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09/27/2022
Efficient Non-Parametric Optimizer Search for Diverse Tasks
Efficient and automated design of optimizers plays a crucial role in ful...
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07/20/2022
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
Federated learning (FL) has recently attracted increasing attention from...
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12/16/2021
Extreme Zero-Shot Learning for Extreme Text Classification
The eXtreme Multi-label text Classification (XMC) problem concerns findi...
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10/13/2021
Adversarial Attack across Datasets
It has been observed that Deep Neural Networks (DNNs) are vulnerable to ...
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09/05/2021
Training Meta-Surrogate Model for Transferable Adversarial Attack
We consider adversarial attacks to a black-box model when no queries are...
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10/19/2020
How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers
Many optimizers have been proposed for training deep neural networks, an...
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04/25/2020
Improved Adversarial Training via Learned Optimizer
Adversarial attack has recently become a tremendous threat to deep learn...
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10/21/2019
Learning to Learn by Zeroth-Order Oracle
In the learning to learn (L2L) framework, we cast the design of optimiza...
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05/12/2019
Learning Phase Competition for Traffic Signal Control
Increasingly available city data and advanced learning techniques have e...
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02/26/2019