Alberto Bietti

According to our database1, Alberto Bietti authored at least 39 papers between 2015 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Level Set Teleportation: An Optimization Perspective.
CoRR, 2024

Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models.
CoRR, 2024

Learning Associative Memories with Gradient Descent.
CoRR, 2024

2023
On Learning Gaussian Multi-index Models with Gradient Flow.
CoRR, 2023

AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models.
CoRR, 2023

Multiple Physics Pretraining for Physical Surrogate Models.
CoRR, 2023

xVal: A Continuous Number Encoding for Large Language Models.
CoRR, 2023

Scaling Laws for Associative Memories.
CoRR, 2023

Birth of a Transformer: A Memory Viewpoint.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The SSL Interplay: Augmentations, Inductive Bias, and Generalization.
Proceedings of the International Conference on Machine Learning, 2023

On Minimal Variations for Unsupervised Representation Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes.
CoRR, 2022

Efficient Kernel UCB for Contextual Bandits.
CoRR, 2022

Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization.
CoRR, 2022

When does return-conditioned supervised learning work for offline reinforcement learning?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning single-index models with shallow neural networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Personalization Improves Privacy-Accuracy Tradeoffs in Federated Learning.
Proceedings of the International Conference on Machine Learning, 2022

Approximation and Learning with Deep Convolutional Models: a Kernel Perspective.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient Kernelized UCB for Contextual Bandits.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
A Contextual Bandit Bake-off.
J. Mach. Learn. Res., 2021

Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks.
CoRR, 2021

On the Sample Complexity of Learning with Geometric Stability.
CoRR, 2021

On Approximation in Deep Convolutional Networks: a Kernel Perspective.
CoRR, 2021

On the Universality of Graph Neural Networks on Large Random Graphs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Sample Complexity of Learning under Geometric Stability.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Energy-Based Models with Overparametrized Shallow Neural Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Deep Equals Shallow for ReLU Networks in Kernel Regimes.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions.
CoRR, 2020

Convergence and Stability of Graph Convolutional Networks on Large Random Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Foundations of deep convolutional models through kernel methods. (Méthodes à noyaux pour les réseaux convolutionnels profonds).
PhD thesis, 2019

Group Invariance, Stability to Deformations, and Complexity of Deep Convolutional Representations.
J. Mach. Learn. Res., 2019

On the Inductive Bias of Neural Tangent Kernels.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Kernel Perspective for Regularizing Deep Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
On Regularization and Robustness of Deep Neural Networks.
CoRR, 2018

Practical Evaluation and Optimization of Contextual Bandit Algorithms.
CoRR, 2018

2017
Group Invariance and Stability to Deformations of Deep Convolutional Representations.
CoRR, 2017

Invariance and Stability of Deep Convolutional Representations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2015
An online EM algorithm in hidden (semi-)Markov models for audio segmentation and clustering.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015


  Loading...