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The evaluation of hyperparameters, neural architectures, or data augmentation policies becomes a critical model selection problem in advanced deep learning with a large hyperparameter search space. In this paper, we propose an efficient and…

Machine Learning · Statistics 2020-12-17 Yimin Huang , Yujun Li , Hanrong Ye , Zhenguo Li , Zhihua Zhang

Service systems are labor intensive due to the large variation in the tasks required to address service requests from multiple customers. Aligning the staffing levels to the forecasted workloads adaptively in such systems is nontrivial…

Systems and Control · Computer Science 2013-12-31 L. A. Prashanth , H. L. Prasad , Nirmit Desai , Shalabh Bhatnagar , Gargi Dasgupta

Parameter updating is an important stage in parallelism-based distributed deep learning. Synchronous methods are widely used in distributed training the Deep Neural Networks (DNNs). To reduce the communication and synchronization overhead…

Machine Learning · Computer Science 2020-09-09 Qing Ye , Yuxuan Han , Yanan sun , JIancheng Lv

This paper presents a new predictive second order sliding controller (PSSC) formulation for setpoint tracking of constrained linear systems. The PSSC scheme is developed by combining the concepts of model predictive control (MPC) and second…

Systems and Control · Computer Science 2018-02-07 Mohammad Reza Amini , Mahdi Shahbakhti , Jing Sun

We propose a method for controlling synchronization patterns of limit-cycle oscillators by common noisy inputs, i.e., by utilizing noise-induced synchronization. Various synchronization patterns, including fully synchronized and clustered…

Adaptation and Self-Organizing Systems · Physics 2015-02-18 Wataru Kurebayashi , Tsubasa Ishii , Mikio Hasegawa , Hiroya Nakao

Ant Colony System (ACS) is a distributed (agent- based) algorithm which has been widely studied on the Symmetric Travelling Salesman Problem (TSP). The optimum parameters for this algorithm have to be found by trial and error. We use a…

Optimization and Control · Mathematics 2018-03-23 D Gómez-Cabrero , D. N. Ranasinghe

Although the raison d'etre of the brain is the survival of the body, there are relatively few theoretical studies of closed-loop rhythmic motor control systems. In this paper we provide a unified framework, based on variational analysis,…

Neurons and Cognition · Quantitative Biology 2024-09-13 Zhuojun Yu , Peter J. Thomas

This paper explores the novel concept of damping controller coordination, which aims to minimize the Total Action metric by identifying an optimal switching combination (on/off) of these controllers. The metric is rooted in power system…

Systems and Control · Electrical Eng. & Systems 2024-05-03 Francisco Zelaya-Arrazabal , Hector Pulgar-Painemal , Jingzi Liu , Horacio Silva-Saravia , Fangxing Li

5G backscatter communication presents an emerging energy-efficient IoT connectivity solution with enhanced availability and data rate advantages over traditional wireless networks. For 5G backscatter, synchronization is crucial as it…

Networking and Internet Architecture · Computer Science 2026-04-29 Yunyun Feng , Chenhong Cao , Si Chen , Wei Gong

This paper considers an adaptive tracking control problem for stochastic regression systems with multi-threshold quantized observations. Different from the existing studies for periodic reference signals, the reference signal in this paper…

Systems and Control · Electrical Eng. & Systems 2024-04-30 Chuiliu Kong , Ying Wang

Optimization with preference feedback is an active research area with many applications in engineering systems where humans play a central role, such as building control and autonomous vehicles. While most existing studies focus on…

Optimization and Control · Mathematics 2026-03-31 Wenbin Wang , Wenjie Xu , Colin N. Jones

Stochastic optimal control (SOC) aims to direct the behavior of noisy systems and has widespread applications in science, engineering, and artificial intelligence. In particular, reward fine-tuning of diffusion and flow matching models and…

Machine Learning · Computer Science 2024-10-29 Carles Domingo-Enrich

BPSO algorithm is a swarm intelligence optimization algorithm, which has the characteristics of good optimization effect, high efficiency and easy to implement. In recent years, it has been used to optimize a variety of machine learning and…

Neural and Evolutionary Computing · Computer Science 2024-07-26 Qing Zhao , Chengkui Zhang , Hao Li , Ting Ke

A method of targeting engineering synchronization states in two identical and mismatch chaotic systems is explained in details. The method is proposed using linear feedback controller coupling for engineering synchronization such as mixed…

Chaotic Dynamics · Physics 2015-06-16 Sourav K. Bhowmick , Dibakar Ghosh

Optimal nonlinear damping control was recently introduced for the second-order SISO systems, showing some advantages over a classical PD feedback controller. This paper summarizes the main theoretical developments and properties of the…

Systems and Control · Electrical Eng. & Systems 2022-08-09 Michael Ruderman

In this paper, we study the numerical method for stochastic optimal control problems (SOCPs). By reducing the optimal control problem to the discrete case, we derive a discrete stochastic maximum principle (SMP). With the help of this SMP,…

Numerical Analysis · Mathematics 2020-07-14 Mingshang Hu , Lianzi Jiang

Decentralized heading control is crucial for robotic network operations such as surveillance, exploration, and cooperative construction. However, few results consider decentralized heading control when the speed of heading adjustment is…

Systems and Control · Electrical Eng. & Systems 2019-10-17 Timothy Anglea , Yongqiang Wang

The aim of this research is to design a PID Controller using particle swarm optimization (PSO) algorithm for multiple-input multiple output (MIMO) Takagi-Sugeno fuzzy model. The conventional gain tuning of PID controller (such as…

Systems and Control · Computer Science 2013-06-27 Adel Taeib , Ali Ltaeif , Abdelkader Chaari

In this paper, we consider the problem of sleeping bandits with stochastic action sets and adversarial rewards. In this setting, in contrast to most work in bandits, the actions may not be available at all times. For instance, some products…

Machine Learning · Computer Science 2020-08-11 Aadirupa Saha , Pierre Gaillard , Michal Valko

This article presents the parallel implementation of the coupled harmonic oscillator. From the analytical solution of the coupled harmonic oscillator, the design parameters are obtained. After that, a numerical integration of the system…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-09 Anas M. Al-Oraiqat