Search Results for author: Elisa Riccietti

Found 9 papers, 3 papers with code

A path-norm toolkit for modern networks: consequences, promises and challenges

1 code implementation2 Oct 2023 Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval

The versatility of the toolkit and its ease of implementation allow us to challenge the concrete promises of path-norm-based generalization bounds, by numerically evaluating the sharpest known bounds for ResNets on ImageNet.

Generalization Bounds

Does a sparse ReLU network training problem always admit an optimum?

no code implementations5 Jun 2023 Quoc-Tung Le, Elisa Riccietti, Rémi Gribonval

Then, the existence of a global optimum is proved for every concrete optimization problem involving a shallow sparse ReLU neural network of output dimension one.

Network Pruning

A Block-Coordinate Approach of Multi-level Optimization with an Application to Physics-Informed Neural Networks

no code implementations23 May 2023 Serge Gratton, Valentin Mercier, Elisa Riccietti, Philippe L. Toint

Multi-level methods are widely used for the solution of large-scale problems, because of their computational advantages and exploitation of the complementarity between the involved sub-problems.

Self-supervised learning with rotation-invariant kernels

1 code implementation28 Jul 2022 Léon Zheng, Gilles Puy, Elisa Riccietti, Patrick Pérez, Rémi Gribonval

We introduce a regularization loss based on kernel mean embeddings with rotation-invariant kernels on the hypersphere (also known as dot-product kernels) for self-supervised learning of image representations.

Self-Supervised Learning

Approximation speed of quantized vs. unquantized ReLU neural networks and beyond

no code implementations24 May 2022 Antoine Gonon, Nicolas Brisebarre, Rémi Gribonval, Elisa Riccietti

This is achieved using a new lower-bound on the Lipschitz constant of the map that associates the parameters of ReLU networks to their realization, and an upper-bound generalizing classical results.

Quantization

Identifiability in Two-Layer Sparse Matrix Factorization

no code implementations4 Oct 2021 Léon Zheng, Elisa Riccietti, Rémi Gribonval

In particular, in the case of fixed-support sparse matrix factorization, we give a general sufficient condition for identifiability based on rank-one matrix completability, and we derive from it a completion algorithm that can verify if this sufficient condition is satisfied, and recover the entries in the two sparse factors if this is the case.

Vocal Bursts Valence Prediction

Efficient Identification of Butterfly Sparse Matrix Factorizations

1 code implementation4 Oct 2021 Léon Zheng, Elisa Riccietti, Rémi Gribonval

Our main contribution is to prove that any $N \times N$ matrix having the so-called butterfly structure admits an essentially unique factorization into $J$ butterfly factors (where $N = 2^{J}$), and that the factors can be recovered by a hierarchical factorization method, which consists in recursively factorizing the considered matrix into two factors.

Multilevel physics informed neural networks (MPINNs)

no code implementations29 Sep 2021 Elisa Riccietti, Valentin Mercier, Serge Gratton, Pierre Boudier

In this paper we introduce multilevel physics informed neural networks (MPINNs).

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