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ORCIDPedro Savarese
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- affiliation: Toyota Technological Institute at Chicago, IL, USA
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2020 – today
- 2023
[c13]Xin Yuan, Pedro Savarese, Michael Maire:
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation. NeurIPS 2023- [i13]Xin Yuan, Pedro Savarese, Michael Maire:
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation. CoRR abs/2306.12700 (2023) - [i12]Cyrus Zhou, Vaughn Richard, Pedro Savarese, Zachary Hassman, Michael Maire, Michael DiBrino, Yanjing Li:
SySMOL: A Hardware-software Co-design Framework for Ultra-Low and Fine-Grained Mixed-Precision Neural Networks. CoRR abs/2311.14114 (2023) - 2022
- [c12]Pedro Savarese, Xin Yuan, Yanjing Li, Michael Maire:
Not All Bits have Equal Value: Heterogeneous Precisions via Trainable Noise. NeurIPS 2022 - 2021
- [c11]Pedro Savarese, Sunnie S. Y. Kim, Michael Maire, Greg Shakhnarovich, David McAllester:
Information-Theoretic Segmentation by Inpainting Error Maximization. CVPR 2021: 4029-4039 - [c10]Pedro Savarese, David McAllester, Sudarshan Babu, Michael Maire:
Domain-Independent Dominance of Adaptive Methods. CVPR 2021: 16286-16295 - [c9]Xin Yuan, Pedro Henrique Pamplona Savarese, Michael Maire:
Growing Efficient Deep Networks by Structured Continuous Sparsification. ICLR 2021 - [c8]Sudarshan Babu, Pedro Savarese, Michael Maire:
Meta-Learning via Learning with Distributed Memory. NeurIPS 2021: 14795-14808 - 2020
- [c7]Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro:
Kernel and Rich Regimes in Overparametrized Models. COLT 2020: 3635-3673 - [c6]Pedro Savarese, Hugo Silva, Michael Maire:
Winning the Lottery with Continuous Sparsification. NeurIPS 2020 - [i11]Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro:
Kernel and Rich Regimes in Overparametrized Models. CoRR abs/2002.09277 (2020) - [i10]Xin Yuan, Pedro Savarese, Michael Maire:
Growing Efficient Deep Networks by Structured Continuous Sparsification. CoRR abs/2007.15353 (2020) - [i9]Pedro Savarese, Sunnie S. Y. Kim, Michael Maire, Greg Shakhnarovich, David McAllester:
Information-Theoretic Segmentation by Inpainting Error Maximization. CoRR abs/2012.07287 (2020)
2010 – 2019
- 2019
- [c5]Mor Shpigel Nacson, Jason D. Lee, Suriya Gunasekar, Pedro Henrique Pamplona Savarese, Nathan Srebro, Daniel Soudry:
Convergence of Gradient Descent on Separable Data. AISTATS 2019: 3420-3428 - [c4]Daniel Specht Menezes, Ruy Milidiú, Pedro Savarese:
Building a Massive Corpus for Named Entity Recognition Using Free Open Data Sources. BRACIS 2019: 6-11 - [c3]Pedro Savarese, Itay Evron, Daniel Soudry, Nathan Srebro:
How do infinite width bounded norm networks look in function space? COLT 2019: 2667-2690 - [c2]Pedro Savarese, Michael Maire:
Learning Implicitly Recurrent CNNs Through Parameter Sharing. ICLR (Poster) 2019 - [i8]Pedro Savarese, Itay Evron, Daniel Soudry, Nathan Srebro:
How do infinite width bounded norm networks look in function space? CoRR abs/1902.05040 (2019) - [i7]Pedro Savarese, Michael Maire:
Learning Implicitly Recurrent CNNs Through Parameter Sharing. CoRR abs/1902.09701 (2019) - [i6]Pedro Savarese:
On the Convergence of AdaBound and its Connection to SGD. CoRR abs/1908.04457 (2019) - [i5]Daniel Specht Menezes, Pedro Savarese, Ruy Luiz Milidiú:
Building a Massive Corpus for Named Entity Recognition using Free Open Data Sources. CoRR abs/1908.05758 (2019) - [i4]Pedro Savarese, David McAllester, Sudarshan Babu, Michael Maire:
Domain-independent Dominance of Adaptive Methods. CoRR abs/1912.01823 (2019) - [i3]Pedro Savarese, Hugo Silva, Michael Maire:
Winning the Lottery with Continuous Sparsification. CoRR abs/1912.04427 (2019) - 2018
- [c1]Pedro H. P. Savarese, Mayank Kakodkar, Bruno Ribeiro:
From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets. AAAI 2018: 4016-4025 - 2017
- [i2]Pedro H. P. Savarese, Mayank Kakodkar, Bruno Ribeiro:
From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets. CoRR abs/1711.08442 (2017) - 2016
- [i1]Pedro H. P. Savarese:
Learning Identity Mappings with Residual Gates. CoRR abs/1611.01260 (2016)
Coauthor Index
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