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Given a bounded class of functions G and independent random variables X1, . . . , Xn, we provide an upper bound for the expectation of the supremum of the empirical process over elements of G having a small variance. Our bound applies in…

Probability · Mathematics 2015-09-08 Yannick Baraud

Weak superimposed codes are combinatorial structures related closely to generalized cover-free families, superimposed codes, and disjunct matrices in that they are only required to satisfy similar but less stringent conditions. This class…

Information Theory · Computer Science 2024-09-17 Yu Tsunoda , Yuichiro Fujiwara

We present a theory for slicing probabilistic imperative programs -- containing random assignments, and ``observe'' statements (for conditioning) -- represented as probabilistic control-flow graphs (pCFGs) whose nodes modify probability…

Programming Languages · Computer Science 2017-11-08 Torben Amtoft , Anindya Banerjee

We give a finite-sample analysis of predictive inference procedures after model selection in regression with random design. The analysis is focused on a statistically challenging scenario where the number of potentially important…

Statistics Theory · Mathematics 2009-08-26 Hannes Leeb

Control systems operating in the real world face countless sources of unpredictable uncertainties. These random disturbances can render deterministic guarantees inapplicable and cause catastrophic safety failures. To overcome this, this…

Systems and Control · Electrical Eng. & Systems 2026-02-10 Pol Mestres , Blake Werner , Ryan K. Cosner , Aaron D. Ames

Bounded-size rules are dynamic random graph processes which incorporate limited choice along with randomness in the evolution of the system. One starts with the empty graph and at each stage two edges are chosen uniformly at random. One of…

Probability · Mathematics 2019-02-20 Shankar Bhamidi , Amarjit Budhiraja , Xuan Wang

Despite numerous countermeasures proposed by practitioners and researchers, remote control-flow alteration of programs with memory-safety vulnerabilities continues to be a realistic threat. Guaranteeing that complex software is completely…

Cryptography and Security · Computer Science 2017-02-20 Martín Ochoa , Sebastian Banescu , Cynthia Disenfeld , Gilles Barthe , Vijay Ganesh

Distributional collision resistance is a relaxation of collision resistance that only requires that it is hard to sample a collision $(x,y)$ where $x$ is uniformly random and $y$ is uniformly random conditioned on colliding with $x$. The…

Cryptography and Security · Computer Science 2021-05-04 Nir Bitansky , Iftach Haitner , Ilan Komargodski , Eylon Yogev

Conditional risk minimization arises in high-stakes decisions where risk must be assessed in light of side information, such as stressed economic conditions, specific customer profiles, or other contextual covariates. Constructing reliable…

Machine Learning · Statistics 2025-09-30 Xinqiao Xie , Jonathan Yu-Meng Li

Random K-out graphs are garnering interest in designing distributed systems including secure sensor networks, anonymous crypto-currency networks, and differentially-private decentralized learning. In these security-critical applications, it…

Information Theory · Computer Science 2023-11-07 Eray Can Elumar , Mansi Sood , Osman Yağan

We study the richness of the ensemble of graphical structures (i.e., unlabeled graphs) of the one-dimensional random geometric graph model defined by $n$ nodes randomly scattered in $[0,1]$ that connect if they are within the connection…

Information Theory · Computer Science 2022-06-24 Mihai-Alin Badiu , Justin P. Coon

We present new estimators for the statistical analysis of the dependence of the mean gap time length between consecutive recurrent events, on a set of explanatory random variables and in the presence of right censoring. The dependence is…

Applications · Statistics 2021-09-10 Ioana Schiopu-Kratina , Hai Yan Liu , Mayer Alvo , Pierre-Jerome Bergeron

We present two new constructions of quantum hash functions: the first based on expander graphs and the second based on extractor functions and estimate the amount of randomness that is needed to construct them. We also propose a keyed…

Quantum Physics · Physics 2016-06-02 Mansur Ziatdinov

We obtain revenue guarantees for the simple pricing mechanism of a single posted price, in terms of a natural parameter of the distribution of buyers' valuations. Our revenue guarantee applies to the single item n buyers setting, with…

Computer Science and Game Theory · Computer Science 2015-06-02 Balasubramanian Sivan , Vasilis Syrgkanis , Omer Tamuz

We take a general approach to uncertainty on product spaces, and give sufficient conditions for the independence structures of uncertainty measures to satisfy graphoid properties. Since these conditions are arguably more intuitive than some…

Artificial Intelligence · Computer Science 2013-02-28 Nic Wilson

We derive an exponentially decaying upper-bound on the unnormalized amount of information leaked to the wire-tapper in Wyner's wire-tap channel setting. We characterize the exponent of the bound as a function of the randomness used by the…

Information Theory · Computer Science 2016-02-12 Mani Bastani Parizi , Emre Telatar

The main objective of this work is twofold. On the one hand, it gives a brief overview of the area of two-party cryptographic protocols. On the other hand, it proposes new schemes and guidelines for improving the practice of robust protocol…

Cryptography and Security · Computer Science 2015-03-17 Pino Caballero-Gil , Amparo Fúster-Sabater

In this article we introduce a simple tool to derive polynomial upper bounds for the probability of observing unusually large maximal components in some models of random graphs when considered at criticality. Specifically, we apply our…

Probability · Mathematics 2022-02-01 Umberto De Ambroggio

Let $D \subseteq A$ be an inclusion of unital abelian $C^*$-algebras. In this note we characterize (in topological terms) when there is a unique conditional expectation $E:A \to D$, at least when $A$ is separable. As an application, we…

Operator Algebras · Mathematics 2016-09-21 Vrej Zarikian

{\em Algorithms with predictions} incorporate machine learning predictions into algorithm design. A plethora of recent works incorporated predictions to improve on worst-case optimal bounds for online problems. In this paper, we initiate…

Data Structures and Algorithms · Computer Science 2023-09-12 Monika Henzinger , Barna Saha , Martin P. Seybold , Christopher Ye
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