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Yong Zhang 0004
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Publications
- 2024
- [i40]Zhenan Fan, Bissan Ghaddar, Xinglu Wang, Linzi Xing, Yong Zhang, Zirui Zhou:
Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process. CoRR abs/2401.03244 (2024) - [i39]Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, Weilin Luo, Meng Lu, Yimin Huang, Zhenan Fan, Zirui Zhou, Yufei Kuang, Zhihai Wang, Zijie Geng, Yang Li, Haoyang Liu, Zhiwu An, Muming Yang, Jianshu Li, Jie Wang, Junchi Yan, Defeng Sun, Tao Zhong, Yong Zhang, Jia Zeng, Mingxuan Yuan, Jianye Hao, Jun Yao, Kun Mao:
Machine Learning Insides OptVerse AI Solver: Design Principles and Applications. CoRR abs/2401.05960 (2024) - 2023
- [j18]Changxin Liu, Zirui Zhou, Jian Pei, Yong Zhang, Yang Shi:
Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach With Linear Convergence. IEEE Trans. Autom. Control. 68(8): 4650-4665 (2023) - [c34]Mohammad Akbari, Saeed Ranjbar Alvar, Behnam Kamranian, Amin Banitalebi-Dehkordi, Yong Zhang:
ArchBERT: Bi-Modal Understanding of Neural Architectures and Natural Languages. CoNLL 2023: 87-107 - [c33]Zhenan Fan, Xinglu Wang, Oleksandr Yakovenko, Abdullah Ali Sivas, Owen Ren, Yong Zhang, Zirui Zhou:
Smart Initial Basis Selection for Linear Programs. ICML 2023: 9650-9664 - [c32]Xubo Lyu, Amin Banitalebi-Dehkordi, Mo Chen, Yong Zhang:
Asynchronous, Option-Based Multi-Agent Policy Gradient: A Conditional Reasoning Approach. IROS 2023: 7348-7353 - [c31]Saeed Ranjbar Alvar, Mohammad Akbari, David (Ming Xuan) Yue, Yong Zhang:
NFT-Based Data Marketplace with Digital Watermarking. KDD 2023: 4756-4767 - [c30]Mehdi Seyfi, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang:
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks. ECML/PKDD (4) 2023: 268-283 - [i38]Rindranirina Ramamonjison, Timothy T. L. Yu, Raymond Li, Haley Li, Giuseppe Carenini, Bissan Ghaddar, Shiqi He, Mahdi Mostajabdaveh, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang:
NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions. CoRR abs/2303.08233 (2023) - [i37]Mohsen Gholami, Mohammad Akbari, Xinglu Wang, Behnam Kamranian, Yong Zhang:
ETran: Energy-Based Transferability Estimation. CoRR abs/2308.02027 (2023) - [i36]Mohammad Akbari, Saeed Ranjbar Alvar, Behnam Kamranian, Amin Banitalebi-Dehkordi, Yong Zhang:
ArchBERT: Bi-Modal Understanding of Neural Architectures and Natural Languages. CoRR abs/2310.17737 (2023) - [i35]Mehdi Seyfi, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang:
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks. CoRR abs/2311.13843 (2023) - 2022
- [j17]Zicun Cong, Xuan Luo, Jian Pei, Feida Zhu, Yong Zhang:
Data pricing in machine learning pipelines. Knowl. Inf. Syst. 64(6): 1417-1455 (2022) - [j16]Mehdi Seyfi, Amin Banitalebi-Dehkordi, Yong Zhang:
Extending Momentum Contrast With Cross Similarity Consistency Regularization. IEEE Trans. Circuits Syst. Video Technol. 32(10): 6714-6727 (2022) - [c29]Laurent Charette, Lingyang Chu, Yizhou Chen, Jian Pei, Lanjun Wang, Yong Zhang:
Cosine Model Watermarking against Ensemble Distillation. AAAI 2022: 9512-9520 - [c28]Mohammad Akbari, Amin Banitalebi-Dehkordi, Yong Zhang:
