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Stabiliser states are efficiently PAC-learnable
v1v2 (latest)

Stabiliser states are efficiently PAC-learnable

30 April 2017
Andrea Rocchetto
ArXiv (abs)PDFHTML

Papers citing "Stabiliser states are efficiently PAC-learnable"

9 / 9 papers shown
Title
A survey on the complexity of learning quantum states
A survey on the complexity of learning quantum states
Anurag Anshu
Srinivasan Arunachalam
82
74
0
31 May 2023
Learnability of the output distributions of local quantum circuits
Learnability of the output distributions of local quantum circuits
M. Hinsche
M. Ioannou
A. Nietner
J. Haferkamp
Yihui Quek
D. Hangleiter
Jean-Pierre Seifert
Jens Eisert
R. Sweke
64
17
0
11 Oct 2021
On the Hardness of PAC-learning Stabilizer States with Noise
On the Hardness of PAC-learning Stabilizer States with Noise
Aravind Gollakota
Daniel Liang
74
16
0
09 Feb 2021
Quantum statistical query learning
Quantum statistical query learning
Srinivasan Arunachalam
A. Grilo
Henry Yuen
75
32
0
19 Feb 2020
Quantum Boosting
Quantum Boosting
Srinivasan Arunachalam
Reevu Maity
62
26
0
12 Feb 2020
Pseudo-dimension of quantum circuits
Pseudo-dimension of quantum circuits
Matthias C. Caro
Ishaun Datta
74
43
0
04 Feb 2020
Online Learning of Quantum States
Online Learning of Quantum States
S. Aaronson
Xinyi Chen
Elad Hazan
Satyen Kale
A. Nayak
93
91
0
25 Feb 2018
Experimental learning of quantum states
Experimental learning of quantum states
Andrea Rocchetto
Scott Aaronson
Simone Severini
G. Carvacho
D. Poderini
I. Agresti
M. Bentivegna
F. Sciarrino
72
71
0
30 Nov 2017
Machine learning \& artificial intelligence in the quantum domain
Machine learning \& artificial intelligence in the quantum domain
Vedran Dunjko
Hans J. Briegel
76
347
0
08 Sep 2017
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