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The Journal of Machine Learning Research 2022年第1期23卷 9893-9988页

作者： Alireza Fallah Mert Gürbüzbalaban Asuman Ozdaglar Umut Şimşekli Lingjiong Zhu Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA Department of Management Science and Information Systems Departments of Electrical Engineering and Statistics Rutgers University Piscataway NJ INRIA - Département d'Informatique de l' École Normale Supérieure PSL Research University Paris France Department of Mathematics Florida State University Tallahassee FL

We study distributed stochastic gradient (D-SG) method and its accelerated variant (D-ASG) for solving decentralized strongly convex stochastic optimization problems where the objective function is distributed over several computational units, lying on a fixed but arbitrary connected communication graph, subject to local communication constraints where noisy estimates of the gradients are available. We develop a framework which allows to choose the stepsize and the momentum parameters of these algorithms in a way to optimize performance by systematically trading off the bias, variance and dependence to network effects. When gradients do not contain noise, we also prove that D-ASG can achieve acceleration, in the sense that it requires O(√κlog(1/ε)) gradient evaluations and O(√κlog(1/ε)) communications to converge to the same fixed point with the non-accelerated variant where κ is the condition number and ε is the target accuracy. For quadratic functions, we also provide finer performance bounds that are tight with respect to bias and variance terms. Finally, we study a multistage version of D-ASG with parameters carefully varied over stages to ensure exact convergence to the optimal solution. It achieves optimal and accelerated O(-k/√κ) linear decay in the bias term as well as optimal O(σ2/k) in the variance term. We illustrate through numerical experiments that our approach results in accelerated practical algorithms that are robust to gradient noise and that can outperform existing methods.

关键词： distributed optimization accelerated methods stochastic optimization robustness multi-agent networks

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Learning from Multi-Perception Features for Real-Word Image Super-resolution

arXiv

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arXiv 2023年

作者： Niu, Axi Zhang, Kang Pham, Trung X. Wang, Pei Sun, Jinqiu Kweon, In So Zhang, Yanning The School of Computer Science Northwestern Polytechnical University Xi’an710072 China The National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710072 China The School of Electrical Engineering Korea Advanced Institute of Science and Technology Korea Republic of The School of Astronautics Northwestern Polytechnical University Xi’an710072 China

Currently, there are two popular approaches for addressing real-world image super-resolution problems: degradation-estimation-based and blind-based methods. However, degradation-estimation-based methods may be inaccurate in estimating the degradation, making them less applicable to real-world LR images. On the other hand, blind-based methods are often limited by their fixed single perception information, which hinders their ability to handle diverse perceptual characteristics. To overcome this limitation, we propose a novel SR method called MPF-Net that leverages multiple perceptual features of input images. Our method incorporates a Multi-Perception Feature Extraction (MPFE) module to extract diverse perceptual information and a series of newly-designed Cross-Perception Blocks (CPB) to combine this information for effective super-resolution reconstruction. Additionally, we introduce a contrastive regularization term (CR) that improves the model’s learning capability by using newly generated HR and LR images as positive and negative samples for ground truth HR. Experimental results on challenging real-world SR datasets demonstrate that our approach significantly outperforms existing state-of-the-art methods in both qualitative and quantitative measures. © 2023, CC BY.

关键词： Feature extraction

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Percolative Silver Nanowires/Polyvinylidene Fluoride Epsilon-Negative Materials with Low Losses Derived from the Ultra-Low Percolation Threshold

SSRN

引用

SSRN 2022年

作者： Hou, Qing Wang, Zongxiang Sun, Kai Tian, Jiahong Ju, Licheng Fan, Runhua Institute of Photonic Chips University of Shanghai for Science and Technology Shanghai200093 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China College of Ocean Science and Engineering Shanghai Maritime University Shanghai201306 China School of Materials Science and Engineering Zhejiang University Hangzhou310027 China

The epsilon-negative materials involving lower losses have attracted increasing attention due to their significant applications in novel capacitors and antennas. The silver nanowires/polyvinylidene fluoride (AgNWs/PVDF) composites were therefore prepared to reveal the mechanism of negative permittivity response involving lower losses. Due to the large aspect ratios of AgNWs, an ultra-low percolation threshold (fc) between 0.7 and 0.8 wt.% was achieved in which the losses have been effectively decreased with several magnitudes to a low level of 0.2. The negative permittivity response from Lorentz type and Drude type presented the transition from insulator to conductor. The tunable Drude type negative permittivity was ascribed to the plasma oscillation of free electrons which leads to an inductive property. The conduction mechanism was switched from hopping to metallic conduction with the observation of skin effect. © 2022, The Authors. All rights reserved.

