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Ioannis Mitliagkas

Manifold Mixup: Better Representations by Interpolating Hidden States
2018 · Verma, Vikas, Lamb, Alex, et al. · arXiv (Cornell University) · 919
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Learning Representations and Generative Models for 3D Point Clouds
2017 · Achlioptas, Panos, Diamanti, Olga, et al. · arXiv (Cornell University) · 755
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Asynchrony begets momentum, with an application to deep learning
2016 · Ioannis Mitliagkas, Ce Zhang, et al. · Allerton Conference on Communication, Control, and Computing · 116
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Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
2021 · Ahuja, Kartik, Caballero, Ethan, et al. · arXiv (Cornell University) · 114
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A Modern Take on the Bias-Variance Tradeoff in Neural Networks
2018 · Neal, Brady, Mittal, Sarthak, et al. · arXiv (Cornell University) · 111
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Memory Limited, Streaming PCA
2013 · Mitliagkas, Ioannis, Caramanis, Constantine, et al. · arXiv (Cornell University) · 94
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Generalizing to unseen domains via distribution matching
2019 · Albuquerque, Isabela, Monteiro, João, et al. · arXiv (Cornell University) · 87
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Joint Power and Admission Control for Ad-Hoc and Cognitive Underlay Networks: Convex Approximation and Distributed Implementation
2011 · Ioannis Mitliagkas, Nicholas D. Sidiropoulos, et al. · IEEE Transactions on Wireless Communications · 83
Parallel SGD: When does averaging help?
2016 · Zhang, Jian, De Sa, Christopher, et al. · arXiv (Cornell University) · 76
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Gotta Go Fast When Generating Data with Score-Based Models
2021 · Jolicoeur-Martineau, Alexia, Li, Ke, et al. · arXiv (Cornell University) · 74
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YellowFin and the Art of Momentum Tuning
2017 · Zhang, Jian, Mitliagkas, Ioannis · arXiv (Cornell University) · 67
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Representation Learning and Adversarial Generation of 3D Point Clouds
2017 · Panos Achlioptas, Olga Diamanti, et al. · arXiv (Cornell University) · 63
Deep learning at 15PF
2017 · Thorsten Kurth, Jian Zhang, et al. · 2012 International Conference for High Performance Computing, Networking, Storage and Analysis · 62
Adversarial score matching and improved sampling for image generation
2020 · Jolicoeur-Martineau, Alexia, Piché-Taillefer, Rémi, et al. · arXiv (Cornell University) · 50
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Multi-objective training of Generative Adversarial Networks with multiple discriminators
2019 · Albuquerque, Isabela, Monteiro, João, et al. · arXiv (Cornell University) · 47
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Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs
2016 · Hadjis, Stefan, Zhang, Ce, et al. · arXiv (Cornell University) · 44
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In Search of Robust Measures of Generalization
2020 · Dziugaite, Gintare Karolina, Drouin, Alexandre, et al. · arXiv (Cornell University) · 41
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Accelerated Stochastic Power Iteration
2018 · Peng Xu, Bryan He, et al. · International Conference on Artificial Intelligence and Statistics · 39
Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer.
2018 · Vikas Verma, Alex Lamb, et al. · arXiv (Cornell University) · 38
Negative Momentum for Improved Game Dynamics
2018 · Gidel, Gauthier, Hemmat, Reyhane Askari, et al. · arXiv (Cornell University) · 31
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FrogWild!
2015 · Ioannis Mitliagkas, Michael Borokhovich, et al. · Proceedings of the VLDB Endowment · 30
h-detach: Modifying the LSTM Gradient Towards Better Optimization
2018 · Arpit, Devansh, Kanuparthi, Bhargav, et al. · arXiv (Cornell University) · 28
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Linear Lower Bounds and Conditioning of Differentiable Games
2019 · Ibrahim, Adam, Azizian, Waïss, et al. · arXiv (Cornell University) · 26
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Manifold Mixup: Learning Better Representations by Interpolating Hidden States
2018 · Vikas Verma, Alex Lamb, et al. · 26
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations
2018 · Lamb, Alex, Binas, Jonathan, et al. · arXiv (Cornell University) · 26
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Works count: 99
Citation count: 3,425
H-index: 26
I10-index: 39
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