Kevin Scaman
23 papers · 2014–2025 · 7 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 6 separate collaboration groups - the largest holds only 39% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Kevin Scaman?
4 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Ludovic DOS SANTOS, Aladin Virmaux, Cedric Malherbe
8 papers
· 2018–2022
· NeurIPS, ICML, IJCAI
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Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness
ICML 2022
Robustness in Multi-Objective Submodular Optimization: a Quantile Approach
ICML 2022
Lipschitz normalization for self-attention layers with application to graph neural networks
ICML 2021
A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration
NeurIPS 2020
Coloring Graph Neural Networks for Node Disambiguation
IJCAI 2020
Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations
NeurIPS 2020
Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning
NeurIPS 2019
Lipschitz regularity of deep neural networks: analysis and efficient estimation
NeurIPS 2018