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The incompressibility method is an elementary yet powerful proof technique. It has been used successfully in many areas. To further demonstrate its power and elegance we exhibit new simple proofs using the incompressibility method.

Computational Complexity · Computer Science 2007-05-23 Tao Jiang , Ming Li , Paul Vitanyi

Verification methods based on SAT, SMT, and Theorem Proving often rely on proofs of unsatisfiability as a powerful tool to extract information in order to reduce the overall effort. For example a proof may be traversed to identify a minimal…

Logic in Computer Science · Computer Science 2014-04-16 S. F. Rollini , R. Bruttomesso , N. Sharygina , A. Tsitovich

Explainability is needed to establish confidence in machine learning results. Some explainable methods take a post hoc approach to explain the weights of machine learning models, others highlight areas of the input contributing to…

Machine Learning · Computer Science 2024-07-15 Paul Whitten , Francis Wolff , Chris Papachristou

We present a fully-explicit, iteration-free, weakly-compressible method to simulate immiscible incompressible two-phase flows. To update pressure, we circumvent the computationally expensive Poisson equation and use the general pressure…

Fluid Dynamics · Physics 2024-06-03 Hormuzd Bodhanwalla , Dheeraj Raghunathan , Y. Sudhakar

We examine a new approach to modeling uncertainty based on plausibility measures, where a plausibility measure just associates with an event its plausibility, an element is some partially ordered set. This approach is easily seen to…

Artificial Intelligence · Computer Science 2013-02-21 Nir Friedman , Joseph Y. Halpern

We present a novel, perspicuous framework for building iterated ultrapowers. Furthermore, our framework naturally lends itself to the construction of a certain type of order indiscernibles, here dubbed tight indiscernibles, which are shown…

Logic · Mathematics 2017-08-01 Ali Enayat , Matt Kaufmann , Zachiri McKenzie

We argue that robustness of explanations---i.e., that similar inputs should give rise to similar explanations---is a key desideratum for interpretability. We introduce metrics to quantify robustness and demonstrate that current methods do…

Machine Learning · Computer Science 2018-06-22 David Alvarez-Melis , Tommi S. Jaakkola

Reachability Logic is a formalism that can be used, among others, for expressing partial-correctness properties of transition systems. In this paper we present three proof systems for this formalism, all of which are sound and complete and…

Logic in Computer Science · Computer Science 2019-09-05 Vlad Rusu , David Nowak

This is a survey on propositional proof complexity aimed at introducing the basics of the field with a particular focus on a method known as feasible interpolation. This method is used to construct "hard theorems" for several proof systems…

Logic · Mathematics 2025-05-07 Amirhossein Akbar Tabatabai

We study a well-known technique of using absoluteness for giving choice-free proofs to some statements which are known to be provable with the axiom of choice. The idea is to reduce the problem to an inner model where the axiom of choice…

Logic · Mathematics 2014-02-20 Asaf Karagila

We present a simple new method for proving that languages are not regular. We prove the correctness of the method, illustrate the ease of using the method on well-known examples of nonregular languages, and prove two additional theorems on…

Formal Languages and Automata Theory · Computer Science 2020-01-27 Jack H. Lutz , Giora Slutzki

We present a method to prove the decidability of provability in several well-known inference systems. This method generalizes both cut-elimination and the construction of an automaton recognizing the provable propositions.

Logic in Computer Science · Computer Science 2016-01-08 Gilles Dowek , Ying Jiang

When a proposition has no proof in an inference system, it is sometimes useful to build a counter-proof explaining, step by step, the reason of this non-provability. In general, this counter-proof is a (possibly) infinite co-inductive proof…

Logic in Computer Science · Computer Science 2023-04-12 Gilles Dowek , Ying Jiang

In this paper we present a new approach to proving some exponential inequalities involving the sinc function. Power series expansions are used to generate new polynomial inequalities that are sufficient to prove the given exponential…

Classical Analysis and ODEs · Mathematics 2019-10-15 T. Lutovac , B. Malesevic , M. Rasajski

Explainability and comprehensibility of AI are important requirements for intelligent systems deployed in real-world domains. Users want and frequently need to understand how decisions impacting them are made. Similarly it is important to…

Computers and Society · Computer Science 2019-07-10 Roman V. Yampolskiy

The article proposes a new technique for proving the undefinability of logical connectives through each other and illustrates the technique with several examples. Some of the obtained results are new proofs of the existing theorems, others…

Artificial Intelligence · Computer Science 2023-07-04 Sophia Knight , Pavel Naumov , Qi Shi , Vigasan Suntharraj

In science and medicine, model interpretations may be reported as discoveries of natural phenomena or used to guide patient treatments. In such high-stakes tasks, false discoveries may lead investigators astray. These applications would…

Machine Learning · Statistics 2020-08-18 Collin Burns , Jesse Thomason , Wesley Tansey

The usual reading of logical implication "A implies B" as "if A then B" fails in intuitionistic logic: there are formulas A and B such that "A implies B" is not provable, even though B is provable whenever A is provable. Intuitionistic…

Logic in Computer Science · Computer Science 2018-10-18 Andrea Condoluci , Matteo Manighetti

This paper suggests a new interpretation of the Dempster-Shafer theory in terms of probabilistic interpretation of plausibility. A new rule of combination of independent evidence is shown and its preservation of interpretation is…

Artificial Intelligence · Computer Science 2017-04-07 Mieczysław Kłopotek

Interpretability is the study of explaining models in understandable terms to humans. At present, interpretability is divided into two paradigms: the intrinsic paradigm, which believes that only models designed to be explained can be…

Machine Learning · Computer Science 2024-11-14 Andreas Madsen , Himabindu Lakkaraju , Siva Reddy , Sarath Chandar
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