Pedro Savarese

According to our database, Pedro Savarese authored at least 18 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Approaching Deep Learning through the Spectral Dynamics of Weights.

David Yunis, Kumar Kshitij Patel, Samuel Wheeler, Pedro Savarese, Gal Vardi, Karen Livescu, Michael Maire, Matthew R. Walter

CoRR, 2024

Drop-Connect as a Fault-Tolerance Approach for RRAM-based Deep Neural Network Accelerators.

Mingyuan Xiang, Xuhan Xie, Pedro Savarese, Xin Yuan, Michael Maire, Yanjing Li

Proceedings of the 42nd IEEE VLSI Test Symposium, 2024

2023

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

Cyrus Zhou, Vaughn Richard, Pedro Savarese, Zachary Hassman, Michael Maire, Michael DiBrino, Yanjing Li

CoRR, 2023

Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation.

Xin Yuan, Pedro Savarese, Michael Maire

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.

Pedro Savarese, Xin Yuan, Yanjing Li, Michael Maire

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.

Sudarshan Babu, Pedro Savarese, Michael Maire

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.

Xin Yuan, Pedro Henrique Pamplona Savarese, Michael Maire

Proceedings of the 9th International Conference on Learning Representations, 2021

Domain-Independent Dominance of Adaptive Methods.

Pedro Savarese, David McAllester, Sudarshan Babu, Michael Maire

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Information-Theoretic Segmentation by Inpainting Error Maximization.

Pedro Savarese, Sunnie S. Y. Kim, Michael Maire, Greg Shakhnarovich, David McAllester

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Winning the Lottery with Continuous Sparsification.

Pedro Savarese, Hugo Silva, Michael Maire

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.

Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro

Proceedings of the Conference on Learning Theory, 2020

2019

On the Convergence of AdaBound and its Connection to SGD.

Pedro Savarese

CoRR, 2019

Learning Implicitly Recurrent CNNs Through Parameter Sharing.

Pedro Savarese, Michael Maire

Proceedings of the 7th International Conference on Learning Representations, 2019

How do infinite width bounded norm networks look in function space?

Pedro Savarese, Itay Evron, Daniel Soudry, Nathan Srebro

Proceedings of the Conference on Learning Theory, 2019

Building a Massive Corpus for Named Entity Recognition Using Free Open Data Sources.

Daniel Specht Menezes, Ruy Milidiú, Pedro Savarese

Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

Convergence of Gradient Descent on Separable Data.

Mor Shpigel Nacson, Jason D. Lee, Suriya Gunasekar, Pedro Henrique Pamplona Savarese, Nathan Srebro, Daniel Soudry

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.

Pedro H. P. Savarese, Mayank Kakodkar, Bruno Ribeiro

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016

Learning Identity Mappings with Residual Gates.

Pedro H. P. Savarese

CoRR, 2016