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Bayesian bandit algorithms with approximate Bayesian inference have been widely used in real-world applications. However, there is a large discrepancy between the superior practical performance of these approaches and their theoretical…

Machine Learning · Computer Science 2023-11-13 Ziyi Huang , Henry Lam , Amirhossein Meisami , Haofeng Zhang

Alternative exact expressions are derived for the minimum error probability of a hypothesis test discriminating among $M$ quantum states. The first expression corresponds to the error probability of a binary hypothesis test with certain…

Quantum Physics · Physics 2016-11-15 Gonzalo Vazquez-Vilar

We derive information-theoretic lower bounds on the Bayes risk and generalization error of realizable machine learning models. In particular, we employ an analysis in which the rate-distortion function of the model parameters bounds the…

Machine Learning · Computer Science 2021-11-09 Matthew Nokleby , Ahmad Beirami

In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinforcement learning problems. While utility bounds are known to…

Machine Learning · Computer Science 2011-11-14 Christos Dimitrakakis

This paper addresses the integration of additional information sources into a Bayesian optimization framework while ensuring that safety constraints are satisfied. The interdependencies between these information sources are modeled using an…

Machine Learning · Computer Science 2025-05-06 Jannis O. Luebsen , Annika Eichler

Previous research on PAC-Bayes learning theory has focused extensively on establishing tight upper bounds for test errors. A recently proposed training procedure called PAC-Bayes training, updates the model toward minimizing these bounds.…

Machine Learning · Statistics 2024-10-22 Xitong Zhang , Avrajit Ghosh , Guangliang Liu , Rongrong Wang

We consider the problem of parameter estimation in a Bayesian setting and propose a general lower-bound that includes part of the family of $f$-Divergences. The results are then applied to specific settings of interest and compared to other…

Information Theory · Computer Science 2022-05-19 Adrien Vandenbroucque , Amedeo Roberto Esposito , Michael Gastpar

A new lower bound on the error probability of maximum likelihood decoding of a binary code on a binary symmetric channel was proved in Barg and McGregor (2004, cs.IT/0407011). It was observed in that paper that this bound leads to a new…

Information Theory · Computer Science 2007-07-13 Alexander Barg

A central problem in Binary Hypothesis Testing (BHT) is to determine the optimal tradeoff between the Type I error (referred to as false alarm) and Type II (referred to as miss) error. In this context, the exponential rate of convergence of…

Information Theory · Computer Science 2021-11-29 Sebastian Espinosa , Jorge F. Silva , Pablo Piantanida

We evaluate the asymptotics of equivocations, their exponents as well as their second-order coding rates under various R\'{e}nyi information measures. Specifically, we consider the effect of applying a hash function on a source and we…

Information Theory · Computer Science 2016-07-06 Masahito Hayashi , Vincent Y. F. Tan

In contrast to a maximum-likelihood decoder, it is often desirable to use an incomplete decoder that can detect its decoding errors with high probability. One common choice is the bounded distance decoder. Bounds are derived for the total…

Information Theory · Computer Science 2012-07-26 Kenneth Andrews , Sam Dolinar

We introduce a modified version of the excess risk, which can be used to obtain tighter, fast-rate PAC-Bayesian generalisation bounds. This modified excess risk leverages information about the relative hardness of data examples to reduce…

Machine Learning · Computer Science 2023-01-25 Felix Biggs , Benjamin Guedj

The application of current generation computing machines in safety-centric applications like implantable biomedical chips and automobile safety has immensely increased the need for reviewing the worst-case error behavior of computing…

Information Theory · Computer Science 2021-08-23 Karthikeyan Lingasubramanian , Syed M. Alam , Sanjukta Bhanja

The generalized Poor-Verdu error lower bound established in [1] for multihypothesis testing is studied in the classical channel coding context. It is proved that for any sequence of block codes sent over the memoryless binary symmetric…

Information Theory · Computer Science 2021-11-05 Ling-Hua Chang , Po-Ning Chen , Fady Alajaji , Yunghsiang S. Han

When utilising PAC-Bayes theory for risk certification, it is usually necessary to estimate and bound the Gibbs risk of the PAC-Bayes posterior. Many works in the literature employ a method for this which requires a large number of passes…

Machine Learning · Computer Science 2022-10-21 Felix Biggs

Adversarial examples pose a security threat to many critical systems built on neural networks. While certified training improves robustness, it also decreases accuracy noticeably. Despite various proposals for addressing this issue, the…

Machine Learning · Statistics 2024-06-21 Ruihan Zhang , Jun Sun

New upper and lower bounds for the error probability over an erasure channel are provided, making use of Wei's generalized weights, hierarchy and spectra. In many situations the upper and lower bounds coincide and this allows improvement of…

Information Theory · Computer Science 2014-07-18 Leandro Cruvinel Lemes , Marcelo Firer

We consider the problem of discriminating finite-dimensional quantum processes, also called quantum supermaps, that can consist of multiple time steps. Obtaining the ultimate performance for discriminating quantum processes is of…

Quantum Physics · Physics 2022-02-22 Kenji Nakahira , Kentaro Kato

We derive bounds on the asymptotic density of parity-check matrices and the achievable rates of binary linear block codes transmitted over memoryless binary-input output-symmetric (MBIOS) channels. The lower bounds on the density of…

Information Theory · Computer Science 2007-07-13 Gil Wiechman , Igal Sason

We consider secrecy obtained when one transmits on a Gaussian Wiretap channel above the secrecy capacity. Instead of equivocation, we consider probability of error as the criterion of secrecy. The usual channel codes are considered for…

Information Theory · Computer Science 2014-01-07 R. Rajesh , Shahid M. Shah , Vinod Sharma