Sixin Zhang

33 papers A* 4Journal 23Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Feature Representation Transferring to Lightweight Models via Perception Coherence.
Trans. Mach. Learn. Res.
Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang, Reda Chhaibi, Serge Gratton, Thierry Giaccone
2026 J jnl
Training More Robust Classification Model via Discriminative Loss and Gaussian Noise Injection.
Trans. Mach. Learn. Res.
Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang, Reda Chhaibi, Serge Gratton, Thierry Giaccone
2025 J jnl
Convolutional Rectangular Attention Module.
CoRR
Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang, Reda Chhaibi, Serge Gratton, Thierry Giaccone
2025 J jnl
Feature Representation Transferring to Lightweight Models via Perception Coherence.
CoRR
Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang, Reda Chhaibi, Serge Gratton, Thierry Giaccone
2025 J jnl
LSAM: Asynchronous Distributed Training with Landscape-Smoothed Sharpness-Aware Minimization.
CoRR
Yunfei Teng, Sixin Zhang
2025 A* conf
Local convergence of simultaneous min-max algorithms to differential equilibrium on Riemannian manifold.
ICLR
Sixin Zhang
2024 J jnl
CNN-based Compressor Mass Flow Estimator in Industrial Aircraft Vapor Cycle System.
CoRR
Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini
2024 A* conf
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification.
NeurIPS
Hai-Vy Nguyen, Fabrice Gamboa, Reda Chhaibi, Sixin Zhang, Serge Gratton, Thierry Giaccone
2024 J jnl
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification.
CoRR
Hai-Vy Nguyen, Fabrice Gamboa, Reda Chhaibi, Sixin Zhang, Serge Gratton, Thierry Giaccone
2024 J jnl
Large Margin Discriminative Loss for Classification.
CoRR
Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang, Reda Chhaibi, Serge Gratton, Thierry Giaccone
2024 J jnl
Local convergence of min-max algorithms to differentiable equilibrium on Riemannian manifold.
CoRR
Sixin Zhang
2022 J jnl
Generalized Rectifier Wavelet Covariance Models For Texture Synthesis.
CoRR
Antoine Brochard, Sixin Zhang, Stéphane Mallat
2022 A* conf
Generalized rectifier wavelet covariance models for texture synthesis.
ICLR
Antoine Brochard, Sixin Zhang, Stéphane Mallat
2022 J jnl
Leveraging Joint-Diagonalization in Transform-Learning NMF.
IEEE Trans. Signal Process.
Sixin Zhang, Emmanuel Soubies, Cédric Févotte
2022 — conf
On the Nash equilibrium of moment-matching GANs for stationary Gaussian processes.
MSML
Sixin Zhang
2022 J jnl
On the Nash equilibrium of moment-matching GANs for stationary Gaussian processes.
CoRR
Sixin Zhang
2022 J jnl
Particle gradient descent model for point process generation.
Stat. Comput.
Antoine Brochard, Bartlomiej Blaszczyszyn, Sixin Zhang, Stéphane Mallat
2021 J jnl
On the Relationships between Transform-Learning NMF and Joint-Diagonalization.
CoRR
Sixin Zhang, Emmanuel Soubies, Cédric Févotte
2020 J jnl
Kymatio: Scattering Transforms in Python.
J. Mach. Learn. Res.
Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine Cella, Michael Eickenberg
2020 J jnl
On the Identifiability of Transform Learning for Non-Negative Matrix Factorization.
IEEE Signal Process. Lett.
Sixin Zhang, Emmanuel Soubies, Cédric Févotte
2020 J jnl
Particle gradient descent model for point process generation.
CoRR
Antoine Brochard, Bartlomiej Blaszczyszyn, Stéphane Mallat, Sixin Zhang
2019 J jnl
Maximum Entropy Models from Phase Harmonic Covariances.
CoRR
Sixin Zhang, Stéphane Mallat
2019 A* conf
Statistical learning of geometric characteristics of wireless networks.
INFOCOM
Antoine Brochard, Bartlomiej Blaszczyszyn, Stéphane Mallat, Sixin Zhang
2018 J jnl
Kymatio: Scattering Transforms in Python.
CoRR
Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine Cella, Michael Eickenberg
2018 J jnl
Phase Harmonics and Correlation Invariants in Convolutional Neural Networks.
CoRR
Stéphane Mallat, Sixin Zhang, Gaspar Rochette
2018 J jnl
Statistical learning of geometric characteristics of wireless networks.
CoRR
Antoine Brochard, Bartlomiej Blaszczyszyn, Stéphane Mallat, Sixin Zhang
2016 — —
Distributed Stochastic Optimization for Deep Learning.
Sixin Zhang
2016 J jnl
Distributed stochastic optimization for deep learning (thesis).
CoRR
Sixin Zhang
2015 — conf
Deep learning with Elastic Averaging SGD.
NIPS
Sixin Zhang, Anna Choromanska, Yann LeCun
2015 — conf
Deep learning with Elastic Averaging SGD.
ICLR (Workshop)
Sixin Zhang, Anna Choromanska, Yann LeCun
2013 — conf
No more pesky learning rates.
ICML (3)
Tom Schaul, Sixin Zhang, Yann LeCun
2013 — conf
Regularization of Neural Networks using DropConnect.
ICML (3)
Li Wan, Matthew D. Zeiler, Sixin Zhang, Yann LeCun, Rob Fergus
2012 J jnl
No More Pesky Learning Rates
CoRR
Tom Schaul, Sixin Zhang, Yann LeCun