Kevin Scaman
According to our database1,
Kevin Scaman
authored at least 33 papers
between 2014 and 2024.
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Bibliography
2024
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
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
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
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
Proceedings of the International Conference on Machine Learning, 2022
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
Proceedings of the IEEE International Conference on Acoustics, 2021
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
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
2019
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
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
2017
CoRR, 2017
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017
2016
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
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