Results 31 to 40 of about 283,757 (265)

Quantum-Enhanced Machine Learning [PDF]

open access: yesPhysical Review Letters, 2016
5+15 pages. This paper builds upon and mostly supersedes arXiv:1507.08482. In addition to results provided in this previous work, here we achieve learning improvements in more general environments, and provide connections to other work in quantum machine learning. Explicit constructions of oracularized environments given in arXiv:1507.08482 are omitted
Dunjko, Vedran   +2 more
openaire   +3 more sources

Quantum machine learning: a classical perspective [PDF]

open access: yes, 2018
Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning techniques to impressive results in regression, classification, data-generation and reinforcement learning tasks.
Ben-David S   +15 more
core   +2 more sources

Basic protocols in quantum reinforcement learning with superconducting circuits [PDF]

open access: yes, 2017
Superconducting circuit technologies have recently achieved quantum protocols involving closed feedback loops. Quantum artificial intelligence and quantum machine learning are emerging fields inside quantum technologies which may enable quantum devices ...
Lamata, Lucas
core   +4 more sources

PENGEMBANGAN MULTIMEDIA PEMBELAJARAN AKUNTANSI PAJAK DENGAN PENDEKATAN QUANTUM LEARNING DI SMK

open access: yesJurnal Inovasi Teknologi Pendidikan, 2016
Penelitian ini bertujuan untuk: (1) menghasilkan produk multimedia pembelajaran akuntansi pajak dengan pendekatan quantum learning, (2) mengungkapkan kualitas kelayakan multimedia pembelajaran akuntansi pajak, (3) mengungkapkan keefektivan multimedia ...
Fitria Yuniarti, Herminarto Sofyan
doaj   +1 more source

Peningkatan Kemampuan Menulis Melalui Model Quantum Learning dengan Teknik Tandur pada Siswa Kelas IV SDN 1 Manggar

open access: yesJurnal Educatio FKIP UNMA, 2021
Penelitian ini bertujuan untuk meningkatkan kemampuan menulis melalui model quantum learning dengan teknik TANDUR pada siswa kelas IV SDN 1 Manggar Sluke Rembang Tahun Pelajaran 2020/2021.
Tri Wahyu Werdiningtyas
doaj   +1 more source

Pengaruh Model Pembelajaran Quantum Learning Dengan Media Piranti Lunak Presentasi Terhadap Hasil Belajar Pada Materi Perkalian Bilangan Bulat Di Kelas V SDN 5 Simpangkatis

open access: yesInovasi Matematika, 2019
Penelitian ini tentang Pengaruh Model Pembelajaran Quantum Learning dengan Media Piranti Lunak Presentasi Terhadap Hasil Belajar Pada Materi Perkalian Bilangan Bulat di Kelas V SDN 5 Simpangkatis yang bertujuan untuk mengetahui ada atau tidaknya pengaruh
Yessy Andiani   +2 more
doaj   +1 more source

PENGARUH MODEL QUANTUM LEARNING TERHADAP HASIL BELAJAR SISWA KELAS V DI SD NEGERI 060970

open access: yesJurnal Educatio FKIP UNMA, 2020
Populasi dalam penelitian ini adalah seluruh siswa SD Negeri 060970 belawan. Sampel penelitian terdiri dari dua kelas yaitu Kelas V A yang berjumlah 40 siswa( sebagai kelas eksperimen) dan kelas V B berjumlah 40 siswa (sebagai kelas kontrol).
Diana Simanjuntak   +3 more
doaj   +1 more source

Quantum Statistical Learning via Quantum Wasserstein Natural Gradient [PDF]

open access: yesJournal of Statistical Physics, 2021
AbstractIn this article, we introduce a new approach towards the statistical learning problem $$\mathrm{argmin}_{\rho (\theta ) \in {\mathcal {P}}_{\theta }} W_{Q}^2 (\rho _{\star },\rho (\theta ))$$ argmin ρ
Becker, Simon, Li, Wuchen
openaire   +6 more sources

Quantum deep learning

open access: yesQuantum Information and Computation, 2016
In recent years, deep learning has had a profound impact on machine learning and artificial intelligence. At the same time, algorithms for quantum computers have been shown to efficiently solve some problems that are intractable on conventional, classical computers.
Wiebe, Nathan   +2 more
openaire   +2 more sources

Quantum self-supervised learning

open access: yesQuantum Science and Technology, 2022
AbstractThe resurgence of self-supervised learning, whereby a deep learning model generates its own supervisory signal from the data, promises a scalable way to tackle the dramatically increasing size of real-world data sets without human annotation.
Jaderberg, B   +5 more
openaire   +2 more sources

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