Michael G. Rabbat

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 74

Top Venues

CoRR

ICASSP

IEEE Trans. Signal Inf. Process. over Networks

IEEE Trans. Signal Process.

Publications

Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael G. Rabbat, Yann LeCun, Mahmoud Assran, Nicolas Ballas
Revisiting Feature Prediction for Learning Visual Representations from Video. CoRR (2024)
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael G. Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski
DINOv2: Learning Robust Visual Features without Supervision. CoRR (2023)
Chuan Guo, Kamalika Chaudhuri, Pierre Stock, Michael G. Rabbat
Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design. ICML (2023)
Mitchell Wortsman, Suchin Gururangan, Shen Li, Ali Farhadi, Ludwig Schmidt, Michael G. Rabbat, Ari S. Morcos
lo-fi: distributed fine-tuning without communication. Trans. Mach. Learn. Res. 2023 (2023)
Mido Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas
The hidden uniform cluster prior in self-supervised learning. ICLR (2023)
Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CoRR (2023)
John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. ICLR (2023)
Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture. CVPR (2023)
Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael G. Rabbat, Nicolas Ballas
Masked Siamese Networks for Label-Efficient Learning. CoRR (2022)
Mahmoud Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas
The Hidden Uniform Cluster Prior in Self-Supervised Learning. CoRR (2022)
Samuel Horváth, Maziar Sanjabi, Lin Xiao, Peter Richtárik, Michael G. Rabbat
FedShuffle: Recipes for Better Use of Local Work in Federated Learning. Trans. Mach. Learn. Res. 2022 (2022)
Mitchell Wortsman, Suchin Gururangan, Shen Li, Ali Farhadi, Ludwig Schmidt, Michael G. Rabbat, Ari S. Morcos
lo-fi: distributed fine-tuning without communication. CoRR (2022)
Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Armand Joulin, Nicolas Ballas, Michael G. Rabbat
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples. ICCV (2021)
Robert M. Gower, Aaron Defazio, Michael G. Rabbat
Stochastic Polyak Stepsize with a Moving Target. CoRR (2021)
Mahmoud Assran, Michael G. Rabbat
Asynchronous Gradient Push. IEEE Trans. Autom. Control. 66 (1) (2021)
Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Armand Joulin, Nicolas Ballas, Michael G. Rabbat
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples. CoRR (2021)
Florian Knoll, Tullie Murrell, Anuroop Sriram, Nafissa Yakubova, Jure Zbontar, Michael G. Rabbat, Aaron Defazio, Matthew J. Muckley, Daniel K. Sodickson, C. Lawrence Zitnick, Michael P. Recht
Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge. CoRR (2020)
Jianyu Wang, Vinayak Tantia, Nicolas Ballas, Michael G. Rabbat
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum. ICLR (2020)
Julien M. Hendrickx, Michael G. Rabbat
Stability of Decentralized Gradient Descent in Open Multi-Agent Systems. CoRR (2020)
Jianyu Wang, Vinayak Tantia, Nicolas Ballas, Michael G. Rabbat
Lookahead Converges to Stationary Points of Smooth Non-convex Functions. ICASSP (2020)
Mahmoud Assran, Arda Aytekin, Hamid Reza Feyzmahdavian, Mikael Johansson, Michael G. Rabbat
Advances in Asynchronous Parallel and Distributed Optimization. Proc. IEEE 108 (11) (2020)
Mahmoud Assran, Michael G. Rabbat
On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings. CoRR (2020)
Mahmoud Assran, Nicolas Ballas, Lluís Castrejón, Michael G. Rabbat
Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations. CoRR (2020)
Mahmoud Assran, Arda Aytekin, Hamid Reza Feyzmahdavian, Mikael Johansson, Michael G. Rabbat
Advances in Asynchronous Parallel and Distributed Optimization. CoRR (2020)
Julien M. Hendrickx, Michael G. Rabbat
Stability of Decentralized Gradient Descent in Open Multi-Agent Systems. CDC (2020)
Shagun Sodhani, Olivier Delalleau, Mahmoud Assran, Koustuv Sinha, Nicolas Ballas, Michael G. Rabbat
A Closer Look at Codistillation for Distributed Training. CoRR (2020)
