Xuanqing Liu

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 32

Top Topics

Reduction Method

Nearest Neighbor Classifiers

Top Venues

Publications

Xuanqing Liu, Luyang Kong, Runhui Wang, Patrick Song, Austin Nevins, Henrik Johnson, Nimish Amlathe, Davor Golac
GRAM: Generative Retrieval Augmented Matching of Data Schemas in the Context of Data Security. CoRR (2024)
Xuanqing Liu, Runhui Wang, Yang Song, Luyang Kong
GRAM: Generative Retrieval Augmented Matching of Data Schemas in the Context of Data Security. KDD (2024)
Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, Dacheng Tao
Stochastic Optimization for Non-convex Problem with Inexact Hessian Matrix, Gradient, and Function. CoRR (2023)
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Kumar Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
Evaluations and Methods for Explanation through Robustness Analysis. ICLR (2021)
Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
Label Disentanglement in Partition-based Extreme Multilabel Classification. NeurIPS (2021)
Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
Label Disentanglement in Partition-based Extreme Multilabel Classification. CoRR (2021)
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
Evaluations and Methods for Explanation through Robustness Analysis. CoRR (2020)
Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
Learning to Encode Position for Transformer with Continuous Dynamical Model. CoRR (2020)
Sarkhan Badirli, Xuanqing Liu, Zhengming Xing, Avradeep Bhowmik, Sathiya S. Keerthi
Gradient Boosting Neural Networks: GrowNet. CoRR (2020)
Jiachen Zhong, Xuanqing Liu, Cho-Jui Hsieh
Improving the Speed and Quality of GAN by Adversarial Training. CoRR (2020)
Yuanhao Xiong, Xuanqing Liu, Li-Cheng Lan, Yang You, Si Si, Cho-Jui Hsieh
How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers. CoRR (2020)
Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh
Provably Robust Metric Learning. NeurIPS (2020)
Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework. CVPR (2020)
Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
Learning to Encode Position for Transformer with Continuous Dynamical Model. ICML (2020)
Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh
Provably Robust Metric Learning. CoRR (2020)
Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. CoRR (2019)
Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise. CoRR (2019)
Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, Cho-Jui Hsieh
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning. CoRR (2019)
Lu Wang, Xuanqing Liu, Jinfeng Yi, Zhi-Hua Zhou, Cho-Jui Hsieh
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective. CoRR (2019)
Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network. ICLR (Poster) (2019)
Xuanqing Liu, Cho-Jui Hsieh
Rob-GAN: Generator, Discriminator, and Adversarial Attacker. CVPR (2019)
Xiaoyun Wang, Xuanqing Liu, Cho-Jui Hsieh
GraphDefense: Towards Robust Graph Convolutional Networks. CoRR (2019)
Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. KDD (2019)
Xuanqing Liu, Si Si, Jerry Zhu, Yang Li, Cho-Jui Hsieh
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning. NeurIPS (2019)
Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network. CoRR (2018)
Xuanqing Liu, Cho-Jui Hsieh
From Adversarial Training to Generative Adversarial Networks. CoRR (2018)
Xuanqing Liu, Cho-Jui Hsieh
Fast Variance Reduction Method with Stochastic Batch Size. CoRR (2018)
Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh
Towards Robust Neural Networks via Random Self-ensemble. ECCV (7) (2018)
Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, Dacheng Tao
Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient. CoRR (2018)
Xuanqing Liu, Cho-Jui Hsieh
Fast Variance Reduction Method with Stochastic Batch Size. ICML (2018)
Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh
Towards Robust Neural Networks via Random Self-ensemble. CoRR (2017)
Xuanqing Liu, Cho-Jui Hsieh, Jason D. Lee, Yuekai Sun
An inexact subsampled proximal Newton-type method for large-scale machine learning. CoRR (2017)