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New contributions in the field of iterative optimisation heuristics are often made in an iterative manner. Novel algorithmic ideas are not proposed in isolation, but usually as an extension of a preexisting algorithm. Although these…

Neural and Evolutionary Computing · Computer Science 2023-04-20 Diederick Vermetten , Fabio Caraffini , Anna V. Kononova , Thomas Bäck

In matching markets such as kidney exchanges and freight exchanges, delayed matching has been shown to improve overall market efficiency. The benefits of delay are highly sensitive to participants' sojourn times and departure behavior, and…

Machine Learning · Computer Science 2026-02-27 Ruiqi Zhou , Donghao Zhu , Houcai Shen

This paper studies the adaptive optimal control problem for a class of linear time-delay systems described by delay differential equations (DDEs). A crucial strategy is to take advantage of recent developments in reinforcement learning and…

Systems and Control · Electrical Eng. & Systems 2022-10-04 Leilei Cui , Bo Pang , Zhong-Ping Jiang

Ultra-dense edge computing (UDEC) has great potential, especially in the 5G era, but it still faces challenges in its current solutions, such as the lack of: i) efficient utilization of multiple 5G resources (e.g., computation,…

Networking and Internet Architecture · Computer Science 2020-09-23 Shuai Yu , Xu Chen , Zhi Zhou , Xiaowen Gong , Di Wu

Quantum error correction (QEC) for fault-tolerant quantum computing requires a balanced decoding solution that offers high performance, low complexity, and low latency. However, the de facto standard, belief propagation (BP) combined with…

Quantum Physics · Physics 2026-05-04 Hee-Youl Kwak , Seong-Joon Park , Hyunwoo Jung , Jeongseok Ha , Jae-Won Kim

Cascades and speculative decoding are two common approaches to improving language models' inference efficiency. Both approaches involve interleaving models of different sizes, but via fundamentally distinct mechanisms: cascades employ a…

Computation and Language · Computer Science 2024-10-23 Harikrishna Narasimhan , Wittawat Jitkrittum , Ankit Singh Rawat , Seungyeon Kim , Neha Gupta , Aditya Krishna Menon , Sanjiv Kumar

The accuracy of information transmission while solving domain decomposed problems is crucial to smooth transition of a solution around the interface/overlapping region. This paper describes a systematical study on an accuracy enhancing…

Numerical Analysis · Mathematics 2021-12-17 Wenbin Dong , Yingjie Liu , Hansong Tang

For gradient flows, the existing structure-preserving schemes are difficult to achieve arbitrary high-order accuracy in time while preserving maximum-principle (MBP) and energy dissipating simultaneously. In this paper, we develop a new…

Numerical Analysis · Mathematics 2025-11-04 Qing Cheng , Tingfeng Wang , Xiaofei Zhao

Quantum error correction (QEC) is essential for scalable quantum computing. However, it requires classical decoders that are fast and accurate enough to keep pace with quantum hardware. While quantum low-density parity-check codes have…

Quantum Physics · Physics 2026-04-10 Andi Gu , J. Pablo Bonilla Ataides , Mikhail D. Lukin , Susanne F. Yelin

Fully implicit Runge-Kutta (IRK) methods have many desirable accuracy and stability properties as time integration schemes, but high-order IRK methods are not commonly used in practice with large-scale numerical PDEs because of the…

Numerical Analysis · Mathematics 2021-10-07 Ben S. Southworth , Oliver Krzysik , Will Pazner

We develop a delay-adaptive controller for a class of first-order hyperbolic partial integro-differential equations (PIDEs) with an unknown input delay. By employing a transport PDE to represent delayed actuator states, the system is…

Analysis of PDEs · Mathematics 2023-07-11 Shanshan Wang , Jie Qi , Miroslav Krstic

Latent ODE models provide flexible descriptions of dynamic systems, but they can struggle with extrapolation and predicting complicated non-linear dynamics. The latent ODE approach implicitly relies on encoders to identify unknown system…

Machine Learning · Computer Science 2024-10-14 Matt L. Sampson , Peter Melchior

Robust optimization is a framework for modeling optimization problems involving data uncertainty and during the last decades has been an area of active research. If we focus on linear programming (LP) problems with i) uncertain data, ii)…

Numerical Analysis · Computer Science 2017-02-15 Roberto Mínguez , Víctor Casero-Alonso

We propose a practical implementation of high-order fully implicit Runge-Kutta(IRK) methods in a multiple precision floating-point environment. Although implementations based on IRK methods in an IEEE754 double precision environment have…

Numerical Analysis · Mathematics 2013-06-18 Tomonori Kouya

Delay-Differential Equations (DDEs) are the most common representation for systems with delay. However, the DDE representation is limited. In network models with delay, the delayed channels are low-dimensional and accounting for this…

Optimization and Control · Mathematics 2020-12-21 Matthew M. Peet

We introduce a family of stochastic optimization methods based on the Runge-Kutta-Chebyshev (RKC) schemes. The RKC methods are explicit methods originally designed for solving stiff ordinary differential equations by ensuring that their…

Optimization and Control · Mathematics 2022-02-01 Tony Stillfjord , Måns Williamson

We present a dynamically load-balanced parallel $ p $-adaptive implicit high-order flux reconstruction method for under-resolved turbulence simulation. The high-order explicit first stage, singly diagonal implicit Runge-Kutta (ESDIRK)…

Computational Physics · Physics 2020-07-15 Lai Wang , Matthias K. Gobbert , Meilin Yu

One of main obstacles in verifying the energy dissipation laws of implicit-explicit Runge-Kutta (IERK) methods for phase field equations is to establish the uniform boundedness of stage solutions without the global Lipschitz continuity…

Numerical Analysis · Mathematics 2024-12-11 Hong-lin Liao , Tao Tang , Xuping Wang , Tao Zhou

We present the Rate-Distortion Explanation (RDE) framework, a mathematically well-founded method for explaining black-box model decisions. The framework is based on perturbations of the target input signal and applies to any differentiable…

Machine Learning · Computer Science 2021-10-19 Stefan Kolek , Duc Anh Nguyen , Ron Levie , Joan Bruna , Gitta Kutyniok

In order to investigate correspondences between 3D shapes, many methods rely on a feature descriptor which is invariant under almost isometric transformations. An interesting class of models for such descriptors relies on partial…

Numerical Analysis · Mathematics 2019-10-10 Martin Bähr , Michael Breuß , Robert Dachsel
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