Xuanqing Liu

According to our database1, Xuanqing Liu authored at least 22 papers between 2017 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2021
Building Trustworthy Machine Learning Models.
PhD thesis, 2021

Label Disentanglement in Partition-based Extreme Multilabel Classification.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Evaluations and Methods for Explanation through Robustness Analysis.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers.
CoRR, 2020

Improving the Speed and Quality of GAN by Adversarial Training.
CoRR, 2020

Gradient Boosting Neural Networks: GrowNet.
CoRR, 2020

Provably Robust Metric Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Encode Position for Transformer with Continuous Dynamical Model.
Proceedings of the 37th International Conference on Machine Learning, 2020

How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
GraphDefense: Towards Robust Graph Convolutional Networks.
CoRR, 2019

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning.
CoRR, 2019

Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective.
CoRR, 2019

Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise.
CoRR, 2019

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network.
Proceedings of the 7th International Conference on Learning Representations, 2019

Rob-GAN: Generator, Discriminator, and Adversarial Attacker.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient.
CoRR, 2018

From Adversarial Training to Generative Adversarial Networks.
CoRR, 2018

Fast Variance Reduction Method with Stochastic Batch Size.
Proceedings of the 35th International Conference on Machine Learning, 2018

Towards Robust Neural Networks via Random Self-ensemble.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
An inexact subsampled proximal Newton-type method for large-scale machine learning.
CoRR, 2017


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