resnet-32
Towards Robust Detection of Adversarial Examples
Tianyu Pang, Chao Du, Yinpeng Dong, Jun Zhu
Neural Information Processing Systems http://nips.cc/
Technology:
Collaborative Learning for Deep Neural Networks
When training deep neural networks, we must confront the challenges ofgeneral nonconvexoptimization problems.
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.71)
The Elastic Lottery Ticket Hypothesis
Work was done when the author interned at Microsoft.
Genre:
- Contests & Prizes (0.60)
- Research Report > New Finding (0.46)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
Technology:
- Information Technology > Artificial Intelligence > Machine Learning (1.00)
- Information Technology > Communications > Mobile (0.69)
Adaptive Gradient Quantization for Data-Parallel SGD
Let (r)=( r ` (r))/(` (r) +1 ` (r))betherelativedistanceofr to level (r)+ 1. Wedefinetherandomvariableh(r)suchthath(r)= ` (r) withprobability1 (r) andh(r)= ` (r) +1withprobability (r).
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- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.30)
Towards Robust Detection of Adversarial Examples
Tianyu Pang, Chao Du, Yinpeng Dong, Jun Zhu
Although the recent progress is substantial, deep learning methods can be vulnerable to the maliciously generated adversarial examples.
Technology:
Adaptive Gradient Quantization for Data-Parallel SGD
These schemes are often heuristic and fixed over the course of training.
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- North America > Canada > Ontario > Toronto (0.14)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Europe > Russia (0.04)
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Technology:
Country: North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)