检索结果-内蒙古大学图书馆

4th IEEE International Conference on quantum computing and engineering, QCE 2023

作者： Majumdar, Ritajit Rivero, Pedro Metz, Friedrike Hasan, Areeq Wang, Derek S. Ibm Quantum Ibm India Research Lab India Ibm Quantum Ibm T. J. Watson Research Center United States Institute of Physics Ecole Polytechnique Fédérale de Lausanne Switzerland Center for Quantum Science and Engineering Ecole Polytechnique Fédérale de Lausanne Switzerland Princeton University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350343236

Digital zero-noise extrapolation (dZNE) has emerged as a common approach for quantum error mitigation (QEM) due to its conceptual simplicity, accessibility, and resource efficiency. In practice, however, properly applying dZNE to extend the computational reach of noisy quantum processors is rife with subtleties. Here, based on literature review and original experiments on noisy simulators and real quantum hardware, we define best practices for QEM with dZNE for each step of the workflow, including noise amplification, execution on the quantum device, extrapolation to the zero-noise limit, and composition with other QEM methods. We anticipate that this effort to establish best practices for dZNE will be extended to other QEM methods, leading to more reproducible and rigorous calculations on noisy quantum hardware. The full version of this paper can be found in Ref. [1]. © 2023 IEEE.

关键词： Extrapolation

来源：评论

学校读者我要写书评

暂无评论

Frequency-bin Bell state generation via successive single and dual spectral-line pumping

Frequency-bin Bell state generation via successive single an...

引用

CLEO: QELS_Fundamental Science, QELS 2022

作者： Seshadri, Suparna Lu, Hsuan-Hao Leaird, Daniel E. Weiner, Andrew M. Lukens, Joseph M. School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States

We demonstrate a simple and versatile scheme to generate all four two-dimensional frequency-bin Bell states using single and dual spectral-line pumps and passive filtering. Experimentally, we measure ≥97% fidelity fo... 详细信息

ISBN: (纸本)9781557528209

关键词： Spectroscopy

来源：评论

学校读者我要写书评

暂无评论

quantum delay metrology with complete frequency-bin Bell basis synthesizer

Quantum delay metrology with complete frequency-bin Bell bas...

引用

Frontiers in Optics, FiO 2022

We generate all four frequency-bin Bell states via single and dual spectral-line pumping of spontaneous parametric down-conversion and demonstrate their sensitivity to the sum and difference of entangled-photon delays... 详细信息

ISBN: (纸本)9781557528209

关键词： quantum entanglement

来源：评论

学校读者我要写书评

暂无评论

Shared Bodily Fusion: Leveraging Inter-Body electrical Muscle Stimulation for Social Play

Shared Bodily Fusion: Leveraging Inter-Body Electrical Muscl...

引用

2024 ACM Designing Interactive Systems Conference, DIS 2024

作者： Patibanda, Rakesh Overdevest, Nathalie Nisal, Shreyas Saini, Aryan Elvitigala, Don Samitha Knibbe, Jarrod van den Hoven, Elise Mueller, Florian Exertion Games Lab Department of Human-Centred Computing Monash University Melbourne Australia School of Electrical Engineering and Computer Science Faculty of Engineering The University of Queensland St LuciaQLD Australia Materialising Memories & Visualisation Institute University of Technology Sydney Sydney Australia Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9798400705830

Traditional games like "Tag" rely on shared control via inter-body interactions (IBIs) – touching, pushing, and pulling – that foster emotional and social connection. Digital games largely limit IBIs, with players using their bodies as input to control virtual avatars instead. Our "Shared Bodily Fusion" approach addresses this by fusing players’ bodies through a mediating computer, creating a shared input and output system. We demonstrate this approach with "Hidden Touch", a game where a novel social electrical muscle stimulation system transforms touch (input) into muscle actuations (output), facilitating IBIs. Through a study (n=27), we identifed three player experience themes. Informed by these fndings and our design process, we mapped their trajectories across our three experiential spaces – threshold, tolerance, and precision – which collectively form our design framework. This framework facilitates the creation of future digital games where IBIs are intrinsic, ultimately promoting the many benefts of social play. © 2024 Copyright held by the owner/author(s).

关键词： Muscle

来源：评论

学校读者我要写书评

暂无评论

Vector Quantized Compressed Sensing for Communication-Efficient Federated Learning

Vector Quantized Compressed Sensing for Communication-Effici...

