Pedro Savarese

Affiliations:
  • Toyota Technological Institute at Chicago, IL, USA


According to our database1, Pedro Savarese authored at least 16 papers between 2016 and 2023.

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Bibliography

2023
SySMOL: A Hardware-software Co-design Framework for Ultra-Low and Fine-Grained Mixed-Precision Neural Networks.
CoRR, 2023

Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Not All Bits have Equal Value: Heterogeneous Precisions via Trainable Noise.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Meta-Learning via Learning with Distributed Memory.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Growing Efficient Deep Networks by Structured Continuous Sparsification.
Proceedings of the 9th International Conference on Learning Representations, 2021

Domain-Independent Dominance of Adaptive Methods.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Information-Theoretic Segmentation by Inpainting Error Maximization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Winning the Lottery with Continuous Sparsification.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Kernel and Rich Regimes in Overparametrized Models.
Proceedings of the Conference on Learning Theory, 2020

2019
On the Convergence of AdaBound and its Connection to SGD.
CoRR, 2019

Learning Implicitly Recurrent CNNs Through Parameter Sharing.
Proceedings of the 7th International Conference on Learning Representations, 2019

How do infinite width bounded norm networks look in function space?
Proceedings of the Conference on Learning Theory, 2019

Building a Massive Corpus for Named Entity Recognition Using Free Open Data Sources.
Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

Convergence of Gradient Descent on Separable Data.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016
Learning Identity Mappings with Residual Gates.
CoRR, 2016


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