E-LANG: Energy-Based Joint Inferencing of Super and Swift Language Models. ACL (1) 2022: 5229-5244 - [c27]Amin Banitalebi-Dehkordi, Pratik Gujjar, Yong Zhang:
AuxMix: Semi-Supervised Learning with Unconstrained Unlabeled Data. CVPR Workshops 2022: 3998-4005 - [c26]Morgan Heisler, Amin Banitalebi-Dehkordi, Yong Zhang:
SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding. ECCV (36) 2022: 610-626 - [c25]Rindra Ramamonjison, Haley Li, Timothy T. L. Yu, Shiqi He, Vishnu Rengan, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang:
Augmenting Operations Research with Auto-Formulation of Optimization Models From Problem Descriptions. EMNLP (Industry Track) 2022: 29-62 - [c24]Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang:
Improving Fairness for Data Valuation in Horizontal Federated Learning. ICDE 2022: 2440-2453 - [c23]Tianyu Zhang, Amin Banitalebi-Dehkordi, Yong Zhang:
Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch. ICPR 2022: 3105-3111 - [c22]Gursimran Singh, Lingyang Chu, Lanjun Wang, Jian Pei, Qi Tian, Yong Zhang:
Mining Minority-Class Examples with Uncertainty Estimates. MMM (1) 2022: 258-271 - [i34]Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang:
Fair and efficient contribution valuation for vertical federated learning. CoRR abs/2201.02658 (2022) - [i33]Mohammad Akbari, Amin Banitalebi-Dehkordi, Yong Zhang:
E-LANG: Energy-Based Joint Inferencing of Super and Swift Language Models. CoRR abs/2203.00748 (2022) - [i32]Laurent Charette, Lingyang Chu, Yizhou Chen, Jian Pei, Lanjun Wang, Yong Zhang:
Cosine Model Watermarking Against Ensemble Distillation. CoRR abs/2203.02777 (2022) - [i31]Saeed Ranjbar Alvar, Lanjun Wang, Jian Pei, Yong Zhang:
Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation. CoRR abs/2203.05212 (2022) - [i30]Xubo Lyu, Amin Banitalebi-Dehkordi, Mo Chen, Yong Zhang:
Multi-Agent Asynchronous Cooperation with Hierarchical Reinforcement Learning. CoRR abs/2203.15925 (2022) - [i29]Mehdi Seyfi, Amin Banitalebi-Dehkordi, Yong Zhang:
Extending Momentum Contrast with Cross Similarity Consistency Regularization. CoRR abs/2206.04676 (2022) - [i28]Mehdi Seyfi, Amin Banitalebi-Dehkordi, Yong Zhang:
Spatial Cross-Attention Improves Self-Supervised Visual Representation Learning. CoRR abs/2206.05028 (2022) - [i27]Amin Banitalebi-Dehkordi, Pratik Gujjar, Yong Zhang:
AuxMix: Semi-Supervised Learning with Unconstrained Unlabeled Data. CoRR abs/2206.06959 (2022) - [i26]Tianyu Zhang, Amin Banitalebi-Dehkordi, Yong Zhang:
Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch. CoRR abs/2206.06965 (2022) - [i25]Mohit Bajaj, Lingyang Chu, Vittorio Romaniello, Gursimran Singh, Jian Pei, Zirui Zhou, Lanjun Wang, Yong Zhang:
Revealing Unfair Models by Mining Interpretable Evidence. CoRR abs/2207.05811 (2022) - [i24]Fabrizio Pedersoli, Dryden Wiebe, Amin Banitalebi, Yong Zhang, Kwang Moo Yi:
Estimating Visual Information From Audio Through Manifold Learning. CoRR abs/2208.02337 (2022) - [i23]Morgan Heisler, Amin Banitalebi-Dehkordi, Yong Zhang:
SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding. CoRR abs/2208.07407 (2022) - [i22]Zhenan Fan, Zirui Zhou, Jian Pei, Michael P. Friedlander, Jiajie Hu, Chengliang Li, Yong Zhang:
Knowledge-Injected Federated Learning. CoRR abs/2208.07530 (2022) - [i21]Rindranirina Ramamonjison, Haley Li, Timothy T. L. Yu, Shiqi He, Vishnu Rengan, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang:
Augmenting Operations Research with Auto-Formulation of Optimization Models from Problem Descriptions. CoRR abs/2209.15565 (2022) - [i20]Gursimran Singh, Chendi Wang, Ahnaf Tazwar, Lanjun Wang, Yong Zhang:
IPProtect: protecting the intellectual property of visual datasets during data valuation. CoRR abs/2212.11468 (2022) - 2021
- [c21]Yutao Huang, Lingyang Chu, Zirui Zhou, Lanjun Wang, Jiangchuan Liu, Jian Pei, Yong Zhang:
Personalized Cross-Silo Federated Learning on Non-IID Data. AAAI 2021: 7865-7873 - [c20]Amin Banitalebi-Dehkordi, Yong Zhang:
Repaint: Improving the Generalization of Down-Stream Visual Tasks by Generating Multiple Instances of Training Examples. BMVC 2021: 122 - [c19]Mohammad Akbari, Amin Banitalebi-Dehkordi, Yong Zhang:
EBJR: Energy-Based Joint Reasoning for Adaptive Inference. BMVC 2021: 157 - [c18]Amin Banitalebi-Dehkordi, Xinyu Kang, Yong Zhang:
Model Composition: Can Multiple Neural Networks Be Combined into a Single Network Using Only Unlabeled Data? BMVC 2021: 263 - [c17]Peter Cho-Ho Lam, Lingyang Chu, Maxim Torgonskiy, Jian Pei, Yong Zhang, Lanjun Wang:
Finding Representative Interpretations on Convolutional Neural Networks. ICCV 2021: 1325-1334 - [c16]Rindra Ramamonjison, Amin Banitalebi-Dehkordi, Xinyu Kang, Xiaolong Bai, Yong Zhang:
SimROD: A Simple Adaptation Method for Robust Object Detection. ICCV 2021: 3550-3559 - [c15]Prithu Banerjee, Lingyang Chu, Yong Zhang, Laks V. S. Lakshmanan, Lanjun Wang:
Stealthy Targeted Data Poisoning Attack on Knowledge Graphs. ICDE 2021: 2069-2074 - [c14]Liang Hu, Lanjun Wang, Zirui Zhou, Zhenli Sheng, Yong Zhang:
Network-wide Traffic Signal Optimization under Connected Vehicles Environment. ITSC 2021: 2463-2470 - [c13]Amin Banitalebi-Dehkordi, Naveen Vedula, Jian Pei, Fei Xia, Lanjun Wang, Yong Zhang:
Auto-Split: A General Framework of Collaborative Edge-Cloud AI. KDD 2021: 2543-2553 - [c12]Zirui Zhou, Lingyang Chu, Changxin Liu, Lanjun Wang, Jian Pei, Yong Zhang:
Towards Fair Federated Learning. KDD 2021: 4100-4101 - [c11]Rindranirina Ramamonjison, Timothy T. L. Yu, Raymond Li, Haley Li, Giuseppe Carenini, Bissan Ghaddar, Shiqi He, Mahdi Mostajabdaveh, Amin Banitalebi-Dehkordi, Zirui Zhou, Yong Zhang:
NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions. NeurIPS (Competition and Demos) 2021: 189-203 - [c10]Mohit Bajaj, Lingyang Chu, Zi Yu Xue, Jian Pei, Lanjun Wang, Peter Cho-Ho Lam, Yong Zhang:
Robust Counterfactual Explanations on Graph Neural Networks. NeurIPS 2021: 5644-5655 - [i19]Changxin Liu, Zirui Zhou, Jian Pei, Yong Zhang, Yang Shi:
Decentralized Composite Optimization in Stochastic Networks: A Dual Averaging Approach with Linear Convergence. CoRR abs/2106.14075 (2021) - [i18]Mohit Bajaj, Lingyang Chu, Zi Yu Xue, Jian Pei, Lanjun Wang, Peter Cho-Ho Lam, Yong Zhang:
Robust Counterfactual Explanations on Graph Neural Networks. CoRR abs/2107.04086 (2021) - [i17]Rindra Ramamonjison, Amin Banitalebi-Dehkordi, Xinyu Kang, Xiaolong Bai, Yong Zhang:
SimROD: A Simple Adaptation Method for Robust Object Detection. CoRR abs/2107.13389 (2021) - [i16]Peter Cho-Ho Lam, Lingyang Chu, Maxim Torgonskiy, Jian Pei, Yong Zhang, Lanjun Wang:
Finding Representative Interpretations on Convolutional Neural Networks. CoRR abs/2108.06384 (2021) - [i15]Zicun Cong, Xuan Luo, Jian Pei, Feida Zhu, Yong Zhang:
Data Pricing in Machine Learning Pipelines. CoRR abs/2108.07915 (2021) - [i14]Amin Banitalebi-Dehkordi, Naveen Vedula, Jian Pei, Fei Xia, Lanjun Wang, Yong Zhang:
Auto-Split: A General Framework of Collaborative Edge-Cloud AI. CoRR abs/2108.13041 (2021) - [i13]Liang Hu, Jiangcheng Zhu, Zirui Zhou, Ruiqing Cheng, Xiaolong Bai, Yong Zhang:
An Optimal Resource Allocator of Elastic Training for Deep Learning Jobs on Cloud. CoRR abs/2109.03389 (2021) - [i12]Lingyang Chu, Lanjun Wang, Yanjie Dong, Jian Pei, Zirui Zhou, Yong Zhang:
FedFair: Training Fair Models In Cross-Silo Federated Learning. CoRR abs/2109.05662 (2021) - [i11]Changxin Liu, Zirui Zhou, Yang Shi, Jian Pei, Lingyang Chu, Yong Zhang:
Achieving Model Fairness in Vertical Federated Learning. CoRR abs/2109.08344 (2021) - [i10]Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang:
Improving Fairness for Data Valuation in Federated Learning. CoRR abs/2109.09046 (2021) - [i9]Mohammad Akbari, Amin Banitalebi-Dehkordi, Yong Zhang:
EBJR: Energy-Based Joint Reasoning for Adaptive Inference. CoRR abs/2110.10343 (2021) - [i8]Amin Banitalebi-Dehkordi, Yong Zhang:
Repaint: Improving the Generalization of Down-Stream Visual Tasks by Generating Multiple Instances of Training Examples. CoRR abs/2110.10366 (2021) - [i7]Amin Banitalebi-Dehkordi, Xinyu Kang, Yong Zhang:
Model Composition: Can Multiple Neural Networks Be Combined into a Single Network Using Only Unlabeled Data? CoRR abs/2110.10369 (2021) - [i6]Gursimran Singh, Lingyang Chu, Lanjun Wang, Jian Pei, Qi Tian, Yong Zhang:
Mining Minority-class Examples With Uncertainty Estimates. CoRR abs/2112.07835 (2021) - [i5]Amin Banitalebi-Dehkordi, Yong Zhang:
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 abs/2112.12251 (2021) - 2020
- [j15]Ehsan Adeli, Xiaorui Li, Dongjin Kwon, Yong Zhang, Kilian M. Pohl:
Logistic Regression Confined by Cardinality-Constrained Sample and Feature Selection. IEEE Trans. Pattern Anal. Mach. Intell. 42(7): 1713-1728 (2020) - [i4]Yutao Huang, Lingyang Chu, Zirui Zhou, Lanjun Wang, Jiangchuan Liu, Jian Pei, Yong Zhang:
Personalized Federated Learning: An Attentive Collaboration Approach. CoRR abs/2007.03797 (2020) - 2019
- [j14]Geng Chen, Bin Dong, Yong Zhang, Weili Lin, Dinggang Shen, Pew-Thian Yap:
XQ-SR: Joint x-q space super-resolution with application to infant diffusion MRI. Medical Image Anal. 57: 44-55 (2019) - [j13]Geng Chen, Bin Dong, Yong Zhang, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Denoising of Diffusion MRI Data via Graph Framelet Matching in x-q Space. IEEE Trans. Medical Imaging 38(12): 2838-2848 (2019) - 2018