引用

2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Oh, Yongjeong Jeon, Yo-Seb Chen, Mingzhe Saad, Walid POSTECH Department of Electrical Engineering Gyeongbuk Pohang37673 Korea Republic of Institute for Data Science and Computing University of Miami Department of Electrical and Computer Engineering Coral GablesFL33146 United States Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24060 United States

ISBN: (纸本)9781665459754

In this paper, a communication-efficient federated learning (FL) framework is proposed, which leverages ideas from vector quantized compressed sensing, for the first time, to compress the local model updates at wireless devices in FL. For the compression, each local model update is projected onto a lower dimensional space;then, the projected local model update is quantized by using a vector quantizer. The global model update at a parameter server is reconstructed by using a sparse signal recovery algorithm on the aggregation of the compressed local model updates. A key feature of our compression strategy is that the local model update after the projection is effectively modeled as a Gaussian random vector by the central limit theorem. Inspired by this feature, the optimal vector quantizer is derived for minimizing the compression error of the local model update. Simulation results on the MNIST dataset demonstrate that the proposed framework that uses 0.5 bit to represent each local model update entry shows less than a 1% decrease in classification accuracy compared to FL without local update compression. © 2022 IEEE.

关键词： Compressed sensing

来源：评论

学校读者我要写书评

暂无评论

Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Accelerator 8

Deep Mapper: A Multi-Channel Single-Cycle Near-Sensor DNN Ac...

引用

8th IEEE International Conference on Rebooting computing, ICRC 2023

作者： Morsali, Mehrdad Tabrizchi, Sepehr Liehr, Maximilian Cady, Nathaniel Imani, Mohsen Roohi, Arman Angizi, Shaahin New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ United States University of Nebraska-Lincoln School of Computing LincolnNE United States Suny Polytechnic Institute College of Nanoscale Science and Engineering AlbanyNY United States University of California Irvine Department of Computer Science IrvineCA United States

ISBN: (纸本)9798350382044

This work proposes the Deep Mapper, as a new near-sensor resistive accelerator architecture for Deep Neural Networks (DNN) inference that co-integrates the sensing and computing phases of resource-constrained edge devices. Deep Mapper is developed to intrinsically realize highly parallelized multi-channel processing of input frames supported by a new dense hardware-friendly mapping methodology. Our circuit-to-application simulation results on the DNN acceleration task show that Deep Mapper reaches an efficiency of 4.71 TOp/s/W outperforming state-of-the-art near-/in-sensor accelerators. © 2023 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Scalable Dynamic Resource Allocation via Domain Randomized Reinforcement Learning

Scalable Dynamic Resource Allocation via Domain Randomized R...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Yiqi Wang Laixi Shi Martin Hyungwoo Lee Jaroslaw Sydir Zhu Zhou Yuejie Chi Bin Li Electrical and Computer Engineering Carnegie Mellon University Computing and Mathematical Sciences California Institute of Technology Intel Labs Intel Corporation

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In 5G wireless networks, the User Plane Function (UPF) plays a crucial role in efficiently transferring users’ traffic — a series of data packets — to manage internet communications. Setting the server’s processor frequency excessively high can easily meet the packet drop requirements but may lead to unnecessary power consumption. Therefore, as user traffic fluctuates, selecting the optimal processor frequency is essential for minimizing power consumption while satisfying packet drop constraints. This challenge motivates us to address the dynamic resource (frequency) allocation problem, where deep reinforcement learning (RL) has shown significant potential. Most existing studies train and evaluate the RL model in the same environment with consistent traffic patterns. However, frequent variations in user traffic can cause the policy trained on the outdated traffic to fail catastrophically on unseen *** address such traffic distribution shifts, we propose a two-phase RL approach augmented with Automatic Domain Randomization (RL-ADR). This method includes a training phase that utilizes domain randomization to create a library of policy candidates, and an inference phase that selects the optimal frequency using this policy library alongside a safe data buffer. The proposed RL-ADR achieves zero packet drops on two unseen long-horizon traffics (3 hours) after being trained on 25 synthetic traffics that only span for 18 seconds. Compared to static resource allocation baselines, RL-ADR reduces power consumption by at least 14.5% and performs comparably to the oracle solution.

