activity
20182024
most citedOn the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks

21 citations · 66 across the 4 of their papers we have counts for

collaborators

9 papers

eess.IV2024

Remote Sensing Data Assimilation with a Chained Hydrologic-hydraulic Model for Flood Forecasting

Thanh Huy Nguyen, Andrea Piacentini, Sophie Ricci +4

A chained hydrologic-hydraulic model is implemented using predicted runoff from a large-scale hydrologic model (namely ISBA-CTRIP) as inputs to local hydrodynamic models (TELEMAC-2…

cs.CV202019 cited

Super-Resolution-based Snake Model -- An Unsupervised Method for Large-Scale Building Extraction using Airborne LiDAR Data and Optical Image

Thanh Huy Nguyen, Sylvie Daniel, Didier Gueriot +2

Automatic extraction of buildings in urban and residential scenes has become a subject of growing interest in the domain of photogrammetry and remote sensing, particularly since mi…

stat.ML201921 cited

On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks

Umut Şimşekli, Mert Gürbüzbalaban, Thanh Huy Nguyen +2

The gradient noise (GN) in the stochastic gradient descent (SGD) algorithm is often considered to be Gaussian in the large data regime by assuming that the \emph{classical} central…

eess.IV2019

Coarse-to-Fine Registration of Airborne LiDAR Data and Optical Imagery on Urban Scenes

Thanh Huy Nguyen, Sylvie Daniel, Didier Gueriot +2

Applications based on synergistic integration of optical imagery and LiDAR data are receiving a growing interest from the remote sensing community. However, a misaligned integratio…

cs.CV2019

Unsupervised Automatic Building Extraction Using Active Contour Model on Unregistered Optical Imagery and Airborne LiDAR Data

Thanh Huy Nguyen, Sylvie Daniel, Didier Gueriot +2

Automatic extraction of buildings in urban scenes has become a subject of growing interest in the domain of photogrammetry and remote sensing, particularly with the emergence of Li…

stat.ML201911 cited

First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise

Thanh Huy Nguyen, Umut Şimşekli, Mert Gürbüzbalaban +1

Stochastic gradient descent (SGD) has been widely used in machine learning due to its computational efficiency and favorable generalization properties. Recently, it has been empiri…