Sixin Zhang

Orcid: 0000-0002-1021-3638

According to our database1, Sixin Zhang authored at least 21 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
Dataset
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Links

On csauthors.net:

Bibliography

2024
CNN-based Compressor Mass Flow Estimator in Industrial Aircraft Vapor Cycle System.
CoRR, 2024

Large Margin Discriminative Loss for Classification.
CoRR, 2024

Local convergence of min-max algorithms to differentiable equilibrium on Riemannian manifold.
CoRR, 2024

Combining Statistical Depth and Fermat Distance for Uncertainty Quantification.
CoRR, 2024

2022
Transform learning NMF.
Dataset, May, 2022

Leveraging Joint-Diagonalization in Transform-Learning NMF.
IEEE Trans. Signal Process., 2022

Particle gradient descent model for point process generation.
Stat. Comput., 2022

On the Nash equilibrium of moment-matching GANs for stationary Gaussian processes.
Proceedings of the Mathematical and Scientific Machine Learning, 2022

Generalized rectifier wavelet covariance models for texture synthesis.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
On the Relationships between Transform-Learning NMF and Joint-Diagonalization.
CoRR, 2021

2020
On the Identifiability of Transform Learning for Non-Negative Matrix Factorization.
IEEE Signal Process. Lett., 2020

Kymatio: Scattering Transforms in Python.
J. Mach. Learn. Res., 2020

2019
Maximum Entropy Models from Phase Harmonic Covariances.
CoRR, 2019

Statistical learning of geometric characteristics of wireless networks.
Proceedings of the 2019 IEEE Conference on Computer Communications, 2019

2018
Kymatio: Scattering Transforms in Python.
CoRR, 2018

Phase Harmonics and Correlation Invariants in Convolutional Neural Networks.
CoRR, 2018

2016
Distributed Stochastic Optimization for Deep Learning.
PhD thesis, 2016

Distributed stochastic optimization for deep learning (thesis).
CoRR, 2016

2015
Deep learning with Elastic Averaging SGD.
Proceedings of the 3rd International Conference on Learning Representations, 2015

2013
Regularization of Neural Networks using DropConnect.
Proceedings of the 30th International Conference on Machine Learning, 2013

No more pesky learning rates.
Proceedings of the 30th International Conference on Machine Learning, 2013


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