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Quantum machine learning has received significant attention in recent years, and promising progress has been made in the development of quantum algorithms to speed up traditional machine learning tasks.
“ ϵ \epsilon -entropy and ϵ \epsilon -capacity of Sets in Functional Spaces”
Andrey˜N. Kolmogorov and Vladimir˜M. Tihomirov · 1961
Earlier work this paper cites.
“The Sizes of Compact Subsets of Hilbert Space and Continuity of Gaussian Processes”
Richard˜M. Dudley · 1967
Earlier work this paper cites.
“Gaussian Random Processes and Measures of Solid Angles in Hilbert Space”
Vladimir˜N. Sudakov · 1971
Earlier work this paper cites.
“A Theory of the Learnable”
L.˜G. Valiant · 1972
Earlier work this paper cites.
“Quantum Theory of Open Systems”
Edward˜B. Davies · 1976
Earlier work this paper cites.
“Estimation of Dependences Based on Empirical Data”
Vladimir˜N. Vapnik · 1982
Earlier work this paper cites.
“Convergence of Stochastic Processes”
D. Pollard · 1984
Earlier work this paper cites.
“Queries and Concept Learning”
Dana Angluin · 1988
Earlier work this paper cites.
“Learnability and the Vapnik-Chervonenkis Dimension”
Anselm Blumer, Andrzej Ehrenfeucht, David Haussler and Manfred˜K. Warmuth · 1989
Earlier work this paper cites.
“Efficient Distribution-free Learning of Probabilistic Concepts”
Michael˜J. Kearns and Robert˜E. Schapire · 1990
Earlier work this paper cites.
“Non Commutative Khintchine and Paley inequalities”
Francoise Lust-Piquard and Gilles Pisier · 1991
Earlier work this paper cites.
“Uniform and Universal Glivenko-Cantelli Classes”
Richard˜M. Dudley, Evarist Gin“’e and Joel Zinn · 1991
Earlier work this paper cites.
“Decision theoretic generalizations of the PAC model for neural net and other learning applications”
David Haussler · 1992
Earlier work this paper cites.
“Principles of Risk Minimization for Learning Theory”
Vladimir˜N. Vapnik · 1992
Earlier work this paper cites.
“Occam’s Razor for Functions”
Balas˜K. Natarajan · 1993
Earlier work this paper cites.
“The Nature of Statistical Learning Theory”
Vladimir˜N. Vapnik · 1995
Earlier work this paper cites.
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Christoph D“”urr and Peter Hyer · 1996
Earlier work this paper cites.
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Earlier work this paper cites.
“Uniform Central Limit Theorems”, Cambridge Studies in Advanced Mathematics 63
Richard˜M. Dudley · 1996
Earlier work this paper cites.
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Peter˜L. Bartlett, Philip˜M. Long and Robert˜C. Williamson · 1996
Earlier work this paper cites.
“Machine Learning”
Tom˜M. Mitchell · 1997
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Lov˜K. Grover · 1997
Earlier work this paper cites.
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Luc Devroye, L“’aszl“’o Gy“:orfi and G“’abor Lugosi · 1997
Earlier work this paper cites.
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Earlier work this paper cites.
“Statistical Learning Theory”
Vladimir˜N. Vapnik · 1998
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
“A Course in Operator Theory”, Graduate Studies in Mathematics (Book 21)
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Earlier work this paper cites.
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Rocco˜A. Servedio and Steven˜J. Gortler · 2001
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Olivier Bousquet, Stephane Boucheron and G“’abor Lugosi · 2003
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“Quantum States and Generalized Observables: A Simple Proof of Gleason’s Theorem”
Paul Busch · 2003
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Gen Kimura · 2003
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Shahar Mendelson and Gideon Schechtman · 2004
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