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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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08/25/2020
GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework
Generative adversarial networks (GANs) have gained increasing popularity...
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10/24/2019
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries
Zero-shot learning (ZSL) has received extensive attention recently espec...
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10/24/2019
Hierarchical Prototype Learning for Zero-Shot Recognition
Zero-Shot Learning (ZSL) has received extensive attention and successes ...
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10/14/2019
Learning Sparsity and Quantization Jointly and Automatically for Neural Network Compression via Constrained Optimization
Deep Neural Networks (DNNs) are widely applied in a wide range of usecas...
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09/25/2019
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions
Graph node embedding aims at learning a vector representation for all no...
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02/10/2019
Adversarially Trained Model Compression: When Robustness Meets Efficiency
The robustness of deep models to adversarial attacks has gained signific...
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05/28/2018
GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning
Graph embedding is a central problem in social network analysis and many...
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03/21/2017
