Samuel L. Smith
According to our database1,
Samuel L. Smith
authored at least 28 papers
between 2016 and 2024.
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Bibliography
2024
CoRR, 2024
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.
CoRR, 2024
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
CoRR, 2023
CoRR, 2023
Proceedings of the International Conference on Machine Learning, 2023
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
CoRR, 2022
2021
Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error.
CoRR, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Characterizing signal propagation to close the performance gap in unnormalized ResNets.
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study.
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
CoRR, 2018
Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks.
Proceedings of the 6th International Conference on Learning Representations, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
2017
Proceedings of the 5th International Conference on Learning Representations, 2017
2016