Training neural networks for and by interpolation

Training neural networks for and by interpolation

In modern supervised learning, many deep neural networks are able to interpolate the data: the empirical loss can be driven to near zero on all samples simultaneously. In this work, we explicitly exploit this interpolation property for the design of a new optimization algorithm for deep learning, wh...

Descrizione completa

Dettagli Bibliografici
Autori principali:	Berrada, L, Zisserman, A, Kumar, MP
Natura:	Conference item
Lingua:	English
Pubblicazione:	Journal of Machine Learning Research 2020

Documenti analoghi

Deep Frank-Wolfe for neural network optimization
di: Berrada, L, et al.
Pubblicazione: (2018)

Deep Frank-Wolfe for neural network optimization
di: Berrada, L, et al.
Pubblicazione: (2019)

Smooth loss functions for deep top-k classification
di: Berrada, L, et al.
Pubblicazione: (2018)

Smooth loss functions for deep top-k classification
di: Berrada, L, et al.
Pubblicazione: (2018)

Trusting SVM for piecewise linear CNNs
di: Berrada, L, et al.
Pubblicazione: (2016)

Trusting SVM for piecewise linear CNNs
di: Berrada, L, et al.
Pubblicazione: (2017)

Kilonova light-curve interpolation with neural networks
di: Yinglei Peng, et al.
Pubblicazione: (2024-07-01)

An Importance Sampling Method for Generating Optimal Interpolation Points in Training Physics-Informed Neural Networks
di: Hui Li, et al.
Pubblicazione: (2025-01-01)

Image Interpolation Based on Spiking Neural Network Model
di: Mürsel Ozan İncetaş
Pubblicazione: (2023-02-01)

Discrete Orthogonal Transforms and Neural Networks for Image Interpolation
di: J. Polec, et al.
Pubblicazione: (1999-09-01)

Interpolating convolutional neural networks using batch normalization
di: Data, G, et al.
Pubblicazione: (2018)

Interpolation for Neural Network Operators Activated by Smooth Ramp Functions
di: Fesal Baxhaku, et al.
Pubblicazione: (2024-07-01)

Pontryagin Neural Networks with Functional Interpolation for Optimal Intercept Problems
di: Andrea D’Ambrosio, et al.
Pubblicazione: (2021-04-01)

Artificial Neural Network (ANN) Based Empirical Interpolation of Precipitation
di: Rajesh Joshi
Pubblicazione: (2016-12-01)

On the choice of interpolation scheme for neural CDEs
di: Morrill, J, et al.
Pubblicazione: (2022)

Treatment of outliers via interpolation method with neural network forecast performances
di: Wahir, N. A., et al.
Pubblicazione: (2017)

Comparison of DEM Super-Resolution Methods Based on Interpolation and Neural Networks
di: Yifan Zhang, et al.
Pubblicazione: (2022-01-01)

Application of two-component neural network for exchange-correlation functional interpolation
di: Alexander Ryabov, et al.
Pubblicazione: (2022-08-01)

Sparse self-attention aggregation networks for neural sequence slice interpolation
di: Zejin Wang, et al.
Pubblicazione: (2021-02-01)

Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators
di: George A Anastassiou
Pubblicazione: (2012-10-01)

Interpolative Boolean Networks
di: Vladimir Dobrić, et al.
Pubblicazione: (2017-01-01)

Interpolation for neural-network operators activated with a generalized logistic-type function
di: Hande Uyan, et al.
Pubblicazione: (2024-09-01)

Recurrent Neural Network-Based Approach for Sparse Geomagnetic Data Interpolation and Reconstruction
di: Huan Liu, et al.
Pubblicazione: (2019-01-01)

Medical Image Interpolation Using Recurrent Type-2 Fuzzy Neural Network
di: Jafar Tavoosi, et al.
Pubblicazione: (2021-09-01)

Interpolation : cubic spline interpolation and hermite interpolation /
di: 495552 Gan, Loon Keat, et al.
Pubblicazione: (2004)

Alternative method: outlier treatments with box-jenkins and neural network via interpolation method
di: Wahir, Norsoraya Azurin, et al.
Pubblicazione: (2018)

Alternative method outlier treatments with Box-Jenkins and neural network via interpolation method
di: Wahir, Norsoraya Azurin, et al.
Pubblicazione: (2018)

Balancing Wigner sampling and geometry interpolation for deep neural networks learning photochemical reactions
di: Li Wang, et al.
Pubblicazione: (2023-12-01)

Physics-Informed Neural Networks and Functional Interpolation for Solving the Matrix Differential Riccati Equation
di: Kristofer Drozd, et al.
Pubblicazione: (2023-08-01)

A generalized spatial autoregressive neural network method for three-dimensional spatial interpolation
di: J. Zhan, et al.
Pubblicazione: (2023-05-01)

NEURAL NETWORK INTERPOLATION PARAMETERS OF A MULTI-MODE DYNAMIC MODEL OF THE AIRCRAFT ENGINE
di: Aleksandr Tamargazin, et al.
Pubblicazione: (2020-08-01)

EXPLORING THE ROLE OF GENETIC ALGORITHMS AND ARTIFICIAL NEURAL NETWORKS FOR INTERPOLATION OF ELEVATION IN GEOINFORMATION MODELS
di: H. Bagheri, et al.
Pubblicazione: (2013-09-01)

Spatial Interpolation of Rainfall Erosivity Using Artificial Neural Networks for Southern Brazil Conditions
di: Michel Castro Moreira, et al.

Surface Roughness Prediction Using Circular Interpolation Based on Artificial Neural Network in Milling Operation
di: Maan Aabid Tawfiq, et al.
Pubblicazione: (2016-05-01)

Neural Hierarchical Interpolation for Standardized Precipitation Index Forecasting
di: Rafael Magallanes-Quintanar, et al.
Pubblicazione: (2024-07-01)

Video frame interpolation neural network for 3D tomography across different length scales
di: Laura Gambini, et al.
Pubblicazione: (2024-09-01)

Recording of Full-Color Snapshot Digital Holographic Portraits Using Neural Network Image Interpolation
di: Philippe Gentet, et al.
Pubblicazione: (2023-11-01)

Deep image retrieval using artificial neural network interpolation and indexing based on similarity measurement
di: Faiyaz Ahmad
Pubblicazione: (2022-06-01)

Enlarging smaller images before inputting into convolutional neural network: zero-padding vs. interpolation
di: Mahdi Hashemi
Pubblicazione: (2019-11-01)

Analysis and Application of Wind Speed Interpolation in Wind Farm Based on BP Neural Network Method
di: ZHENG Kan, et al.
Pubblicazione: (2021-03-01)