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03/13/2022
Symbolic Learning to Optimize: Towards Interpretability and Scalability
Recent studies on Learning to Optimize (L2O) suggest a promising path to...
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06/24/2021
Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks
In this paper, we present a perception-action-communication loop design ...
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05/16/2021
Undistillable: Making A Nasty Teacher That CANNOT teach students
Knowledge Distillation (KD) is a widely used technique to transfer knowl...
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01/08/2021
Good Students Play Big Lottery Better
Lottery ticket hypothesis suggests that a dense neural network contains ...
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10/22/2020
Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free
Adversarial training and its many variants substantially improve deep ne...
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02/24/2020
Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference
Deep networks were recently suggested to face the odds between accuracy ...
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02/06/2020
VGAI: A Vision-Based Decentralized Controller Learning Framework for Robot Swarms
Despite the popularity of decentralized controller learning, very few su...
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07/10/2019