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Related papers: Output Statistics of Random Binning: Tsallis Diver…

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In this paper we develop a finite blocklength version of the Output Statistics of Random Binning (OSRB) framework. The framework is shown to be optimal in the point-to-point case. New second order regions for broadcast channel and wiretap…

Information Theory · Computer Science 2013-03-05 Mohammad Hossein Yassaee , Mohammad Reza Aref , Amin Gohari

In this paper the Output Statistics of Random Binning (OSRB) framework is used to prove a new inner bound for the problem of secure channel simulation. Our results subsume some recent results on the secure function computation. We also…

Information Theory · Computer Science 2012-07-17 Amin Gohari , Mohammad Hossein Yassaee , Mohammad Reza Aref

Kernel method has been developed as one of the standard approaches for nonlinear learning, which however, does not scale to large data set due to its quadratic complexity in the number of samples. A number of kernel approximation methods…

Machine Learning · Computer Science 2018-09-20 Lingfei Wu , Ian E. H. Yen , Jie Chen , Rui Yan

A new method is proposed for analyzing complexity and studying the information in random geometric networks using Tsallis entropy tool. Tsallis entropy of the ensemble of random geometric networks is calculated based on the components of…

Statistical Mechanics · Physics 2025-02-20 O. K. Kazemi , S. M. Taheri

Transient stability boundary (TSB) is an important tool in power system online security monitoring, but practically it suffers from high computational burden using state-of-the-art methods, such as time-domain simulation (TDS), with…

Systems and Control · Electrical Eng. & Systems 2020-04-06 Rong Yan , Guangchao Geng , Quanyuan Jiang

This paper introduces a new and ubiquitous framework for establishing achievability results in \emph{network information theory} (NIT) problems. The framework uses random binning arguments and is based on a duality between channel and…

Information Theory · Computer Science 2014-08-25 Mohammad Hossein Yassaee , Mohammad Reza Aref , Amin Gohari

The Tsallis and R\'enyi entropies are important quantities in the information theory, statistics and related fields because the Tsallis entropy is an one parameter generalization of the Shannon entropy and the R\'enyi entropy includes…

Quantum Physics · Physics 2014-12-24 Yusuke Ide , Norio Konno , Junji Shikata

We derive an algorithm that achieves the optimal (within constants) pseudo-regret in both adversarial and stochastic multi-armed bandits without prior knowledge of the regime and time horizon. The algorithm is based on online mirror descent…

Machine Learning · Computer Science 2022-03-03 Julian Zimmert , Yevgeny Seldin

We develop a variational thermodynamic framework for statistical systems governed by a self-referential nonlinear operator Omega characterized by structural exponents alpha > 0, beta >= 0, a symmetric kernel K, and a self-coupling constant…

Statistical Mechanics · Physics 2026-05-11 Lucio Marassi

The Tsallis entropy barrier or the roundness barrier based dynamic stochastic resonance mechanisms are put forward and simulated. The systems with various Tsallis q values exhibit the effects of emergence as a result of the noise-induced…

Statistical Mechanics · Physics 2008-08-19 Xiangjun Feng

An analytical expression of probability density function (PDF) of velocity fluctuation is derived with the help of the statistics based on generalized entropy (the Tsallis entropy or the R\'{e}nyi entropy). It is revealed that the derived…

Statistical Mechanics · Physics 2007-05-23 N. Arimitsu , T. Arimitsu

Tsallis' non-extensive entropy is extended to incorporate the dependence on affinities between the microstates of a system. At the core of our construction of the extended entropy ($\mathcal{H}$) is the concept of the effective number of…

Quantitative Methods · Quantitative Biology 2022-02-08 Keisuke Okamura

This work elaborates on the important problem of (1) designing optimal randomized routing policies for reaching a target node t from a source note s on a weighted directed graph G and (2) defining distance measures between nodes…

Machine Learning · Computer Science 2021-08-24 Pierre Leleux , Sylvain Courtain , Guillaume Guex , Marco Saerens

Pinsker's and Fannes' type bounds on the Tsallis relative entropy are derived. The monotonicity property of the quantum $f$-divergence is used for its estimating from below. For order $\alpha\in(0,1)$, a family of lower bounds of Pinsker…

Mathematical Physics · Physics 2013-08-26 Alexey E. Rastegin

Interest in Restricted Boltzmann Machine (RBM) is growing as a generative stochastic artificial neural network to implement a novel energy-efficient machine-learning (ML) technique. For a hardware implementation of the RBM, an essential…

Stochastic rising rested bandit (SRRB) is a setting where the arms' expected rewards increase as they are pulled. It models scenarios in which the performances of the different options grow as an effect of an underlying learning process…

Machine Learning · Statistics 2025-05-21 Marco Fiandri , Alberto Maria Metelli , Francesco Trovò

E.T. Jaynes, originator of the maximum entropy interpretation of statistical mechanics, emphasized that there is an inevitable trade-off between the conflicting requirements of robustness and accuracy for any inferencing algorithm. This is…

Information Theory · Computer Science 2014-04-24 Kenric P. Nelson , Brian J. Scannell , Herbert Landau

The design and performance analysis of bandit algorithms in the presence of stage-wise safety or reliability constraints has recently garnered significant interest. In this work, we consider the linear stochastic bandit problem under…

Machine Learning · Computer Science 2020-03-03 Ahmadreza Moradipari , Sanae Amani , Mahnoosh Alizadeh , Christos Thrampoulidis

Randomized benchmarking (RB) protocols are standard tools for characterizing quantum devices. Prior analyses of RB protocols have not provided a complete method for analyzing realistic data, resulting in a variety of ad-hoc methods. The…

Quantum Physics · Physics 2018-02-02 Ian Hincks , Joel J. Wallman , Chris Ferrie , Chris Granade , David G. Cory

We address the problem of detecting deviations of binary sequence from randomness,which is very important for random number (RNG) and pseudorandom number generators (PRNG). Namely, we consider a null hypothesis $H_0$ that a given bit…

Information Theory · Computer Science 2007-07-13 B. Ya. Ryabko , V. A. Monarev
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