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MAP is the problem of finding a most probable instantiation of a set of variables in a Bayesian network given some evidence. Unlike computing posterior probabilities, or MPE (a special case of MAP), the time and space complexity of…

Artificial Intelligence · Computer Science 2012-12-12 James D. Park , Adnan Darwiche

We consider the problem of computing reach-avoid probabilities for iterative predictions made with Bayesian neural network (BNN) models. Specifically, we leverage bound propagation techniques and backward recursion to compute lower bounds…

Machine Learning · Computer Science 2021-06-22 Matthew Wicker , Luca Laurenti , Andrea Patane , Nicola Paoletti , Alessandro Abate , Marta Kwiatkowska

The performance of maximum-likelihood (ML) decoded binary linear block codes is addressed via the derivation of tightened upper bounds on their decoding error probability. The upper bounds on the block and bit error probabilities are valid…

Information Theory · Computer Science 2007-07-13 M. Twitto , I. Sason , S. Shamai

Bounds on information combining are entropic inequalities that determine how the information, or entropy, of a set of random variables can change when they are combined in certain prescribed ways. Such bounds play an important role in…

Information Theory · Computer Science 2020-11-10 Christoph Hirche

In statistical inference problems, we wish to obtain lower bounds on the minimax risk, that is to bound the performance of any possible estimator. A standard technique to obtain risk lower bounds involves the use of Fano's inequality. In an…

Information Theory · Computer Science 2018-04-06 Ramji Venkataramanan , Oliver Johnson

Bayes' Theorem confers inherent limitations on the accuracy of screening tests as a function of disease prevalence. We have shown in previous work that a testing system can tolerate significant drops in prevalence, up until a certain…

Methodology · Statistics 2020-09-01 Jacques Balayla

While the channel capacity reflects a theoretical upper bound on the achievable information transmission rate in the limit of infinitely many bits, it does not characterise the information transfer of a given encoding routine with finitely…

Neurons and Cognition · Quantitative Biology 2017-04-05 Sebastian Weichwald , Tatiana Fomina , Bernhard Schölkopf , Moritz Grosse-Wentrup

We consider the common setting where one observes probability estimates for a large number of events, such as default risks for numerous bonds. Unfortunately, even with unbiased estimates, selecting events corresponding to the most extreme…

Methodology · Statistics 2021-10-14 Gareth M. James , Peter Radchenko , Bradley Rava

It is common practice to collect observations of feature and response pairs from different environments. A natural question is how to identify features that have consistent prediction power across environments. The invariant causal…

Information Theory · Computer Science 2022-07-01 Austin Goddard , Yu Xiang , Ilya Soloveychik

We examine regular and irregular repeat-accumulate (RA) codes with repetition degrees which are all even. For these codes and with a particular choice of an interleaver, we give an upper bound on the decoding error probability of a…

Information Theory · Computer Science 2010-02-22 Idan Goldenberg , David Burshtein

We consider a broad class of permutation invariant statistical problems by extending the standard decision theoretic definition to allow also selective inference tasks, where the target is specified only after seeing the data. For any such…

Statistics Theory · Mathematics 2025-02-06 Asaf Weinstein

In the field of reinforcement learning there has been recent progress towards safety and high-confidence bounds on policy performance. However, to our knowledge, no practical methods exist for determining high-confidence policy performance…

Artificial Intelligence · Computer Science 2018-06-26 Daniel S. Brown , Scott Niekum

In this work, a new upper bound for average error probability of a two-user discrete memoryless (DM) multiple-access channel (MAC) is derived. This bound can be universally obtained for all discrete memoryless MACs with given input and…

Information Theory · Computer Science 2009-01-09 Ali Nazari , Achilleas Anastasopoulos , S. Sandeep Pradhan

The following problem is considered: given a joint distribution $P_{XY}$ and an event $E$, bound $P_{XY}(E)$ in terms of $P_XP_Y(E)$ (where $P_XP_Y$ is the product of the marginals of $P_{XY}$) and a measure of dependence of $X$ and $Y$.…

Information Theory · Computer Science 2019-03-12 Ibrahim Issa , Amedeo Roberto Esposito , Michael Gastpar

We study a variation of Bayesian M-ary hypothesis testing in which the test outputs a list of L candidates out of the M possible upon processing the observation. We study the minimum error probability of list hypothesis testing, where an…

Information Theory · Computer Science 2021-10-28 Ehsan Asadi Kangarshahi , Albert Guillen i Fabregas

The performance of integer-forcing equalization for communication over the compound multiple-input multipleoutput channel is investigated. An upper bound on the resulting outage probability as a function of the gap to capacity has been…

Information Theory · Computer Science 2017-12-05 Elad Domanovitz , Uri Erez

We consider the problem of modulation and estimation of a random parameter $U$ to be conveyed across a discrete memoryless channel. Upper and lower bounds are derived for the best achievable exponential decay rate of a general moment of the…

Information Theory · Computer Science 2016-11-17 Neri Merhav

A new channel coding approach was proposed in [1] for random multiple access communication over the discrete-time memoryless channel. The coding approach allows users to choose their communication rates independently without sharing the…

Information Theory · Computer Science 2016-11-15 Zheng Wang , Jie Luo

A new lower bound for the average probability or error for a two-user discrete memoryless (DM) multiple-access channel (MAC) is derived. This bound has a structure very similar to the well-known sphere packing packing bound derived by…

Information Theory · Computer Science 2010-10-08 Ali Nazari , S. Sandeep Pradhan , Achilleas Anastasopoulos

In certain applications involving the solution of a Bayesian inverse problem, it may not be possible or desirable to evaluate the full posterior, e.g. due to the high computational cost of doing so. This problem motivates the use of…

Statistics Theory · Mathematics 2024-02-27 Han Cheng Lie , T. J. Sullivan , Aretha Teckentrup