Zheng Xu

According to our database1, Zheng Xu authored at least 37 papers between 2012 and 2019.

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

Timeline

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Bibliography

2019
Adversarial Training for Free!
CoRR, 2019

The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent.
CoRR, 2019

2018
Domain Generalization and Adaptation Using Low Rank Exemplar SVMs.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Universal Adversarial Training.
CoRR, 2018

The Effectiveness of Instance Normalization: a Strong Baseline for Single Image Dehazing.
CoRR, 2018

Learning to Cluster for Proposal-Free Instance Segmentation.
CoRR, 2018

Visualizing the Loss Landscape of Neural Nets.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning to Cluster for Proposal-Free Instance Segmentation.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Stabilizing Adversarial Nets with Prediction Methods.
Proceedings of the 6th International Conference on Learning Representations, 2018

Training Shallow and Thin Networks for Acceleration via Knowledge Distillation with Conditional Adversarial Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

Strong Baseline for Single Image Dehazing with Deep Features and Instance Normalization.
Proceedings of the British Machine Vision Conference 2018, 2018

Training Student Networks for Acceleration with Conditional Adversarial Networks.
Proceedings of the British Machine Vision Conference 2018, 2018

Towards Perceptual Image Dehazing by Physics-Based Disentanglement and Adversarial Training.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Visualizing the Loss Landscape of Neural Nets.
CoRR, 2017

Learning Loss for Knowledge Distillation with Conditional Adversarial Networks.
CoRR, 2017

Stabilizing Adversarial Nets With Prediction Methods.
CoRR, 2017

Training Quantized Nets: A Deeper Understanding.
CoRR, 2017

Adaptive Consensus ADMM for Distributed Optimization.
CoRR, 2017

Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation.
CoRR, 2017

Exploring Financial Relationships Using Probabilistic Topic Models (Demonstration Paper).
Proceedings of the 3rd International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets, 2017

Training Quantized Nets: A Deeper Understanding.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Adaptive Consensus ADMM for Distributed Optimization.
Proceedings of the 34th International Conference on Machine Learning, 2017

Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Adaptive ADMM with Spectral Penalty Parameter Selection.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Scalable Classifiers with ADMM and Transpose Reduction.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Adaptive ADMM with Spectral Penalty Parameter Selection.
CoRR, 2016

Exploiting Lists of Names for Named Entity Identification of Financial Institutions from Unstructured Documents.
CoRR, 2016

Training Neural Networks Without Gradients: A Scalable ADMM Approach.
CoRR, 2016

Non-negative Factorization of the Occurrence Tensor from Financial Contracts.
CoRR, 2016

An Empirical Study of ADMM for Nonconvex Problems.
CoRR, 2016

Training Neural Networks Without Gradients: A Scalable ADMM Approach.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Probabilistic Financial Community Models with Latent Dirichlet Allocation for Financial Supply Chains.
Proceedings of the Second International Workshop on Data Science for Macro-Modeling, 2016

resMBS: Constructing a Financial Supply Chain from Prospectus.
Proceedings of the Second International Workshop on Data Science for Macro-Modeling, 2016

2015
Exploiting Low-rank Structure for Discriminative Sub-categorization.
Proceedings of the British Machine Vision Conference 2015, 2015

2014
Exploiting Low-Rank Structure from Latent Domains for Domain Generalization.
Proceedings of the Computer Vision - ECCV 2014, 2014

2013
Mining visualness.
Proceedings of the 2013 IEEE International Conference on Multimedia and Expo, 2013

2012
Towards indexing representative images on the web.
Proceedings of the 20th ACM Multimedia Conference, MM '12, Nara, Japan, October 29, 2012


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