Usman A. Khan, Waheed U. Bajwa, Angelia Nedic, Michael G. Rabbat, Ali H. Sayed
Optimization for Data-Driven Learning and Control. Proc. IEEE 108 (11) (2020)
Jun Ye Yu, Mark J. Coates, Michael G. Rabbat
Graph-Based Compression for Distributed Particle Filters. IEEE Trans. Signal Inf. Process. over Networks 5 (3) (2019)
Aida Nowzari, Michael G. Rabbat
Improved Bounds for Max Consensus in Wireless Networks. IEEE Trans. Signal Inf. Process. over Networks 5 (2) (2019)
Nicolas Loizou, Michael G. Rabbat, Peter Richtárik
Provably Accelerated Randomized Gossip Algorithms. ICASSP (2019)
Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Michael G. Rabbat
Stochastic Gradient Push for Distributed Deep Learning. ICML (2019)
Xiaowen Dong, Dorina Thanou, Michael G. Rabbat, Pascal Frossard
Learning Graphs From Data: A Signal Representation Perspective. IEEE Signal Process. Mag. 36 (3) (2019)
Jianyu Wang, Vinayak Tantia, Nicolas Ballas, Michael G. Rabbat
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum. CoRR (2019)
Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J. Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J. Geras, Joe Katsnelson, Hersh Chandarana, Zizhao Zhang, Michal Drozdzal, Adriana Romero, Michael G. Rabbat, Pascal Vincent, James Pinkerton, Duo Wang, Nafissa Yakubova, Erich Owens, C. Lawrence Zitnick, Michael P. Recht, Daniel K. Sodickson, Yvonne W. Lui
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI. CoRR (2018)
Babak Fotouhi, Michael G. Rabbat
Temporal evolution of the degree distribution of alters in growing networks. Netw. Sci. 6 (1) (2018)
Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Michael G. Rabbat
Stochastic Gradient Push for Distributed Deep Learning. CoRR (2018)
Nicolas Loizou, Michael G. Rabbat, Peter Richtárik
Provably Accelerated Randomized Gossip Algorithms. CoRR (2018)
Yingxue Zhang, Michael G. Rabbat
A Graph-CNN for 3D Point Cloud Classification. ICASSP (2018)
Mahmoud Assran, Michael G. Rabbat
Asynchronous Subgradient-Push. CoRR (2018)
Bastien Pasdeloup, Vincent Gripon, Grégoire Mercier, Dominique Pastor, Michael G. Rabbat
Characterization and Inference of Graph Diffusion Processes From Observations of Stationary Signals. IEEE Trans. Signal Inf. Process. over Networks 4 (3) (2018)
Yingxue Zhang, Michael G. Rabbat
A Graph-CNN for 3D Point Cloud Classification. CoRR (2018)
Xiaowen Dong, Dorina Thanou, Michael G. Rabbat, Pascal Frossard
Learning Graphs from Data: A Signal Representation Perspective. CoRR (2018)
Naghmeh Momeni, Michael G. Rabbat
Effectiveness of Alter Sampling in Social Networks. CoRR (2018)
Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael G. Rabbat, Joelle Pineau
TarMAC: Targeted Multi-Agent Communication. CoRR (2018)
Ahmet Iscen, Teddy Furon, Vincent Gripon, Michael G. Rabbat, Hervé Jégou
Memory Vectors for Similarity Search in High-Dimensional Spaces. IEEE Trans. Big Data 4 (1) (2018)
Angelia Nedic, Alex Olshevsky, Michael G. Rabbat
Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization. Proc. IEEE 106 (5) (2018)
Mahmoud Assran, Michael G. Rabbat
An empirical comparison of multi-agent optimization algorithms. GlobalSIP (2017)
Sean F. Lawlor, Michael G. Rabbat
Time-Varying Mixtures of Markov Chains: An Application to Road Traffic Modeling. IEEE Trans. Signal Process. 65 (12) (2017)
Augustin-Alexandru Saucan, Mark J. Coates, Michael G. Rabbat
A Multisensor Multi-Bernoulli Filter. IEEE Trans. Signal Process. 65 (20) (2017)
Michael G. Rabbat
Inferring sparse graphs from smooth signals with theoretical guarantees. ICASSP (2017)
Angelia Nedic, Alex Olshevsky, Michael G. Rabbat
Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization. CoRR (2017)
Pascal Frossard, Pier Luigi Dragotti, Antonio Ortega, Michael G. Rabbat, Alejandro Ribeiro
Cooperative Special Issue on Graph Signal Processing in the IEEE Journal of Selected Topics in Signal Processing and the IEEE Transactions on Signal and Information Processing Over Networks. IEEE Trans. Signal Inf. Process. over Networks 3 (3) (2017)
