◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Pierre Wolinski

2 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • stat.ML1

identity via Semantic Scholar / OpenAlex

most citedEfficient Neural Networks for Tiny Machine Learning: A Comprehensive Review

7 citations · 7 across the 1 of their papers we have counts for

collaborators

2 papers

stat.ML2023★ 7 cited

Efficient Neural Networks for Tiny Machine Learning: A Comprehensive Review

Minh Tri Lê, Pierre Wolinski, Julyan Arbel

The field of Tiny Machine Learning (TinyML) has gained significant attention due to its potential to enable intelligent applications on resource-constrained devices. This review pr…

cs.LG2018

Learning with Random Learning Rates

Léonard Blier, Pierre Wolinski, Yann Ollivier

Hyperparameter tuning is a bothersome step in the training of deep learning models. One of the most sensitive hyperparameters is the learning rate of the gradient descent. We prese…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.