Daniel Soudry
According to our database1,
Daniel Soudry
authored at least 80 papers
between 2010 and 2024.
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Bibliography
2024
Foldable SuperNets: Scalable Merging of Transformers with Different Initializations and Tasks.
CoRR, 2024
Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes.
CoRR, 2024
How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting - An Analytical Model.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
DropCompute: simple and more robust distributed synchronous training via compute variance reduction.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
The Role of Codeword-to-Class Assignments in Error-Correcting Codes: An Empirical Study.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Proceedings of the International Conference on Machine Learning, 2022
A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Task-Agnostic Continual Learning Using Online Variational Bayes With Fixed-Point Updates.
Neural Comput., 2021
CoRR, 2021
Statistical Testing for Efficient Out of Distribution Detection in Deep Neural Networks.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N: M Transposable Masks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
J. Math. Imaging Vis., 2020
Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming.
CoRR, 2020
Neural gradients are lognormally distributed: understanding sparse and quantized training.
CoRR, 2020
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?
Proceedings of the 37th International Conference on Machine Learning, 2020
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case.
Proceedings of the 8th International Conference on Learning Representations, 2020
At Stability's Edge: How to Adjust Hyperparameters to Preserve Minima Selection in Asynchronous Training of Neural Networks?
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the Conference on Learning Theory, 2020
2019
Mix & Match: training convnets with mixed image sizes for improved accuracy, speed and scale resiliency.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models.
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the Conference on Learning Theory, 2019
Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
Bayesian Gradient Descent: Online Variational Bayes Learning with Increased Robustness to Catastrophic Forgetting and Weight Pruning.
CoRR, 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
Proceedings of the 35th International Conference on Machine Learning, 2018
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
Multi-scale approaches for high-speed imaging and analysis of large neural populations.
PLoS Comput. Biol., 2017
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations.
J. Mach. Learn. Res., 2017
Train longer, generalize better: closing the generalization gap in large batch training of neural networks.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
2016
No bad local minima: Data independent training error guarantees for multilayer neural networks.
CoRR, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the IEEE International Symposium on Circuits and Systems, 2016
2015
IEEE Trans. Neural Networks Learn. Syst., 2015
Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data.
PLoS Comput. Biol., 2015
Training Binary Multilayer Neural Networks for Image Classification using Expectation Backpropagation.
CoRR, 2015
2014
The neuronal response at extended timescales: a linearized spiking input-output relation.
Frontiers Comput. Neurosci., 2014
The neuronal response at extended timescales: long-term correlations without long-term memory.
Frontiers Comput. Neurosci., 2014
Diffusion approximation-based simulation of stochastic ion channels: which method to use?
Frontiers Comput. Neurosci., 2014
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
2012
Frontiers Comput. Neurosci., 2012
"Neuronal spike generation mechanism as an oversampling, noise-shaping A-to-D converter".
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
2010
Frontiers Comput. Neurosci., 2010