Quynh Nguyen

According to our database, Quynh Nguyen authored at least 17 papers between 2015 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

On Connectivity of Solutions in Deep Learning: The Role of Over-parameterization and Feature Quality.

Quynh Nguyen, Pierre Bréchet, Marco Mondelli

CoRR, 2021

A Fully Rigorous Proof of the Derivation of Xavier and He's Initialization for Deep ReLU Networks.

Quynh Nguyen

CoRR, 2021

A Note on Connectivity of Sublevel Sets in Deep Learning.

Quynh Nguyen

CoRR, 2021

When Are Solutions Connected in Deep Networks?

Quynh Nguyen, Pierre Bréchet, Marco Mondelli

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks.

Quynh Nguyen, Marco Mondelli, Guido F. Montúfar

Proceedings of the 38th International Conference on Machine Learning, 2021

On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths.

Quynh Nguyen

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology.

Quynh Nguyen, Marco Mondelli

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

On Connected Sublevel Sets in Deep Learning.

Quynh Nguyen

Proceedings of the 36th International Conference on Machine Learning, 2019

On the loss landscape of a class of deep neural networks with no bad local valleys.

Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions.

Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein

Proceedings of the 35th International Conference on Machine Learning, 2018

Optimization Landscape and Expressivity of Deep CNNs.

Quynh Nguyen, Matthias Hein

Proceedings of the 35th International Conference on Machine Learning, 2018

The loss surface and expressivity of deep convolutional neural networks.

Quynh Nguyen, Matthias Hein

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

An Efficient Multilinear Optimization Framework for Hypergraph Matching.

Quynh Nguyen, Francesco Tudisco, Antoine Gautier, Matthias Hein

IEEE Trans. Pattern Anal. Mach. Intell., 2017

The Loss Surface of Deep and Wide Neural Networks.

Quynh Nguyen, Matthias Hein

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods.

Antoine Gautier, Quynh Nguyen, Matthias Hein

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Latent Embeddings for Zero-Shot Classification.

Yongqin Xian, Zeynep Akata, Gaurav Sharma, Quynh Nguyen, Matthias Hein, Bernt Schiele

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

A flexible tensor block coordinate ascent scheme for hypergraph matching.

Quynh Nguyen Ngoc, Antoine Gautier, Matthias Hein

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015