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Generalizing many well-known and natural scheduling problems, scheduling with job-specific cost functions has gained a lot of attention recently. In this setting, each job incurs a cost depending on its completion time, given by a private…

Data Structures and Algorithms · Computer Science 2014-03-07 Wiebke Höhn , Julián Mestre , Andreas Wiese

A theory of recursive and corecursive definitions has been developed in higher-order logic (HOL) and mechanized using Isabelle. Least fixedpoints express inductive data types such as strict lists; greatest fixedpoints express coinductive…

Logic in Computer Science · Computer Science 2007-05-23 Lawrence C. Paulson

Identifying the specific actions that achieve goals when solving a planning task might be beneficial for various planning applications. Traditionally, this identification occurs post-search, as some actions may temporarily achieve goals…

Artificial Intelligence · Computer Science 2025-08-12 Alberto Pozanco , Marianela Morales , Daniel Borrajo , Manuela Veloso

Exact, fully explicit, purely real analytical expressions for the material functions describing steady, startup, and cessation regimes of shear flows and of planar, uniaxial, and biaxial extensional flows of full linear Phan-Thien--Tanner…

Fluid Dynamics · Physics 2022-01-06 Dimitri Shogin

Special matrix functions have recently been investigated for regions of convergence, integral representations and the systems of matrix differential equation that these functions satisfy. In this paper, we find the recursion formulas for…

Classical Analysis and ODEs · Mathematics 2020-03-18 Vivek Sahai , Ashish Verma

Multi-task learning, as it is understood nowadays, consists of using one single model to carry out several similar tasks. From classifying hand-written characters of different alphabets to figuring out how to play several Atari games using…

Machine Learning · Computer Science 2019-03-25 Unai Garciarena , Alexander Mendiburu , Roberto Santana

We study how to infer new choices from prior choices using the framework of choice functions, a unifying mathematical framework for decision-making based on sets of preference orders. In particular, we define the natural (most conservative)…

Artificial Intelligence · Computer Science 2024-12-02 Arne Decadt , Alexander Erreygers , Jasper De Bock

In this work, we describe a self-replication-based mechanism for designing agents of increasing complexity. We demonstrate the validity of this approach by solving simple, standard evolutionary computation problems in simulation. In the…

Neural and Evolutionary Computing · Computer Science 2018-07-20 Thommen George Karimpanal

In this paper we consider a combination of the joint replenishment problem (JRP) and single machine scheduling with release dates. There is a single machine and one or more item types. Each job has a release date, a positive processing…

Data Structures and Algorithms · Computer Science 2022-03-03 Péter Györgyi , Tamás Kis , Tímea Tamási , József Békési

A key functionality of emerging connected autonomous systems such as smart transportation systems, smart cities, and the industrial Internet-of-Things, is the ability to process and learn from data collected at different physical locations.…

Machine Learning · Computer Science 2021-01-26 Konstantinos Gatsis

Problem definition: Supply chains are constantly evolving networks. Reinforcement learning is increasingly proposed as a solution to provide optimal control of these networks. Academic/practical: However, learning in continuously varying…

Systems and Control · Electrical Eng. & Systems 2023-12-27 Wan Wang , Haiyan Wang , Adam J. Sobey

Many applications that use empirically estimated functions face a curse of dimensionality, because the integrals over most function classes must be approximated by sampling. This paper introduces a novel regression-algorithm that learns…

Machine Learning · Computer Science 2015-03-31 Wendelin Böhmer , Klaus Obermayer

Generating robot motion that fulfills multiple tasks simultaneously is challenging due to the geometric constraints imposed by the robot. In this paper, we propose to solve multi-task problems through learning structured policies from human…

Robotics · Computer Science 2021-03-12 M. Asif Rana , Anqi Li , Dieter Fox , Sonia Chernova , Byron Boots , Nathan Ratliff

We consider a class of optimization problems that involve determining the maximum value that a function in a particular class can attain subject to a collection of difference constraints. We show that a particular linear programming…

Data Structures and Algorithms · Computer Science 2022-11-16 Sungjin Im , Benjamin Moseley , Hung Q. Ngo , Kirk Pruhs , Alireza Samadian

The current landscape of massive production industries is undergoing significant transformations driven by emerging customer trends and new smart manufacturing technologies. One such change is the imperative to implement mass customization,…

Neural and Evolutionary Computing · Computer Science 2024-08-13 Diego Rossit , Daniel Rossit , Sergio Nesmachnow

In this paper we study a proportionate flow shop of batching machines with release dates and a fixed number $m \geq 2$ of machines. The scheduling problem has so far barely received any attention in the literature, but recently its…

Data Structures and Algorithms · Computer Science 2020-11-30 Christoph Hertrich , Christian Weiß , Heiner Ackermann , Sandy Heydrich , Sven O. Krumke

We introduce and study a class of optimization problems we coin replenishment problems with fixed turnover times: a very natural model that has received little attention in the literature. Nodes with capacity for storing a certain commodity…

Data Structures and Algorithms · Computer Science 2017-12-15 Thomas Bosman , Martijn van Ee , Yang Jiao , Alberto Marchetti-Spaccamela , R. Ravi , Leen Stougie

The main purpose of this work is to characterize derivations through functional equations. This work consists of five chapters. In the first one, we summarize the most important notions and results from the theory of functional equations.…

Functional Analysis · Mathematics 2019-04-11 Eszter Gselmann

In this study, we address causal inference when only observational data and a valid causal ordering from the causal graph are available. We introduce a set of flow models that can recover component-wise, invertible transformation of…

Machine Learning · Computer Science 2024-12-16 Minh Khoa Le , Kien Do , Truyen Tran

The aim of this paper is to study a wide class of non-convex sweeping processes with moving constraint whose translation and deformation are represented by regulated functions, i.e., functions of not necessarily bounded variation admitting…

Dynamical Systems · Mathematics 2021-01-08 Pavel Krejci , Giselle Antunes Monteiro , Vincenzo Recupero
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