Pedro Savarese

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Michael MaireUniversity of ChicagoVerified email at uchicago.edu
Daniel Ratton FigueiredoFederal University of Rio de Janeiro (UFRJ)Verified email at cos.ufrj.br
Leonardo F. R. RibeiroAmazonVerified email at amazon.com
Daniel SoudryAssociate ProfessorVerified email at technion.ac.il
Nathan SrebroProfessor, TTIC and University of ChicagoVerified email at ttic.edu
Suriya GunasekarMSR RedmondVerified email at ttic.edu
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityVerified email at princeton.edu
Xin YuanUniversity of ChicagoVerified email at uchicago.edu
Hugo SilvaUniversity of AlbertaVerified email at ualberta.ca
David McAllesterProfessor, Toyota Technological Institute at ChicagoVerified email at ttic.edu
Matthew R. WalterToyota Technological Institute at ChicagoVerified email at ttic.edu
Karen LivescuTTI-ChicagoVerified email at ttic.edu
Kumar Kshitij PatelPhd Student, TTICVerified email at ttic.edu
Gal VardiWeizmann Institute of ScienceVerified email at weizmann.ac.il
David YunisGraduate Student, TTICVerified email at ttic.edu
Jonathan FrankleDatabricks - Mosaic ResearchVerified email at databricks.com
Greg ShakhnarovichProfessor, TTI-ChicagoVerified email at ttic.edu
Sunnie S. Y. KimPrinceton UniversityVerified email at princeton.edu
Bruno RibeiroAssociate Professor of Computer Science at Purdue UniversityVerified email at cs.purdue.edu

Pedro Savarese

TTIC

Verified email at ttic.edu - Homepage

Machine Learning Deep Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
struc2vec: Learning Node Representations from Structural Identity LFR Ribeiro, P Savarese, DR Figueiredo SIGKDD, 2017	1361	2017
Kernel and Rich Regimes in Overparametrized Models B Woodworth, S Gunasekar, JD Lee, E Moroshko, P Savarese, I Golan, ... COLT, 2020	355	2020
How do Infinite Width Bounded Norm Networks look in Function Space? P Savarese, I Evron, D Soudry, N Srebro COLT, 2019	161	2019
Convergence of Gradient Descent on Separable Data MS Nacson, J Lee, S Gunasekar, P Savarese, N Srebro, D Soudry AISTATS, 2019	158	2019
Winning the Lottery with Continuous Sparsification P Savarese, H Silva, M Maire NeurIPS, 2020	130	2020
Learning Implicitly Recurrent CNNs Through Parameter Sharing P Savarese, M Maire ICLR, 2019	77	2019
Growing Efficient Deep Networks by Structured Continuous Sparsification X Yuan, P Savarese, M Maire ICLR, 2021	51	2021
Information-Theoretic Segmentation by Inpainting Error Maximization P Savarese, SSY Kim, M Maire, G Shakhnarovich, D McAllester CVPR, 2021	26	2021
On the Convergence of AdaBound and its Connection to SGD P Savarese arXiv preprint arXiv:1908.04457, 2019	25	2019
struc2vec: Learning node representations from structural identity DR Figueiredo, LFR Ribeiro, PHP Saverese CoRR, 2017	22	2017
Domain-Independent Dominance of Adaptive Methods P Savarese, D McAllester, S Babu, M Maire CVPR, 2021	21	2021
Building a Massive Corpus for Named Entity Recognition using Free Open Data Sources D Menezes, P Savarese, R Milidiu BRACIS, 2019	16	2019
On Convexity and Linear Mode Connectivity in Neural Networks D Yunis, KK Patel, P Savarese, K Livescu, M Walter, J Frankle, M Maire OPT, 2022	13	2022
Residual gates: A Simple Mechanism for Improved Network Optimization P Savarese, D Figueiredo	11	2017
Learning Identity Mappings with Residual Gates P Savarese, LO Mazza, DR Figueiredo arXiv preprint arXiv:1611.01260, 2016	7	2016
Not All Bits have Equal Value: Heterogeneous Precisions via Trainable Noise P Savarese, X Yuan, Y Li, M Maire NeurIPS, 2022	4	2022
Online Meta-Learning via Learning with Layer-Distributed Memory S Babu, P Savarese, M Maire NeurIPS, 2021	4	2021
Accelerated training via incrementally growing neural networks using variance transfer and learning rate adaptation X Yuan, P Savarese, M Maire Advances in Neural Information Processing Systems 36, 2024	3	2024
From Monte Carlo to Las Vegas: Improving Restricted Boltzmann Machine Training Through Stopping Sets P Savarese, M Kakodkar, B Ribeiro AAAI, 2018	3	2018
SySMOL: A Hardware-software Co-design Framework for Ultra-Low and Fine-Grained Mixed-Precision Neural Networks C Zhou, V Richard, P Savarese, Z Hassman, M Maire, M DiBrino, Y Li arXiv preprint arXiv:2311.14114, 2023	1	2023

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