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Empirical modelling often aims for the simplest model consistent with the data. A new technique is presented which quantifies the consistency of the model dynamics as a function of location in state space. As is well-known, traditional…

Chaotic Dynamics · Physics 2009-11-10 Patrick E. McSharry , Leonard A. Smith

Motivated by an application where we try to make proofs for Description Logic inferences smaller by rewriting, we consider the following decision problem, which we call the small term reachability problem: given a term rewriting system $R$,…

Logic in Computer Science · Computer Science 2025-10-22 Franz Baader , Jürgen Giesl

In this paper we present a framework for risk-averse model predictive control (MPC) of linear systems affected by multiplicative uncertainty. Our key innovation is to consider time-consistent, dynamic risk metrics as objective functions to…

Optimization and Control · Mathematics 2015-11-24 Yin-Lam Chow , Marco Pavone

This paper considers parallel machine scheduling with incompatibilities between jobs. The jobs form a graph and no two jobs connected by an edge are allowed to be assigned to the same machine. In particular, we study the case where the…

Computational Complexity · Computer Science 2021-03-16 Klaus Jansen , Alexandra Lassota , Marten Maack , Tytus Pikies

This paper proposes a finitely terminating algorithm to solve reach-and-stay control problems for nonlinear systems. The algorithm is guaranteed to return a control strategy if the specification is robustly realizable. Such a feature is…

Optimization and Control · Mathematics 2020-04-17 Yinan Li , Jun Liu

To implement a linearizable shared memory in synchronous message-passing systems it is necessary to wait for a time linear to the uncertainty in the latency of the network for both read and write operations. Waiting only for one of them…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-07-28 Matthieu Perrin , Matoula Petrolia , Achour Mostefaoui , Claude Jard

Addressing the reproducibility crisis in artificial intelligence through the validation of reported experimental results is a challenging task. It necessitates either the reimplementation of techniques or a meticulous assessment of papers…

Machine Learning · Computer Science 2023-11-14 György Kovács , Attila Fazekas

Methods for forecasting time series adhering to linear constraints have seen notable development in recent years, especially with the advent of forecast reconciliation. This paper extends forecast reconciliation to the open question of…

Methodology · Statistics 2025-10-27 Daniele Girolimetto , Anastasios Panagiotelis , Tommaso Di Fonzo , Han Li

We study decidability of verification problems for timed automata extended with unbounded discrete data structures. More detailed, we extend timed automata with a pushdown stack. In this way, we obtain a strong model that may for instance…

Logic in Computer Science · Computer Science 2017-01-11 Karin Quaas

This paper focuses on the analysis of real-time non preemptive multiprocessor scheduling with precedence and several latency constraints. It aims to specify a schedulability condition which enables a designer to check a priori -without…

Operating Systems · Computer Science 2013-01-22 Omar Kermia

In this paper we propose a new type of random CSP model, called Model RB, which is a revision to the standard Model B. It is proved that phase transitions from a region where almost all problems are satisfiable to a region where almost all…

Artificial Intelligence · Computer Science 2007-05-23 Ke Xu , Wei Li

Model predictive control solves a constrained optimization problem online in order to compute an implicit closed-loop control policy. Recursive feasibility -- guaranteeing that the optimal control problem will have a solution at every time…

Optimization and Control · Mathematics 2024-10-16 Jacob W. Knaup , Panagiotis Tsiotras

As an important and challenging problem in computer vision and graphics, keypoint-based object tracking is typically formulated in a spatio-temporal statistical learning framework. However, most existing keypoint trackers are incapable of…

Computer Vision and Pattern Recognition · Computer Science 2014-12-05 Liming Zhao , Xi Li , Jun Xiao , Fei Wu , Yueting Zhuang

Many statistical models have high accuracy on test benchmarks, but are not explainable, struggle in low-resource scenarios, cannot be reused for multiple tasks, and cannot easily integrate domain expertise. These factors limit their use,…

Computation and Language · Computer Science 2021-09-29 Andrew Lee , Jonathan K. Kummerfeld , Lawrence C. An , Rada Mihalcea

A constant-rate multi-mode system is a hybrid system that can switch freely among a finite set of modes, and whose dynamics is specified by a finite number of real-valued variables with mode-dependent constant rates. Alur, Wojtczak, and…

Logic in Computer Science · Computer Science 2017-07-14 Shankara Narayanan Krishna , Aviral Kumar , Fabio Somenzi , Behrouz Touri , Ashutosh Trivedi

A continuous constraint satisfaction problem (CCSP) is a constraint satisfaction problem (CSP) with an interval domain $U \subset \mathbb{R}$. We engage in a systematic study to classify CCSPs that are complete of the Existential Theory of…

Computational Complexity · Computer Science 2024-08-07 Tillmann Miltzow , Reinier F. Schmiermann

The expressive power of interval temporal logics (ITLs) makes them one of the most natural choices in a number of application domains, ranging from the specification and verification of complex reactive systems to automated planning.…

Logic in Computer Science · Computer Science 2023-06-22 Laura Bozzelli , Alberto Molinari , Angelo Montanari , Adriano Peron , Pietro Sala

In this paper we study reachability verification problems of stochastic discrete-time dynamical systems over the infinite time horizon. The reachability verification of interest in this paper is to certify specified lower and upper bounds…

Systems and Control · Electrical Eng. & Systems 2023-02-21 Bai Xue

Pairwise-constrained clustering incorporates side information through must-link (ML) and cannot-link (CL) relations between samples. While these constraints can improve cluster quality, they complicate optimization at scale and limit…

Machine Learning · Computer Science 2026-03-10 Pedro Chumpitaz-Flores , My Duong , Ying Mao , Kaixun Hua

Conformal risk control (CRC) provides distribution-free guarantees for controlling the expected loss at a user-specified level. Existing theory typically assumes that the loss decreases monotonically with a tuning parameter that governs the…

Machine Learning · Statistics 2026-04-21 Tareq Aldirawi , Yun Li , Wenge Guo
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