23 citations · 56 across the 14 of their papers we have counts for
14 papers
SOME: Symmetric One-Hot Matching Elector -- A Lightweight Microsecond Decoder for Quantum Error Correction
Xinyi Guo, Geguang Miao, Shinichi Nishizawa +3
Conventional quantum error correction (QEC) decoders such as Minimum-Weight Perfect Matching (MWPM) and Union-Find (UF) offer high thresholds and fast decoding, respectively, but b…
Fast Parameter Optimization of Delayed Feedback Reservoir with Backpropagation and Gradient Descent
Sosei Ikeda, Hiromitsu Awano, Takashi Sato
A delayed feedback reservoir (DFR) is a reservoir computing system well-suited for hardware implementations. However, achieving high accuracy in DFRs depends heavily on selecting a…
Hardware-Friendly Delayed-Feedback Reservoir for Multivariate Time-Series Classification
Sosei Ikeda, Hiromitsu Awano, Takashi Sato
Reservoir computing (RC) is attracting attention as a machine-learning technique for edge computing. In time-series classification tasks, the number of features obtained using a re…
Online Training and Inference System on Edge FPGA Using Delayed Feedback Reservoir
Sosei Ikeda, Hiromitsu Awano, Takashi Sato
A delayed feedback reservoir (DFR) is a hardwarefriendly reservoir computing system. Implementing DFRs in embedded hardware requires efficient online training. However, two main ch…
SPulseGen: Succinct pulse generator architecture maximizing gate fidelity for superconducting quantum computers
Ryosuke Matsuo, Kazuhisa Ogawa, Hidehisa Shiomi +6
This paper proposes a cost-effective architecture for an RF pulse generator for superconducting qubits. Most existing works use arbitrary waveform generators (AWGs) that require bo…
Modular DFR: Digital Delayed Feedback Reservoir Model for Enhancing Design Flexibility
Sosei Ikeda, Hiromitsu Awano, Takashi Sato
A delayed feedback reservoir (DFR) is a type of reservoir computing system well-suited for hardware implementations owing to its simple structure. Most existing DFR implementations…
Adaptive Outlier Detection for Power MOSFETs Based on Gaussian Process Regression
Kyohei Shimozato, Michihiro Shintani, Takashi Sato
Outlier detection of semiconductor devices is important since manufacturing variation is inherently inevitable. In order to properly detect outliers, it is necessary to consider th…
Accelerating Parameter Extraction of Power MOSFET Models Using Automatic Differentiation
Michihiro Shintani, Aoi Ueda, Takashi Sato
The extraction of the model parameters is as important as the development of compact model itself because simulation accuracy is fully determined by the accuracy of the parameters…
Respiratory Rate Estimation Based on WiFi Frame Capture
T. Kanda, T. Sato, H. Awano +2
This paper presents a method that estimates the respiratory rate based on the frame capturing of wireless local area networks. The method uses beamforming feedback matrices (BFMs)…
Virtual Secure Platform: A Five-Stage Pipeline Processor over TFHE
Kotaro Matsuoka, Ryotaro Banno, Naoki Matsumoto +2
We present Virtual Secure Platform (VSP), the first comprehensive platform that implements a multi-opcode general-purpose sequential processor over Fully Homomorphic Encryption (FH…
BUNET: Blind Medical Image Segmentation Based on Secure UNET
Song Bian, Xiaowei Xu, Weiwen Jiang +2
The strict security requirements placed on medical records by various privacy regulations become major obstacles in the age of big data. To ensure efficient machine learning as a s…
ENSEI: Efficient Secure Inference via Frequency-Domain Homomorphic Convolution for Privacy-Preserving Visual Recognition
Song Bian, Tianchen Wang, Masayuki Hiromoto +2
In this work, we propose ENSEI, a secure inference (SI) framework based on the frequency-domain secure convolution (FDSC) protocol for the efficient execution of privacy-preserving…
NASS: Optimizing Secure Inference via Neural Architecture Search
Song Bian, Weiwen Jiang, Qing Lu +2
Due to increasing privacy concerns, neural network (NN) based secure inference (SI) schemes that simultaneously hide the client inputs and server models attract major research inte…
Application of the independent component analysis to the iKAGRA data
KAGRA Collaboration, T. Akutsu, M. Ando +244
We apply the independent component analysis (ICA) to the real data from a gravitational wave detector for the first time. Specifically we use the iKAGRA data taken in April 2016, a…