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07/31/2023
Predicting masked tokens in stochastic locations improves masked image modeling
Self-supervised learning is a promising paradigm in deep learning that e...
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04/14/2023
DINOv2: Learning Robust Visual Features without Supervision
The recent breakthroughs in natural language processing for model pretra...
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01/19/2023
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
This paper demonstrates an approach for learning highly semantic image r...
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10/13/2022
The Hidden Uniform Cluster Prior in Self-Supervised Learning
A successful paradigm in representation learning is to perform self-supe...
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04/14/2022
Masked Siamese Networks for Label-Efficient Learning
We propose Masked Siamese Networks (MSN), a self-supervised learning fra...
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06/20/2021
Memory Augmented Optimizers for Deep Learning
Popular approaches for minimizing loss in data-driven learning often inv...
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04/28/2021
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples
This paper proposes a novel method of learning by predicting view assign...
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10/06/2020
A Closer Look at Codistillation for Distributed Training
Codistillation has been proposed as a mechanism to share knowledge among...
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06/24/2020
Advances in Asynchronous Parallel and Distributed Optimization
Motivated by large-scale optimization problems arising in the context of...
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06/18/2020
Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations
We investigate a strategy for improving the computational efficiency of ...
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02/27/2020
On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings
We study Nesterov's accelerated gradient method in the stochastic approx...
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06/09/2019
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning
Multi-simulator training has contributed to the recent success of Deep R...
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11/27/2018
Stochastic Gradient Push for Distributed Deep Learning
Large mini-batch parallel SGD is commonly used for distributed training ...
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03/23/2018