关键词： Percolation (fluids)

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Tuning Negative Permittivity by Anodization of a 3d Copper Network

SSRN

引用

SSRN 2022年

作者： Hou, Qing Ju, Licheng Qin, Faxiang Peng, Huaxin Fan, Runhua Institute of Photonic Chips University of Shanghai for Science and Technology Shanghai200093 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China School of Materials Science and Engineering Zhejiang University Hangzhou310027 China School of Ocean Science and Engineering Shanghai Maritime University Shanghai201306 China

Negative permittivity is a required physical property of metamaterials which has been widely used in some emerging and unconventional applications, such as cloaking, perfect lens and perfect wave absorption. In addition to periodic meta-structured units, a composite with conductive networks, so-called metacomposite, is equivalent to diluted metals, which also exhibits negative permittivity properties at microwave frequency. The percolative metacomposites have the advantages of isotropic property, flexible preparation methods and low cost in achieving negative permittivity. However, building a percolation network from conductive fillers in an insulating matrix is a complicated process, and the dispersion of fillers is difficult to control. In this study, the percolation network was modulated on the basis of the conductive copper foam by anodization treatment. The conductivity and negative permittivity of the foam varied with the anodization time. As the anodization time increased, the foam changed from a typical Drude metal to a less conductive 3D structure with mitigated negative permittivity. The absolute value of the negative permittivity of Cu-30V-5h sample was two orders of magnitude lower than that of the samples anodised for 30V-3h, 20V-3h and 20V-1h. Therefore, anodization is a facile and effective method to control the conductivity and negative permittivity of copper epoxy metacomposites. © 2022, The Authors. All rights reserved.

关键词： Copper

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A probabilistic forecast-driven strategy for a risk-aware participation in the capacity firming market: Extended version

arXiv

引用

arXiv 2021年

作者： Dumas, Jonathan Cointe, Colin Wehenkel, Antoine Sutera, Antonio Fettweis, Xavier Cornélusse, Bertrand Departments of Computer Science and Electrical Engineering and Geography University of Liège Liège4000 Belgium

This paper addresses the energy management of a grid-connected renewable generation plant coupled with a battery energy storage device in the capacity firming market, designed to promote renewable power generation facilities in small noninterconnected grids. The core contribution is to propose a probabilistic forecast-driven strategy, modeled as a min-maxmin robust optimization problem with recourse. It is solved using a Benders-dual cutting plane algorithm and a column and constraints generation algorithm in a tractable manner. A dynamic risk-averse parameters selection strategy based on the quantile forecasts distribution is proposed to improve the results. A secondary contribution is to use a recently developed deep learning model known as normalizing flows to generate quantile forecasts of renewable generation for the robust optimization problem. This technique provides a general mechanism for defining expressive probability distributions, only requiring the specification of a base distribution and a series of bijective transformations. Overall, the robust approach improves the results over a deterministic approach with nominal point forecasts by finding a trade-off between conservative and risk-seeking policies. The case study uses the photovoltaic generation monitored on-site at the University of Liege (ULiège), Belgium. © 2021, CC BY-NC-ND.

关键词： Deep learning

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Pseudo-mutual gazing enhances interbrain synchrony during remote joint attention tasking

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Brain and Behavior 2023年第10期13卷 e3181页

作者： Chuang, Chun-Hsiang Hsu, Hao-Che Research Center for Education and Mind Sciences College of Education National Tsing Hua University Hsinchu Taiwan Institute of Information Systems and Applications College of Electrical Engineering and Computer Science National Tsing Hua University Hsinchu Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Computer Science and Engineering National Taiwan Ocean University Keelung Taiwan

Introduction: Mutual gaze enables people to share attention and increase engagement during social interactions through intentional and implicit messages. Although previous studies have explored gaze behaviors and neural mechanisms underlying in-person eye contact, the growing prevalence of remote communication has raised questions about how to establish mutual gaze remotely and how the brains of interacting individuals synchronize. Methods: To address these questions, we conducted a study using eye trackers to create a pseudo-mutual gaze channel that mirrors the gazes of each interacting dyad on their respective remote screens. To demonstrate fluctuations in coupling across brains, we incorporated electroencephalographic hyperscanning techniques to simultaneously record the brain activity of interacting dyads engaged in a joint attention task in player-observer, collaborative, and competitive modes. Results: Our results indicated that mutual gaze could improve the efficiency of joint attention activities among remote partners. Moreover, by employing the phase locking value, we could estimate interbrain synchrony (IBS) and observe low-frequency couplings in the frontal and temporal regions that varied based on the interaction mode. While dyadic gender composition significantly affected gaze patterns, it did not impact the IBS. Conclusion: These results provide insight into the neurological mechanisms underlying remote interaction through the pseudo-mutual gaze channel and have significant implications for developing effective online communication environments. © 2023 The Authors. Brain and Behavior published by Wiley Periodicals LLC.