Naghmeh Momeni, Michael G. Rabbat
Inferring Structural Characteristics of Networks with Strong and Weak Ties from Fixed-Choice Surveys. CoRR (2017)
Naghmeh Momeni, Michael G. Rabbat
Inferring Structural Characteristics of Networks With Strong and Weak Ties From Fixed-Choice Surveys. IEEE Trans. Signal Inf. Process. over Networks 3 (3) (2017)
Jun Ye Yu, Augustin-Alexandru Saucan, Mark Coates, Michael G. Rabbat
Algorithms for the multi-sensor assignment problem in the δ-generalized labeled multi-Bernoulli filter. CAMSAP (2017)
Pascal Frossard, Pier Luigi Dragotti, Antonio Ortega, Michael G. Rabbat, Alejandro Ribeiro
Introduction to the IEEE Journal on Selected Topics in Signal Processing and IEEE Transactions on Signal and Information Processing Over Networks Joint Special Issue on Graph Signal Processing. IEEE J. Sel. Top. Signal Process. 11 (6) (2017)
François Leduc-Primeau, Vincent Gripon, Michael G. Rabbat, Warren J. Gross
Fault-Tolerant Associative Memories Based on c-Partite Graphs. IEEE Trans. Signal Process. 64 (4) (2016)
Xiaoran Jiang, Vincent Gripon, Claude Berrou, Michael G. Rabbat
Storing Sequences in Binary Tournament-Based Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 27 (5) (2016)
Ahmet Iscen, Michael G. Rabbat, Teddy Furon
Efficient Large-Scale Similarity Search Using Matrix Factorization. CVPR (2016)
Sean F. Lawlor, Timothy Sider, Naveen Eluru, Marianne Hatzopoulou, Michael G. Rabbat
Detecting Convoys Using License Plate Recognition Data. IEEE Trans. Signal Inf. Process. over Networks 2 (3) (2016)
Bastien Pasdeloup, Vincent Gripon, Grégoire Mercier, Dominique Pastor, Michael G. Rabbat
Characterization and inference of weighted graph topologies from observations of diffused signals. CoRR (2016)
Bastien Pasdeloup, Michael G. Rabbat, Vincent Gripon, Dominique Pastor, Grégoire Mercier
Graph reconstruction from the observation of diffused signals. CoRR (2016)
Themistoklis Charalambous, Michael G. Rabbat, Mikael Johansson, Christoforos N. Hadjicostis
Distributed Finite-Time Computation of Digraph Parameters: Left-Eigenvector, Out-Degree and Spectrum. IEEE Trans. Control. Netw. Syst. 3 (2) (2016)
Jun Ye Yu, Mark J. Coates, Michael G. Rabbat, Stéphane Blouin
A Distributed Particle Filter for Bearings-Only Tracking on Spherical Surfaces. IEEE Signal Process. Lett. 23 (3) (2016)
Santosh Nannuru, Stéphane Blouin, Mark Coates, Michael G. Rabbat
Multisensor CPHD filter. IEEE Trans. Aerosp. Electron. Syst. 52 (4) (2016)
Themistoklis Charalambous, Christoforos N. Hadjicostis, Michael G. Rabbat, Mikael Johansson
Totally asynchronous distributed estimation of eigenvector centrality in digraphs with application to the PageRank problem. CDC (2016)
Naghmeh Momeni, Michael G. Rabbat
Qualities and Inequalities in Online Social Networks through the Lens of the Generalized Friendship Paradox. CoRR (2016)
Farhad Farokhi, Iman Shames, Michael G. Rabbat, Mikael Johansson
On reconstructability of quadratic utility functions from the iterations in gradient methods. Autom. 66 (2016)
Sean F. Lawlor, Michael G. Rabbat
Estimation of time-varying mixture models: An application to traffic estimation. SSP (2016)
Konstantinos I. Tsianos, Michael G. Rabbat
Efficient Distributed Online Prediction and Stochastic Optimization With Approximate Distributed Averaging. IEEE Trans. Signal Inf. Process. over Networks 2 (4) (2016)
Naghmeh Momeni, Michael G. Rabbat
Inferring network properties from fixed-choice design with strong and weak ties. SSP (2016)
Jun Ye Yu, Mark Coates, Michael G. Rabbat
Distributed multi-sensor CPHD filter using pairwise gossiping. ICASSP (2016)
Sindri Magnússon, Pradeep Chathuranga Weeraddana, Michael G. Rabbat, Carlo Fischione
On the Convergence of Alternating Direction Lagrangian Methods for Nonconvex Structured Optimization Problems. IEEE Trans. Control. Netw. Syst. 3 (3) (2016)
Michael G. Rabbat, Mark Coates, Stéphane Blouin
Graph Laplacian distributed particle filtering. EUSIPCO (2016)