关键词： Training Power demand Wireless networks Traffic control Dynamic scheduling Deep reinforcement learning Libraries Resource management Global communication Radio spectrum management

来源：评论

学校读者我要写书评

暂无评论

Development of Interpretable Machine Learning Models for COVID-19 Drug Target Docking Scores Prediction

Development of Interpretable Machine Learning Models for COV...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Shi, Wenqi Murakoso, Mio Guo, Xiaoyan Wang, May D. Georgia Institute of Technology Department of Electrical and Computer Engineering Atlanta United States Kyoto University Department of Applied Life Science Kyoto Japan Georgia Institute of Technology College of Computing Atlanta United States Georgia Institute of Technology Wallace H. Coulter Department of Biomedical Engineering Atlanta United States

ISBN: (纸本)9798350337488

With the extensive time and financial requirements incumbent on drug discovery, computational approaches, such as protein-ligand docking predictions, are increasingly crucial for accelerating the process of drug repurposing. However, the proliferation of identified protein targets has exposed a critical knowledge gap in developing robust models that offer both generalizability and interpretability for docking score prediction. Addressing this, our study presents a machine learning-based surrogate model, employing interpretable artificial intelligence techniques for accurate docking score prediction for SARS-CoV-2 protein targets. We demonstrate the model generalization on its expansion to accommodate unseen protein targets by integrating protein target information through feature concatenation. Moreover, we leverage the SHapley Additive exPlanations (SHAP) method to identify the data-driven feature importance of molecular substructures for knowledge-based validation. Our experiments reveal that the combination of data-driven prediction and knowledge-driven validation could provide biomedical insights into the interactions between drugs and SARS-CoV-2 proteins, elucidating their consequent effects on docking scores. © 2023 IEEE.

关键词： COVID-19 drug target explainable artificial intelligence interaction prediction machine learning

来源：评论

学校读者我要写书评

暂无评论

Coil Optimization using Metaheuristic Techniques for Wireless Charging of Electric Vehicles - A Comparative Analysis. 5

Coil Optimization using Metaheuristic Techniques for Wireles...

引用

5th International Conference on Power and Energy Technology, ICPET 2023

作者： Imtiaz, Tabish Elsanabary, Ahmed Mekhilef, Saad Mubin, Marizan Binti Soon, Tey Kok Aziz, Nur Fadilah Ab Universiti Malaya Department of Electrical Engineering Kuala Lumpur Malaysia Universiti Tenaga Nasional Institute of Power Engineering Selangor Kajang Malaysia Swinburne University of Technology School of Science Computing and Engineering Technologies Melbourne Australia Universiti Malaya Department of Computer System & Technology Kuala Lumpur Malaysia Universiti Tenaga Nasional Department of Electrical & Electronic Engineering Selangor Malaysia

ISBN: (纸本)9798350339673

Wireless Power Transfer (WPT) used for charging of electric vehicles (EVs), suffers from the problem of misalignment. In this paper metaheuristic optimizing techniques are used to increase the misalignment tolerance of the receiver coil. This is done by optimizing the length of each turn of the transmitter coil such that a uniform magnetic field density is produced over the charging area, which is kept 26% higher than the transmitting coil area which further aids to accommodate misalignment of the receiver coil. Differential Evolution (DE), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) optimization algorithms are used to obtain the lengths of all the turns of the transmitter coil. These algorithms are also compared by varying the number of turns while keeping the number of iterations to a fixed value. © 2023 IEEE.

关键词： ABC Coil DE Misalignment Opti-mization PSO Wireless Power Transfer

来源：评论

学校读者我要写书评

暂无评论

quantum Polynomial Hierarchies: Karp-Lipton, error reduction, and lower bounds

arXiv

引用

arXiv 2024年

作者： Agarwal, Avantika Gharibian, Sevag Koppula, Venkata Rudolph, Dorian David R. Cheriton School of Computer Science Institute for Quantum Computing University of Waterloo Canada Paderborn University Germany Department of Computer Science and Engineering Indian Institute of Technology Delhi India

The Polynomial-Time Hierarchy (PH) is a staple of classical complexity theory, with applications spanning randomized computation to circuit lower bounds to "quantum advantage" analyses for near-term quantum computers. quantumly, however, despite the fact that at least four definitions of quantum PH exist, it has been challenging to prove analogues for these of even basic facts from PH. This work studies three quantum-verifier based generalizations of PH, two of which are from [Gharibian, Santha, Sikora, Sundaram, Yirka, 2022] and use classical strings (QCPH) and quantum mixed states (QPH) as proofs, and one of which is new to this work, utilizing quantum pure states (pureQPH) as proofs. We first resolve several open problems from [GSSSY22], including a collapse theorem and a Karp-Lipton theorem for QCPH. Then, for our new class pureQPH, we show one-sided error reduction pureQPH, as well as the first bounds relating these quantum variants of PH, namely QCPH ⊆ pureQPH ⊆ EXPPP. © 2024, CC BY.

关键词： Polynomial approximation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：