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Given a sequence of Boolean functions $(f_n)_{n \geq 1}$, $f_n \colon \{ 0,1 \}^{n} \to \{ 0,1 \}$, and a sequence $(X^{(n)})_{n\geq 1} $ of continuous time $p_n $-biased random walks $ X^{(n)} = (X_t^{(n)})_{t \geq 0}$ on $ \{ 0,1 \}^{n}$,…

Probability · Mathematics 2021-01-05 Malin Palö Forsström

We present an algebraic semantics for governed execution in which governance is axiomatized, compositional, and coterminous with expressibility. The framework, mechanized in 32 Rocq modules (~12,000 lines, 454 theorems, 0 admitted), is…

Artificial Intelligence · Computer Science 2026-05-27 Alan L. McCann

Mixed-integer nonlinear programs (MINLPs) arise in domains such as energy systems, process engineering, and transportation, and are notoriously difficult to solve at scale due to the interplay of discrete decisions and nonlinear…

Machine Learning · Computer Science 2025-12-16 Bo Tang , Elias B. Khalil , Ján Drgoňa

Runtime efficiency and termination are crucial properties in the studies of program verification. Instead of dealing with these issues in an ad hoc manner, it would be useful to develop a robust framework in which such properties are…

Programming Languages · Computer Science 2026-04-06 Weijun Chen , Yuxi Fu , Huan Long

Functional linear regression is a widely used approach to model functional responses with respect to functional inputs. However, classical functional linear regression models can be severely affected by outliers. We therefore introduce a…

Methodology · Statistics 2019-09-02 Harjit Hullait , David S. Leslie , Nicos G. Pavlidis , Steve King

As machine learning models are increasingly being employed in various high-stakes settings, it becomes important to ensure that predictions of these models are not only adversarially robust, but also readily explainable to relevant…

Machine Learning · Computer Science 2024-07-25 Satyapriya Krishna , Chirag Agarwal , Himabindu Lakkaraju

Regression models are used in a wide range of applications providing a powerful scientific tool for researchers from different fields. Linear, or simple parametric, models are often not sufficient to describe complex relationships between…

Machine Learning · Statistics 2021-11-24 Aliaksandr Hubin , Geir Storvik , Florian Frommlet

We define a measure for the complexity of Boolean functions related to their implementation in neural networks, and in particular close related to the generalization ability that could be obtained through the learning process. The measure…

Disordered Systems and Neural Networks · Physics 2007-05-23 Leonardo Franco

Given a property of Boolean functions, what is the minimum number of queries required to determine with high probability if an input function satisfies this property or is "far" from satisfying it? This is a fundamental question in Property…

Data Structures and Algorithms · Computer Science 2016-01-13 Noga Alon , Rani Hod , Amit Weinstein

We study the symmetry of the one-loop effective action of bosonic string theory under non-Abelian T-duality transformations. It is shown that the original Lagrangian and its dual are proportional. This result implies that the corresponding…

High Energy Physics - Theory · Physics 2009-10-31 A. Bossard , N. Mohammedi

The performance of state-of-the-art offline RL methods varies widely over the spectrum of dataset qualities, ranging from far-from-optimal random data to close-to-optimal expert demonstrations. We re-implement these methods to test their…

Machine Learning · Computer Science 2022-01-20 Lionel Blondé , Alexandros Kalousis , Stéphane Marchand-Maillet

Hard optimisation problems such as Boolean Satisfiability typically have long solving times and can usually be solved by many algorithms, although the performance can vary widely in practice. Research has shown that no single algorithm…

Machine Learning · Computer Science 2019-09-10 Riccardo Volpato , Guangyan Song

We consider a variant of the Boolean satisfiability problem where a subset E of the propositional variables appearing in formula Fsat encode a symmetric, transitive, binary relation over N elements. Each of these relational variables,…

Logic in Computer Science · Computer Science 2007-05-23 Randal E. Bryant , Miroslav N. Velev

Predictive models are finding an increasing number of applications in many industries. As a result, a practical means for trading-off the cost of deploying a model versus its effectiveness is needed. Our work is motivated by risk prediction…

Machine Learning · Statistics 2016-04-21 Daniel P. Robinson , Suchi Saria

Border's theorem gives an intuitive linear characterization of the feasible interim allocation rules of a Bayesian single-item environment, and it has several applications in economic and algorithmic mechanism design. All known…

Computer Science and Game Theory · Computer Science 2015-04-30 Parikshit Gopalan , Noam Nisan , Tim Roughgarden

The distinction between strong negation and default negation has been useful in answer set programming. We present an alternative account of strong negation, which lets us view strong negation in terms of the functional stable model…

Artificial Intelligence · Computer Science 2013-12-24 Michael Bartholomew , Joohyung Lee

In Boolean algebra, it is known that the logical function that corresponds to the negation of the conjunction --NAND-- is universal in the sense that any other logical function can be built based on it. This property makes it essential to…

Emerging Technologies · Computer Science 2015-08-14 Victor Hernandez-Urbina

We study the most-informative Boolean function conjecture using a differential equation approach. This leads to a formulation of a functional inequality on finite-dimensional random variables. We also develop a similar inequality in the…

Information Theory · Computer Science 2025-02-17 Zijie Chen , Amin Gohari , Chandra Nair

In the fillable array problem one must maintain an array A[1..n] of $w$-bit entries subject to random access reads and writes, and also a $\texttt{fill}(\Delta)$ operation which sets every entry of to some $\Delta\in\{0,\ldots,2^w-1\}$. We…

Data Structures and Algorithms · Computer Science 2017-09-28 Jacob Teo Por Loong , Jelani Nelson , Huacheng Yu

We give a structure theorem for all coalitionally strategy-proof social choice functions whose range is a subset of cardinality two of a given larger set of alternatives. We provide this in the case where the voters/agents are allowed to…

Theoretical Economics · Economics 2020-07-06 Achille Basile , Surekha Rao , K. P. S. Bhaskara Rao
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