Kevin Scaman

According to our database1, Kevin Scaman authored at least 28 papers between 2014 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
Generalization Error of First-Order Methods for Statistical Learning with Generic Oracles.
CoRR, 2023

Breaking the Log Barrier: a Novel Universal Restart Strategy for Faster Las Vegas Algorithms.
CoRR, 2023

2022
Convergence beyond the over-parameterized regime using Rayleigh quotients.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Sample Optimality in Personalized Collaborative and Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Periodic signal recovery with regularized sine neural networks.
Proceedings of the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 2022

Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness.
Proceedings of the International Conference on Machine Learning, 2022

Robustness in Multi-Objective Submodular Optimization: a Quantile Approach.
Proceedings of the International Conference on Machine Learning, 2022

2021
Improving Hierarchical Adversarial Robustness of Deep Neural Networks.
CoRR, 2021

Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Lipschitz normalization for self-attention layers with application to graph neural networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Ego-Based Entropy Measures for Structural Representations on Graphs.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Ego-based Entropy Measures for Structural Representations.
CoRR, 2020

A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Coloring Graph Neural Networks for Node Disambiguation.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Optimal Convergence Rates for Convex Distributed Optimization in Networks.
J. Mach. Learn. Res., 2019

Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

KONG: Kernels for ordered-neighborhood graphs.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
A Spectral Method for Activity Shaping in Continuous-Time Information Cascades.
CoRR, 2017

Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Multivariate Hawkes Processes for Large-Scale Inference.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Suppressing Epidemics in Networks Using Priority Planning.
IEEE Trans. Netw. Sci. Eng., 2016

2015
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

A Greedy Approach for Dynamic Control of Diffusion Processes in Networks.
Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015

2014
What Makes a Good Plan? An Efficient Planning Approach to Control Diffusion Processes in Networks.
CoRR, 2014

Tight Bounds for Influence in Diffusion Networks and Application to Bond Percolation and Epidemiology.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014


  Loading...