English
Related papers

Related papers: Expanding Belnap 2: the dual category in depth

200 papers

Deep learning has achieved impressive prediction accuracies in a variety of scientific and industrial domains. However, the nested non-linear feature of deep learning makes the learning highly non-transparent, i.e., it is still unknown how…

Machine Learning · Computer Science 2020-10-26 Chan Li , Haiping Huang

We propose a new bi-intuitionistic type theory called Dualized Type Theory (DTT). It is a simple type theory with perfect intuitionistic duality, and corresponds to a single-sided polarized sequent calculus. We prove DTT strongly…

Logic in Computer Science · Computer Science 2019-03-14 Harley Eades , Aaron Stump , Ryan McCleeary

In this paper we show that there is a link between approximate Bayesian methods and prior robustness. We show that what is typically recognized as an approximation to the likelihood, either due to the simulated data as in the Approximate…

Methodology · Statistics 2020-04-03 Chaitanya Joshi , Fabrizio Ruggeri

In problems such as variable selection and graph estimation, models are characterized by Boolean logical structure such as presence or absence of a variable or an edge. Consequently, false positive error or false negative error can be…

Methodology · Statistics 2025-04-15 Armeen Taeb , Peter Bühlmann , Venkat Chandrasekaran

We introduce the notion of pre-weight structure on a triangulated category and study the corresponding pseudo-identities. We propose the notion of canonical derived equivalence between algebras that are not necessarily flat, which is…

Representation Theory · Mathematics 2025-11-20 Xiao-Wu Chen

There is much interest in providing probabilistic semantics for defaults but most approaches seem to suffer from one of two problems: either they require numbers, a problem defaults were intended to avoid, or they generate peculiar side…

Artificial Intelligence · Computer Science 2013-04-10 Eric Neufeld , David L Poole

We investigate finite right-distributive binary algebraic structures called shelves. We first use symbolic computations with Python to classify (up to isomorphism) all connected shelves with order less than six. We explore the group…

Geometric Topology · Mathematics 2023-07-24 Mohamed Elhamdadi , Neranga Fernando , Mathew Goonewardena

The first system of many-valued logic was introduced by J. Lukasiewicz, his motivation was of philosophical nature as he was looking for an interpretation of the concepts of possibility and necessity. Since then, plenty of research has been…

Logic · Mathematics 2012-04-20 A. V. Figallo , I. Pascual y A. Ziliani

Many applications, e.g. in content recommendation, sports, or recruitment, leverage the comparisons of alternatives to score those alternatives. The classical Bradley-Terry model and its variants have been widely used to do so. The…

Methodology · Statistics 2024-02-23 Julien Fageot , Sadegh Farhadkhani , Lê Nguyên Hoang , Oscar Villemaud

This paper introduces a novel method for compact representation of sets of n-dimensional binary sequences in a form of compact triplets structures (CTS), supposing both logic and arithmetic interpretations of data. Suitable illustration of…

Data Structures and Algorithms · Computer Science 2011-01-13 V. F. Romanov

Bipartite determinantal ideals are introduced by Illian and the author as a vast generalization of the classical determinantal ideals intensively studied in commutative algebra, algebraic geometry, representation theory and combinatorics.…

Commutative Algebra · Mathematics 2024-07-22 Li Li

Display calculi are generalized sequent calculi which enjoy a `canonical' cut elimination strategy. That is, their cut elimination is uniformly obtained by verifying the assumptions of a meta-theorem, and is preserved by adding or removing…

Bayesian networks (BNs) are graphical \emph{first-order} probabilistic models that allow for a compact representation of large probability distributions, and for efficient inference, both exact and approximate. We introduce a…

Logic in Computer Science · Computer Science 2023-12-12 Claudia Faggian , Daniele Pautasso , Gabriele Vanoni

We present a new approach to dealing with default information based on the theory of belief functions. Our semantic structures, inspired by Adams' epsilon-semantics, are epsilon-belief assignments, where values committed to focal elements…

Artificial Intelligence · Computer Science 2013-02-21 Salem Benferhat , Alessandro Saffiotti , Philippe Smets

Regular and higher regular graded algebras (in simplest case satisfying Von Neumann regularity $\Theta_{1}\Theta_{2}\Theta_{1}=\Theta_{1}$ instead of anticommutativity) are introduced and their properties are studied. They are described in…

Quantum Algebra · Mathematics 2007-05-23 Steven Duplij , Wladyslaw Marcinek

Learning from Label Proportions (LLP) is a learning problem where only aggregate level labels are available for groups of instances, called bags, during training, and the aim is to get the best performance at the instance-level on the test…

Machine Learning · Computer Science 2024-03-21 Shreyas Havaldar , Navodita Sharma , Shubhi Sareen , Karthikeyan Shanmugam , Aravindan Raghuveer

Derived categories were invented by Grothendieck and Verdier around 1960, not very long after the "old" homological algebra (of derived functors between abelian categories) was established. This "new" homological algebra, of derived…

K-Theory and Homology · Mathematics 2015-01-28 Amnon Yekutieli

Profinite algebras are exactly those that are isomorphic to inverse limits of finite algebras. Such algebras are naturally equipped with Boolean topologies. A variety $\mathcal V$ is standard if every Boolean topological algebra with the…

Logic · Mathematics 2019-02-20 Anvar M. Nurakunov , Michał M. Stronkowski

In this paper, we investigate proof-theoretic aspects of the logics of evidence and truth LETJ and LETF. These logics extend, respectively, Nelson's logic N and the logic of first-degree entailment FDE, also known as Belnap-Dunn four-valued…

Logic · Mathematics 2024-06-03 Marcelo E. Coniglio , Martín Figallo , Abilio Rodrigues

Recent research towards understanding neural networks probes models in a top-down manner, but is only able to identify model tendencies that are known a priori. We propose Susceptibility Identification through Fine-Tuning (SIFT), a novel…

Computation and Language · Computer Science 2019-09-11 Jonas Pfeiffer , Aishwarya Kamath , Iryna Gurevych , Sebastian Ruder