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In today's data-driven landscape, time series forecasting is pivotal in decision-making across various sectors. Yet, the proliferation of more diverse time series data, coupled with the expanding landscape of available forecasting methods,…

Machine Learning · Computer Science 2024-05-01 Marc-André Zöller , Marius Lindauer , Marco F. Huber

K-fold cross-validation is a widely used tool for assessing classifier performance. The reproducibility crisis faced by artificial intelligence partly results from the irreproducibility of reported k-fold cross-validation-based performance…

Machine Learning · Computer Science 2024-01-26 Attila Fazekas , Gyorgy Kovacs

Machine scheduling problems are a long-time key domain of algorithms and complexity research. A novel approach to machine scheduling problems are fixed-parameter algorithms. To stimulate this thriving research direction, we propose 15 open…

Optimization and Control · Mathematics 2018-10-02 Matthias Mnich , René van Bevern

Runtime verification is an area of formal methods that studies the dynamic analysis of execution traces against formal specifications. Typically, the two main activities in runtime verification efforts are the process of creating monitors…

Ensuring the reliability and verifiability of large language model (LLM)-enabled systems remains a significant challenge in software engineering. We propose a probabilistic framework for systematically analyzing and improving these systems…

Software Engineering · Computer Science 2025-04-15 Juan Manuel Baldonado , Flavia Bonomo-Braberman , Víctor Adrián Braberman

Strategies that artificially tighten high-criticality task deadlines in low-criticality behaviors have been successfully employed for scheduling mixed-criticality systems. Although efficient scheduling algorithms have been developed for…

Operating Systems · Computer Science 2020-03-13 Arvind Easwaran

Model-based verification allows to express behavioral correctness conditions like the validity of execution states, boundaries of variables or timing at a high level of abstraction and affirm that they are satisfied by a software system.…

Software Engineering · Computer Science 2017-03-21 Bugra M. Yildiz , Arend Rensink , Christoph Bockisch , Mehmet Aksit

The rapid proliferation of benchmarks for evaluating large language models (LLMs) has created an urgent need for systematic methods to assess benchmark quality itself. We propose Benchmark^2, a comprehensive framework comprising three…

We present Task Bench, a parameterized benchmark designed to explore the performance of parallel and distributed programming systems under a variety of application scenarios. Task Bench lowers the barrier to benchmarking multiple…

Autonomous robotic inspection, where a robot moves through its environment and inspects points of interest, has applications in industrial settings, structural health monitoring, and medicine. Planning the paths for a robot to safely and…

We address the problem of statically checking safety properties (such as assertions or deadlocks) for parameterized phaser programs. Phasers embody a non-trivial and modern synchronization construct used to orchestrate executions of…

Programming Languages · Computer Science 2021-05-13 Zeinab Ganjei , Ahmed Rezine , Ludovic Henrio , Petru Eles , Zebo Peng

Automatic verification of concurrent programs faces state explosion due to the exponential possible interleavings of its sequential components coupled with large or infinite state spaces. An alternative is deductive verification, where…

Programming Languages · Computer Science 2024-01-01 Yuan Xia , Jyotirmoy V. Deshmukh , Mukund Raghothaman , Srivatsan Ravi

The work concerns automatic generation of logical specifications from requirements models. Logical specifications obtained in such a way can be subjected to formal verification using deductive reasoning. Formal verification concerns…

Software Engineering · Computer Science 2014-02-11 Radoslaw Klimek

Modeling scheduling problems with conditional time intervals and cumulative functions has become a common approach when using modern commercial constraint programming solvers. This paradigm enables the modeling of a wide range of scheduling…

Artificial Intelligence · Computer Science 2025-12-09 Pierre Schaus , Charles Thomas , Roger Kameugne

We present a flexible framework for the automated competitive analysis of on-line scheduling algorithms for firm-deadline real-time tasks based on multi-objective graphs: Given a taskset and an on-line scheduling algorithm specified as a…

Data Structures and Algorithms · Computer Science 2014-09-16 Krishnendu Chatterjee , Andreas Pavlogiannis , Alexander Kößler , Ulrich Schmid

When a robot autonomously performs a complex task, it frequently must balance competing objectives while maintaining safety. This becomes more difficult in uncertain environments with stochastic outcomes. Enhancing transparency in the…

Robotics · Computer Science 2024-06-19 Peter Amorese , Shohei Wakayama , Nisar Ahmed , Morteza Lahijanian

Most real-world document collections involve various types of metadata, such as author, source, and date, and yet the most commonly-used approaches to modeling text corpora ignore this information. While specialized models have been…

Machine Learning · Statistics 2018-10-25 Dallas Card , Chenhao Tan , Noah A. Smith

We explore the effectiveness of an LLM-guided query refinement paradigm for extending the usability of embedding models to challenging zero-shot search and classification tasks. Our approach refines the embedding representation of a user…

Computation and Language · Computer Science 2026-05-13 Ariel Gera , Shir Ashury-Tahan , Gal Bloch , Ohad Eytan , Assaf Toledo

Timed B\"uchi automata provide a very expressive formalism for expressing requirements of real-time systems. Online monitoring and active testing of embedded real-time systems can then be achieved by symbolic execution of such automata on…

Formal Languages and Automata Theory · Computer Science 2025-07-30 Martin Fränzle , Thomas M. Grosen , Kim G. Larsen , Martin Zimmermann

Many tasks can be easily solved using machine learning techniques. However, some tasks cannot readily be solved using statistical models, requiring a symbolic approach instead. Program induction is one of the ways that such tasks can be…

Machine Learning · Computer Science 2024-02-13 Ahmad Ayaz Amin