no code implementations • 1 Apr 2024 • Tsuyoshi Idé, Dzung T. Phan, Rudy Raymond
This paper presents two methodological advancements in decentralized multi-task learning under privacy constraints, aiming to pave the way for future developments in next-generation Blockchain platforms.
no code implementations • 3 Jul 2023 • Yaswitha Gujju, Atsushi Matsuo, Rudy Raymond
The past decade has witnessed significant advancements in quantum hardware, encompassing improvements in speed, qubit quantity, and quantum volume-a metric defining the maximum size of a quantum circuit effectively implementable on near-term quantum devices.
no code implementations • 23 Aug 2022 • Tsuyoshi Idé, Rudy Raymond
We discuss future directions of Blockchain as a collaborative value co-creation platform, in which network participants can gain extra insights that cannot be accessed when disconnected from the others.
1 code implementation • 17 Jun 2021 • Napat Thumwanit, Chayaphol Lortaraprasert, Hiroshi Yano, Rudy Raymond
Quantum classifiers provide sophisticated embeddings of input data in Hilbert space promising quantum advantage.
1 code implementation • 25 Jan 2021 • Bo Yang, Rudy Raymond, Hiroshi Imai, Hyungseok Chang, Hidefumi Hiraishi
We are able to show violations of the inequalities on various graph states by constructing low-depth quantum circuits producing them, and by applying the readout error mitigation technique.
Quantum Physics
2 code implementations • 4 Sep 2020 • Lukas Burgholzer, Rudy Raymond, Robert Wille
In this paper, we propose an efficient scheme for quantum circuit equivalence checking---specialized for verifying results of the IBM Qiskit quantum circuit compilation flow.
Quantum Circuit Equivalence Checking Quantum Physics
no code implementations • 26 Apr 2018 • Taro Sekiyama, Takashi Imamichi, Haruki Imai, Rudy Raymond
We address this challenge by developing a novel profile-guided memory optimization to efficiently and quickly allocate memory blocks during the propagation in DNNs.
no code implementations • 17 Dec 2017 • Rudy Raymond, Takayuki Osogami, Sakyasingha Dasgupta
Gaussian DyBM is a DyBM that assumes the predicted data is generated by a Gaussian distribution whose first-order moment (mean) dynamically changes over time but its second-order moment (variance) is fixed.
no code implementations • 6 Jun 2016 • Yuko Hada-Muranushi, Takayuki Muranushi, Ayumi Asai, Daisuke Okanohara, Rudy Raymond, Gentaro Watanabe, Shigeru Nemoto, Kazunari Shibata
Automated forecasts serve important role in space weather science, by providing statistical insights to flare-trigger mechanisms, and by enabling tailor-made forecasts and high-frequency forecasts.