, almost surely, to a Nash equilibrium of the one-shot game. ...
  • Devroye, Luc; Lugosi, Gábor; Udina, Frederic (1998-02-01)
  • Olkhovskaya, Julia (Universitat Pompeu Fabra, 2022-03-29)
    La toma secuencial de decisiones con incertidumbre cubre una amplia clase de problemas. Las aplicaciones reales requieren que los algoritmos sean computacionalmente eficientes y escalables. Nosotros estudiamos un rango ...
  • Kulkarni, Sanjeev R.; Lugosi, Gábor (1997-02-01)
  • Bartlett, Peter; Boucheron, Stéphane; Lugosi, Gábor (2000-10-01)
    We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be ...
  • Devroye, Luc; Györfi, László; Lugosi, Gábor; Walk, Harro (The Institute of Mathematical Statistics and the Bernoulli Society, 2018)
    We study the problem of estimating the smallest achievable mean-squared error in regression function estimation. The problem is equivalent to estimating the second moment of the regression function of Y on X∈Rd. We introduce ...
  • Cesana Arlotti, Nicolò, 1981-; Lugosi, Gábor (1998-07-01)
    Sequential randomized prediction of an arbitrary binary sequence is investigated. No assumption is made on the mechanism of generating the bit sequence. The goal of the predictor is to minimize its relative loss, i.e., ...

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