Fetching the paper…
Reading the bibliography…
Fault-tolerant quantum computers offer the promise of dramatically improving machine learning through speed-ups in computation or improved model scalability.
Learning to learn with quantum neural networks via classical neural networks, 2019
G. Verdon, M. Broughton, J. R. McClean, K. J. Sung, R. Babbush, Z. Jiang, H. Neven, and M. Mohseni · 1907
Earlier work this paper cites.
The capacity of quantum neural networks, 2019
L. G. Wright and P. L. McMahon · 1908
Earlier work this paper cites.
Information-theoretic local minima characterization and regularization, 2019
Z. Jia and H. Su · 1911
Earlier work this paper cites.
Finite-Dimensional Vector Spaces
P. Halmos · 1958
Earlier work this paper cites.
On the uniform convergence of relative frequencies of events to their probabilities
V. N. Vapnik and A. Y. Chervonenkis · 1971
Earlier work this paper cites.
Exact calculation of the Hessian matrix for the multilayer perceptron, 1992
C. Bishop · 1992
Earlier work this paper cites.
Measuring the VC-dimension of a learning machine
V. Vapnik, E. Levin, and Y. L. Cun · 1994
Earlier work this paper cites.
Fisher information and stochastic complexity
J. J. Rissanen · 1996
Earlier work this paper cites.
VC dimension of neural networks
E. D. Sontag · 1998
Earlier work this paper cites.
Natural gradient works efficiently in learning
S.-I. Amari · 1998
Earlier work this paper cites.
The Nature of Statistical Learning Theory
V. Vapnik · 2000
Earlier work this paper cites.
A scale-dependent notion of effective dimension, 2020
O. Berezniuk, A. Figalli, R. Ghigliazza, and K. Musaelian · 2001
Earlier work this paper cites.
Cost-function-dependent barren plateaus in shallow quantum neural networks, 2020
M. Cerezo, A. Sone, T. Volkoff, L. Cincio, and P. J. Coles · 2001
Earlier work this paper cites.
Quantum embeddings for machine learning, 2020
S. Lloyd, M. Schuld, A. Ijaz, J. Izaac, and N. Killoran · 2001
Earlier work this paper cites.
Science from Fisher Information: A Unification
B. R. Frieden · 2004
Earlier work this paper cites.
Large gradients via correlation in random parameterized quantum circuits, 2020
T. Volkoff and P. J. Coles · 2005
Earlier work this paper cites.
Elements of Information Theory
T. M. Cover and J. A. Thomas · 2006
Earlier work this paper cites.
Layerwise learning for quantum neural networks, 2020
A. Skolik, J. R. McClean, M. Mohseni, P. van der Smagt, and M. Leib · 2006
Earlier work this paper cites.
Noise-induced barren plateaus in variational quantum algorithms
S. Wang, E. Fontana, M. Cerezo, K. Sharma, A. Sone, L. Cincio, and P. J. Coles · 2007
Earlier work this paper cites.
The minimum description length principle
P. D. Grünwald · 2007
Cited alongside, same era.
Characterizing the loss landscape of variational quantum circuits, 2020
P. Huembeli and A. Dauphin · 2008
Cited alongside, same era.
Impact of barren plateaus on the Hessian and higher order derivatives, 2020
M. Cerezo and P. J. Coles · 2008
Cited alongside, same era.
M. Schuld, R. Sweke, and J. J. Meyer · 2008
Cited alongside, same era.
Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
Cited alongside, same era.
Stronger generalization bounds for deep nets via a compression approach, 2018
S. Arora, R. Ge, B. Neyshabur, and Y. Zhang · 2018
Later among the works it cites.
Barren plateaus in quantum neural network training landscapes
J. R. McClean, S. Boixo, V. N. Smelyanskiy, R. Babbush, and H. Neven · 2018
Later among the works it cites.
Lipschitz regularity of deep neural networks: analysis and efficient estimation
A. Virmaux and K. Scaman · 2018
Later among the works it cites.
The spectrum of the Fisher information matrix of a single-hidden-layer neural network
J. Pennington and P. Worah · 2018
Later among the works it cites.
Approximate fisher information matrix to characterise the training of deep neural networks
Z. Liao, T. Drummond, I. Reid, and G. Carneiro · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Efficient BackProp
Y. A. LeCun, L. Bottou, G. B. Orr, and K.-R. Müller · 2012
Cited alongside, same era.
The quest for a quantum neural network
M. Schuld, I. Sinayskiy, and F. Petruccione · 2014
Cited alongside, same era.
Read the fine print
S. Aaronson · 2015
Cited alongside, same era.
Path-sgd: Path-normalized optimization in deep neural networks
B. Neyshabur, R. R. Salakhutdinov, and N. Srebro · 2015
Cited alongside, same era.
Norm-based capacity control in neural networks
B. Neyshabur, R. Tomioka, and N. Srebro · 2015
Cited alongside, same era.
Deep Learning
I. Goodfellow, Y. Bengio, and A. Courville · 2016
Cited alongside, same era.
G. K. Dziugaite and D. M. Roy · 2017
Cited alongside, same era.
M. Mohri, A. Rostamizadeh, and A. Talwalkar · 2018
Later among the works it cites.
The capacity of feedforward neural networks
P. Baldi and R. Vershynin · 2019
Later among the works it cites.
Quantum generative adversarial networks for learning and loading random distributions
C. Zoufal, A. Lucchi, and S. Woerner · 2019
Later among the works it cites.
Continuous-variable quantum neural networks
N. Killoran, T. R. Bromley, J. M. Arrazola, M. Schuld, N. Quesada, and S. Lloyd · 2019
Later among the works it cites.
Limitations of the empirical Fisher approximation for natural gradient descent
F. Kunstner, P. Hennig, and L. Balles · 2019
Later among the works it cites.
Universal statistics of Fisher information in deep neural networks: Mean field approach
R. Karakida, S. Akaho, and S.-I. Amari · 2019
Later among the works it cites.
Quantum convolutional neural networks
I. Cong, S. Choi, and M. D. Lukin · 2019
Later among the works it cites.
Supervised learning with quantum-enhanced feature spaces
V. Havlíček, A. D. Córcoles, K. Temme, A. W. Harrow, A. Kandala, J. M. Chow, and J. M. Gambetta · 2019
Later among the works it cites.
Expressibility and entangling capability of parameterized quantum circuits for hybrid quantum-classical algorithms
S. Sim, P. D. Johnson, and A. Aspuru-Guzik · 2019
Later among the works it cites.
Fisher-Rao metric, geometry, and complexity of neural networks
T. Liang, T. Poggio, A. Rakhlin, and J. Stokes · 2019
Later among the works it cites.
Qiskit: An open-source framework for quantum computing, 2019
H. Abraham et al · 2019
Later among the works it cites.
Circuit-centric quantum classifiers
M. Schuld, A. Bocharov, K. M. Svore, and N. Wiebe · 2020
Closest in time.
Stochastic gradient descent for hybrid quantum-classical optimization
R. Sweke, F. Wilde, J. J. Meyer, M. Schuld, P. K. Fährmann, B. Meynard-Piganeau, and J. Eisert · 2020
Closest in time.
Quantum autoencoders for efficient compression of quantum data
J. Romero, J. P. Olson, and A. Aspuru-Guzik · 2058
Closest in time.