关键词： cooperation and competition hyperscanning EEG interbrain synchrony joint attention mutual gaze phase locking value

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Convolution and Attention Mixer for Synthetic Aperture Radar Image Change Detection

arXiv

引用

arXiv 2023年

作者： Zhang, Haopeng Lin, Zijing Gao, Feng Dong, Junyu Du, Qian Li, Heng-Chao The School of Computer Science and Technology Ocean University of China Qingdao266100 China The Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States The Sichuan Provincial Key Laboratory of Information Coding and Transmission Southwest Jiaotong University Chengdu610031 China

Synthetic aperture radar (SAR) image change detection is a critical task and has received increasing attentions in the remote sensing community. However, existing SAR change detection methods are mainly based on convolutional neural networks (CNNs), with limited consideration of global attention mechanism. In this letter, we explore Transformer-like architecture for SAR change detection to incorporate global attention. To this end, we propose a convolution and attention mixer (CAMixer). First, to compensate the inductive bias for Transformer, we combine self-attention with shift convolution in a parallel way. The parallel design effectively captures the global semantic information via the self-attention and performs local feature extraction through shift convolution simultaneously. Second, we adopt a gating mechanism in the feed-forward network to enhance the non-linear feature transformation. The gating mechanism is formulated as the element-wise multiplication of two parallel linear layers. Important features can be highlighted, leading to high-quality representations against speckle noise. Extensive experiments conducted on three SAR datasets verify the superior performance of the proposed CAMixer. The source codes will be publicly available at https://***/summitgao/CAMixer. © 2023, CC BY.

关键词： Convolution

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Study of ASIC Readout Used for Detectors in an MR Compatible, RF-Penetrable TOF-PET Insert

Study of ASIC Readout Used for Detectors in an MR Compatible...

引用

IEEE Symposium on Nuclear science (NSS/MIC)

作者： Qian Dong Salar Sajedi Ilaria Sacco Peter Fischer Craig S. Levin Departments of Electrical Engineering and Radiology Stanford University Stanford CA USA Departments of Radiology Stanford University Stanford CA USA Department of Computer Science Heidelberg University Baden-Württemberg Germany Department of Radiology Electrical Engineering Bioengineering and Physics Stanford University Molecular Imaging Program at Stanford (MIPS) Stanford CA USA

Developing positron emission tomography (PET) systems with high channel number has driven the need for application-specific integrated circuits (ASICs) owing to their compactness, multi-channel readout capability, and excellent time and energy resolution performance. They can also be quite flexible by employing field-programmable gate arrays (FPGAs) in the readout circuit. In particular, the ASIC+FPGA approach provides a high performance and compact solution for TOF-PET applications. ASICs serve functions of extracting time and energy information from analog SiPM signals, and an FPGA is employed for other application-specific requirements like on-board chip configuration, communication with data acquisition (DAQ) systems, and system monitoring. Based on this foundation, we developed TOF-capable detector modules for our second generation RF-penetrable PET insert. During our previous experiments, we found that different trigger and readout methods lead to different noise pattern and intensity in MR environment, and also have different singles count loss ratio. This paper aims to study and compare different readout configurations for our MR-compatible detectors. We studied four trigger and readout methods: hit-standard, frequent-standard, hit-bypass, and frequent-bypass, and compared their singles count loss ratios with both theoretical models and experimental results. For all four methods, the theoretical results matched the experimental results well. The two methods which used bypass mode performed better than those using the standard mode approach. With the most optimized trigger and readout method (hit-bypass), we achieved 1.2% singles count loss ratio at a 20 kcps count rate per channel.

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High-Fidelity Micro- and Nano-Scale Infrared Spectroscopic Imaging

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 562-562页

作者： Bhargava, Rohit Yeh, Kevin Kenkel, Seth Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign Urbana IL United States Departments of Bioengineering Chemical and Biomolecular Engineering Electrical and Computer Engineering Mechanical Science and Engineering University of Illinois at Urbana-Champaign Urbana IL United States Cancer Center at Illinois University of Illinois at Urbana- Champaign Urbana IL United States

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A Conditional Flow Variational Autoencoder for Controllable Synthesis of Virtual Populations of Anatomy

arXiv

引用

arXiv 2023年

作者： Dou, Haoran Ravikumar, Nishant Frangi, Alejandro F. University of Leeds Leeds United Kingdom Division of Informatics Imaging and Data Science Schools of Computer Science and Health Sciences University of Manchester Manchester United Kingdom Electrical Engineering and Cardiovascular Sciences Departments KU Leuven Leuven Belgium Alan Turing Institute London United Kingdom

The generation of virtual populations (VPs) of anatomy is essential for conducting in silico trials of medical devices. Typically, the generated VP should capture sufficient variability while remaining plausible and should reflect the specific characteristics and demographics of the patients observed in real populations. In several applications, it is desirable to synthesise virtual populations in a controlled manner, where relevant covariates are used to conditionally synthesise virtual populations that fit a specific target population/characteristics. We propose to equip a conditional variational autoencoder (cVAE) with normalising flows to boost the flexibility and complexity of the approximate posterior learnt, leading to enhanced flexibility for controllable synthesis of VPs of anatomical structures. We demonstrate the performance of our conditional flow VAE using a data set of cardiac left ventricles acquired from 2360 patients, with associated demographic information and clinical measurements (used as covariates/conditional information). The results obtained indicate the superiority of the proposed method for conditional synthesis of virtual populations of cardiac left ventricles relative to a cVAE. Conditional synthesis performance was evaluated in terms of generalisation and specificity errors and in terms of the ability to preserve clinically relevant biomarkers in synthesised VPs, that is, the left ventricular blood pool and myocardial volume, relative to the real observed population. © 2023, CC BY.

关键词： Population statistics

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