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Related papers: Scoped Capabilities for Polymorphic Effects

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Mapper is an algorithm that summarizes the topological information contained in a dataset and provides an insightful visualization. It takes as input a point cloud which is possibly high-dimensional, a filter function on it and an open…

Algebraic Topology · Mathematics 2019-03-12 Bishal Deb , Ankita Sarkar , Nupur Kumari , Akash Rupela , Piyush Gupta , Balaji Krishnamurthy

We introduce a variable importance measure to quantify the impact of individual input variables to a black box function. Our measure is based on the Shapley value from cooperative game theory. Many measures of variable importance operate by…

Machine Learning · Computer Science 2020-10-05 Masayoshi Mase , Art B. Owen , Benjamin Seiler

Complex information-processing systems, for example quantum circuits, cryptographic protocols, or multi-player games, are naturally described as networks composed of more basic information-processing systems. A modular analysis of such…

Quantum Physics · Physics 2017-04-27 Christopher Portmann , Christian Matt , Ueli Maurer , Renato Renner , Björn Tackmann

Context: Tables are ubiquitous formats for data. Therefore, techniques for writing correct programs over tables, and debugging incorrect ones, are vital. Our specific focus in this paper is on rich types that articulate the properties of…

Programming Languages · Computer Science 2021-11-23 Kuang-Chen Lu , Ben Greenman , Shriram Krishnamurthi

A software product line models the variability of highly configurable systems. Complete exploration of all valid configurations (the configuration space) is infeasible as it grows exponentially with the number of features in the worst case.…

Quantum Physics · Physics 2023-07-28 Joshua Ammermann , Tim Bittner , Domenik Eichhorn , Ina Schaefer , Christoph Seidl

We present a complete polymorphic effect inference algorithm for an ML-style language with handlers of not only exceptions, but of any other algebraic effect such as input & output, mutable references and many others. Our main aim is to…

Programming Languages · Computer Science 2015-07-01 Matija Pretnar

We propose the integration of staged metaprogramming into a session-typed message passing functional language. We build on a model of contextual modal type theory with multi-level contexts, where contextual values, closing arbitrary terms…

Programming Languages · Computer Science 2026-01-22 Pedro Ângelo , Atsushi Igarashi , Yuito Murase , Vasco T. Vasconcelos

Polymorphic types are an important feature in most strongly typed programming languages. They allow functions to be written in a way that can be used with different data types, while still enforcing the relationship and constraints between…

Programming Languages · Computer Science 2024-05-22 Shuai Fu , Tim Dwyer , Peter J. Stuckey

Labelled tableaux have been a traditional approach to define satisfiability checking procedures for Modal Logics. In many cases, they can also be used to obtain tight complexity bounds and lead to efficient implementations of reasoning…

Logic in Computer Science · Computer Science 2025-12-10 Carlos Areces , Valentin Cassano , Raul Fervari

Mathematics has many useful properties for developing of complex software systems. One is that it can exactly describe a physical situation of the object or outcome of an action. Mathematics support abstraction and this is an excellent…

Software Engineering · Computer Science 2010-04-19 Manoranjan Kumar Singh , Rakesh. L

We describe a type system for the linear-algebraic $\lambda$-calculus. The type system accounts for the linear-algebraic aspects of this extension of $\lambda$-calculus: it is able to statically describe the linear combinations of terms…

Logic in Computer Science · Computer Science 2017-05-12 Pablo Arrighi , Alejandro Díaz-Caro , Benoît Valiron

Many computer science disciplines (e.g., combinatorial optimization, natural language processing, and information retrieval) use standard or established test suites for evaluating algorithms. In visualization, similar approaches have been…

Graphics · Computer Science 2020-09-29 Pascal Nardini , Min Chen , Roxana Bujack , Michael Böttinger , Gerik Scheuermann

Understanding the effect of a feature vector $x \in \mathbb{R}^d$ on the response value (label) $y \in \mathbb{R}$ is the cornerstone of many statistical learning problems. Ideally, it is desired to understand how a set of collected…

Machine Learning · Computer Science 2023-06-22 Mohammad Mehrabi , Ryan A. Rossi

Configuration-Constrained Tube Model Predictive Control (CCTMPC) offers flexibility by using a polytopic parameterization of invariant sets and the optimization of an associated vertex control law. This flexibility, however, often demands…

Systems and Control · Electrical Eng. & Systems 2026-01-21 Filippo Badalamenti , Sampath Kumar Mulagaleti , Mario Eduardo Villanueva , Boris Houska , Alberto Bemporad

Optimization-based safety filters, such as control barrier function (CBF) based quadratic programs (QPs), have demonstrated success in controlling autonomous systems to achieve complex goals. These CBF-QPs can be shown to be continuous, but…

Systems and Control · Electrical Eng. & Systems 2023-09-25 Max H. Cohen , Pio Ong , Gilbert Bahati , Aaron D. Ames

Video Captioning (VC) is a challenging multi-modal task since it requires describing the scene in language by understanding various and complex videos. For machines, the traditional VC follows the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-11 Jianqiao Sun , Yudi Su , Hao Zhang , Ziheng Cheng , Zequn Zeng , Zhengjue Wang , Bo Chen , Xin Yuan

This paper proposes probabilistic conformal prediction (PCP), a predictive inference algorithm that estimates a target variable by a discontinuous predictive set. Given inputs, PCP construct the predictive set based on random samples from…

Machine Learning · Statistics 2022-06-22 Zhendong Wang , Ruijiang Gao , Mingzhang Yin , Mingyuan Zhou , David M. Blei

Multivariate time-dependent data, where multiple features are observed over time for a set of individuals, are increasingly widespread in many application domains. To model these data we need to account for relations among both time…

Methodology · Statistics 2021-04-08 Alessandro Casa , Charles Bouveyron , Elena Erosheva , Giovanna Menardi

Data-trained predictive models see widespread use, but for the most part they are used as black boxes which output a prediction or score. It is therefore hard to acquire a deeper understanding of model behavior, and in particular how…

The paper describes a novel method of sampled-data in space (spatial variable) control of scalar semilinear systems of parabolic and hyperbolic type with unknown parameters and distributed disturbances. A finite set of sampled-data in the…

Systems and Control · Electrical Eng. & Systems 2020-09-30 Igor Furtat , Pavel Gushchin