Yong Zhang

Orcid: 0000-0002-0238-0719

Affiliations:
  • Huawei Technologies Canada, Vancouver Research Center, Burnaby, Canada
  • Colin Artificial Intelligence Laboratory, Richmond, Canada
  • Stanford University, Department of Psychiatry, Stanford, CA, USA (2014 - 2016)
  • Simon Fraser University, Department of Mathematics, Burnaby, Canada (PhD 2014)


According to our database1, Yong Zhang authored at least 69 papers between 2011 and 2024.

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

Timeline

Legend:

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Bibliography

2024
Machine Learning Insides OptVerse AI Solver: Design Principles and Applications.
CoRR, 2024

Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process.
CoRR, 2024

2023
Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach With Linear Convergence.
IEEE Trans. Autom. Control., August, 2023

ETran: Energy-Based Transferability Estimation.
CoRR, 2023

Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

NFT-Based Data Marketplace with Digital Watermarking.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Asynchronous, Option-Based Multi-Agent Policy Gradient: A Conditional Reasoning Approach.
IROS, 2023

Smart Initial Basis Selection for Linear Programs.
Proceedings of the International Conference on Machine Learning, 2023

ArchBERT: Bi-Modal Understanding of Neural Architectures and Natural Languages.
Proceedings of the 27th Conference on Computational Natural Language Learning, 2023

2022
Extending Momentum Contrast With Cross Similarity Consistency Regularization.
IEEE Trans. Circuits Syst. Video Technol., 2022

Data pricing in machine learning pipelines.
Knowl. Inf. Syst., 2022

IPProtect: protecting the intellectual property of visual datasets during data valuation.
CoRR, 2022

Knowledge-Injected Federated Learning.
CoRR, 2022

Estimating Visual Information From Audio Through Manifold Learning.
CoRR, 2022

Revealing Unfair Models by Mining Interpretable Evidence.
CoRR, 2022

Spatial Cross-Attention Improves Self-Supervised Visual Representation Learning.
CoRR, 2022

Multi-Agent Asynchronous Cooperation with Hierarchical Reinforcement Learning.
CoRR, 2022

Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation.
CoRR, 2022

Fair and efficient contribution valuation for vertical federated learning.
CoRR, 2022

Mining Minority-Class Examples with Uncertainty Estimates.
Proceedings of the MultiMedia Modeling - 28th International Conference, 2022

Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Improving Fairness for Data Valuation in Horizontal Federated Learning.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Augmenting Operations Research with Auto-Formulation of Optimization Models From Problem Descriptions.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: EMNLP 2022 - Industry Track, Abu Dhabi, UAE, December 7, 2022

SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding.
Proceedings of the Computer Vision - ECCV 2022, 2022

AuxMix: Semi-Supervised Learning with Unconstrained Unlabeled Data.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

E-LANG: Energy-Based Joint Inferencing of Super and Swift Language Models.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Cosine Model Watermarking against Ensemble Distillation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
ML4CO: Is GCNN All You Need? Graph Convolutional Neural Networks Produce Strong Baselines For Combinatorial Optimization Problems, If Tuned and Trained Properly, on Appropriate Data.
CoRR, 2021

Improving Fairness for Data Valuation in Federated Learning.
CoRR, 2021

Achieving Model Fairness in Vertical Federated Learning.
CoRR, 2021

FedFair: Training Fair Models In Cross-Silo Federated Learning.
CoRR, 2021

An Optimal Resource Allocator of Elastic Training for Deep Learning Jobs on Cloud.
CoRR, 2021

NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions.
Proceedings of the NeurIPS 2022 Competition Track, 2021

Robust Counterfactual Explanations on Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Fair Federated Learning.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Auto-Split: A General Framework of Collaborative Edge-Cloud AI.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Network-wide Traffic Signal Optimization under Connected Vehicles Environment.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

Stealthy Targeted Data Poisoning Attack on Knowledge Graphs.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

SimROD: A Simple Adaptation Method for Robust Object Detection.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Finding Representative Interpretations on Convolutional Neural Networks.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Model Composition: Can Multiple Neural Networks Be Combined into a Single Network Using Only Unlabeled Data?
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Repaint: Improving the Generalization of Down-Stream Visual Tasks by Generating Multiple Instances of Training Examples.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

EBJR: Energy-Based Joint Reasoning for Adaptive Inference.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Personalized Cross-Silo Federated Learning on Non-IID Data.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Logistic Regression Confined by Cardinality-Constrained Sample and Feature Selection.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Personalized Federated Learning: An Attentive Collaboration Approach.
CoRR, 2020

2019
Denoising of Diffusion MRI Data via Graph Framelet Matching in x-q Space.
IEEE Trans. Medical Imaging, 2019

XQ-SR: Joint <i>x</i>-<i>q</i> space super-resolution with application to infant diffusion MRI.
Medical Image Anal., 2019

2018
eCurves: A Temporal Shape Encoding.
IEEE Trans. Biomed. Eng., 2018

Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space.
Frontiers Neuroinformatics, 2018

2017
Computing group cardinality constraint solutions for logistic regression problems.
Medical Image Anal., 2017

\(\ell _p\) Regularized low-rank approximation via iterative reweighted singular value minimization.
Comput. Optim. Appl., 2017

Neighborhood Matching for Curved Domains with Application to Denoising in Diffusion MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

q-Space Upsampling Using x-q Space Regularization.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

2016
Multi-Tissue Decomposition of Diffusion MRI Signals via ℓ<sub>0</sub> Sparse-Group Estimation.
IEEE Trans. Image Process., 2016

Harmonizing DTI measurements across scanners to examine the development of white matter microstructure in 803 adolescents of the NCANDA study.
NeuroImage, 2016

Joint Data Harmonization and Group Cardinality Constrained Classification.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

Tight Graph Framelets for Sparse Diffusion MRI q-Space Representation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015
Penalty decomposition methods for rank minimization.
Optim. Methods Softw., 2015

Solving Logistic Regression with Group Cardinality Constraints for Time Series Analysis.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Brain Tissue Segmentation Based on Diffusion MRI Using ℓ0 Sparse-Group Representation Classification.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Iterative Subspace Screening for Rapid Sparse Estimation of Brain Tissue Microstructural Properties.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

Diffusion Compartmentalization Using Response Function Groups with Cardinality Penalization.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

2013
Sparse Approximation via Penalty Decomposition Methods.
SIAM J. Optim., 2013

ℓ<sub>0</sub> Minimization for wavelet frame based image restoration.
Math. Comput., 2013

An Efficient Algorithm for ℓ 0 Minimization in Wavelet Frame Based Image Restoration.
J. Sci. Comput., 2013

2012
An augmented Lagrangian approach for sparse principal component analysis.
Math. Program., 2012

An alternating direction method for finding Dantzig selectors.
Comput. Stat. Data Anal., 2012

2011
Penalty Decomposition Methods for Rank Minimization.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011


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