Bastien Pasdeloup, Michael G. Rabbat, Vincent Gripon, Dominique Pastor, Grégoire Mercier
Graph reconstruction from the observation of diffused signals. Allerton (2015)
Jun Ye Yu, Michael G. Rabbat, Mark Coates, Stéphane Blouin
Performance investigation on constraint sufficient statistics distributed particle filter. CCECE (2015)
Bastien Pasdeloup, Réda Alami, Vincent Gripon, Michael G. Rabbat
Toward an uncertainty principle for weighted graphs. EUSIPCO (2015)
Syamantak Datta Gupta, Mark Coates, Michael G. Rabbat
Error Propagation in Gossip-Based Distributed Particle Filters. IEEE Trans. Signal Inf. Process. over Networks 1 (3) (2015)
Naghmeh Momeni, Michael G. Rabbat
Measuring the Generalized Friendship Paradox in Networks with Quality-Dependent Connectivity. CompleNet (2015)
Michael G. Rabbat
Multi-agent mirror descent for decentralized stochastic optimization. CAMSAP (2015)
Bastien Pasdeloup, Réda Alami, Vincent Gripon, Michael G. Rabbat
Toward An Uncertainty Principle For Weighted Graphs. CoRR (2015)
Chon-Wang Chao, Michael G. Rabbat, Stéphane Blouin
Particle weight approximation with clustering for gossip-based distributed particle filters. CAMSAP (2015)
Santosh Nannuru, Mark Coates, Michael G. Rabbat, Stéphane Blouin
General solution and approximate implementation of the multisensor multitarget CPHD filter. ICASSP (2015)
Farhad Farokhi, Iman Shames, Michael G. Rabbat, Mikael Johansson
On Reconstructability of Quadratic Utility Functions from the Iterations in Gradient Methods. CoRR (2015)
Konstantinos I. Tsianos, Michael G. Rabbat
Efficient Distributed Online Prediction and Stochastic Optimization with Approximate Distributed Averaging. CoRR (2014)
François Leduc-Primeau, Vincent Gripon, Michael G. Rabbat, Warren J. Gross
Cluster-based associative memories built from unreliable storage. ICASSP (2014)
Pegah Sattari, Maciej Kurant, Animashree Anandkumar, Athina Markopoulou, Michael G. Rabbat
Active Learning of Multiple Source Multiple Destination Topologies. IEEE Trans. Signal Process. 62 (8) (2014)
Sindri Magnússon, P. C. Weeraddana, Michael G. Rabbat, Carlo Fischione
On the convergence of an alternating direction penalty method for nonconvex problems. ACSSC (2014)
Euhanna Ghadimi, André Teixeira, Michael G. Rabbat, Mikael Johansson
The ADMM algorithm for distributed averaging: Convergence rates and optimal parameter selection. ACSSC (2014)
Michael G. Rabbat, Vincent Gripon
Towards a spectral characterization of signals supported on small-world networks. ICASSP (2014)
Konstantinos I. Tsianos, Anand D. Sarwate, Michael G. Rabbat
Tradeoffs for task parallelization in distributed optimization. MLSP (2014)
Vitaly Skachek, Michael G. Rabbat
Subspace synchronization: A network-coding approach to object reconciliation. ISIT (2014)
Ahmet Iscen, Teddy Furon, Vincent Gripon, Michael G. Rabbat, Hervé Jégou
Memory vectors for similarity search in high-dimensional spaces. CoRR (2014)
Babak Fotouhi, Naghmeh Momeni, Michael G. Rabbat
Generalized Friendship Paradox: An Analytical Approach. SocInfo Workshops (2014)
R. Michael Buehrer, Christopher Robert Anderson, Richard K. Martin, Neal Patwari, Michael G. Rabbat
Introduction to the Special Issue on Non-Cooperative Localization Networks. IEEE J. Sel. Top. Signal Process. 8 (1) (2014)
Vincent Gripon, Vitaly Skachek, Michael G. Rabbat
Sparse binary matrices as efficient associative memories. Allerton (2014)
Xiaoran Jiang, Vincent Gripon, Claude Berrou, Michael G. Rabbat
Storing sequences in binary tournament-based neural networks. CoRR (2014)
Zhe Yao, Vincent Gripon, Michael G. Rabbat
A GPU-based associative memory using sparse Neural Networks. HPCS (2014)
Sean F. Lawlor, Michael G. Rabbat
Detecting convoys in networks of short-ranged sensors. ACSSC (2014)
Naghmeh Momeni, Michael G. Rabbat
Measuring the Generalized Friendship Paradox in Networks with Quality-dependent Connectivity. CoRR (2014)

Michael G. Rabbat.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Michael G. Rabbat