- [j12]Geng Chen, Bin Dong, Yong Zhang, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space. Frontiers Neuroinformatics 12: 57 (2018) - [j11]Elena Bernardis, Yong Zhang, Ender Konukoglu, Yangming Ou, Harold S. Javitz, Leon Axel, Dimitris N. Metaxas, Benoit Desjardins, Kilian M. Pohl:
eCurves: A Temporal Shape Encoding. IEEE Trans. Biomed. Eng. 65(4): 733-744 (2018) - 2017
- [j10]Zhaosong Lu, Yong Zhang, Jian Lu:
\(\ell _p\) Regularized low-rank approximation via iterative reweighted singular value minimization. Comput. Optim. Appl. 68(3): 619-642 (2017) - [j9]Yong Zhang, Dongjin Kwon, Kilian M. Pohl:
Computing group cardinality constraint solutions for logistic regression problems. Medical Image Anal. 35: 58-69 (2017) - [c9]Geng Chen, Bin Dong, Yong Zhang, Dinggang Shen, Pew-Thian Yap:
q-Space Upsampling Using x-q Space Regularization. MICCAI (1) 2017: 620-628 - [c8]Geng Chen, Bin Dong, Yong Zhang, Dinggang Shen, Pew-Thian Yap:
Neighborhood Matching for Curved Domains with Application to Denoising in Diffusion MRI. MICCAI (1) 2017: 629-637 - 2016
- [j8]Kilian M. Pohl, Edith V. Sullivan, Torsten Rohlfing, Weiwei Chu, Dongjin Kwon, B. Nolan Nichols, Yong Zhang, Sandra A. Brown, Susan F. Tapert, Kevin Cummins, Wesley K. Thompson, Ty Brumback, Ian M. Colrain, Fiona C. Baker, Devin Prouty, Michael D. De Bellis, James T. Voyvodic, Duncan B. Clark, Claudiu V. Schirda, Bonnie J. Nagel, Adolf Pfefferbaum:
Harmonizing DTI measurements across scanners to examine the development of white matter microstructure in 803 adolescents of the NCANDA study. NeuroImage 130: 194-213 (2016) - [j7]Pew-Thian Yap, Yong Zhang, Dinggang Shen:
Multi-Tissue Decomposition of Diffusion MRI Signals via ℓ0 Sparse-Group Estimation. IEEE Trans. Image Process. 25(9): 4340-4353 (2016) - [c7]Yong Zhang, Sang Hyun Park, Kilian M. Pohl:
Joint Data Harmonization and Group Cardinality Constrained Classification. MICCAI (1) 2016: 282-290 - [c6]Pew-Thian Yap, Bin Dong, Yong Zhang, Dinggang Shen:
Tight Graph Framelets for Sparse Diffusion MRI q-Space Representation. MICCAI (3) 2016: 561-569 - 2015
- [j6]Zhaosong Lu, Yong Zhang, Xiaorui Li:
Penalty decomposition methods for rank minimization. Optim. Methods Softw. 30(3): 531-558 (2015) - [c5]Pew-Thian Yap, Yong Zhang, Dinggang Shen:
Brain Tissue Segmentation Based on Diffusion MRI Using ℓ0 Sparse-Group Representation Classification. MICCAI (3) 2015: 132-139 - [c4]Pew-Thian Yap, Yong Zhang, Dinggang Shen:
Diffusion Compartmentalization Using Response Function Groups with Cardinality Penalization. MICCAI (1) 2015: 183-190 - [c3]Pew-Thian Yap, Yong Zhang, Dinggang Shen:
Iterative Subspace Screening for Rapid Sparse Estimation of Brain Tissue Microstructural Properties. MICCAI (1) 2015: 223-230 - [c2]Yong Zhang, Kilian M. Pohl:
Solving Logistic Regression with Group Cardinality Constraints for Time Series Analysis. MICCAI (3) 2015: 459-466 - 2013
- [j5]Bin Dong, Yong Zhang:
An Efficient Algorithm for ℓ 0 Minimization in Wavelet Frame Based Image Restoration. J. Sci. Comput. 54(2-3): 350-368 (2013) - [j4]Yong Zhang, Bin Dong, Zhaosong Lu:
ℓ0 Minimization for wavelet frame based image restoration. Math. Comput. 82(282): 995-1015 (2013) - [j3]Zhaosong Lu, Yong Zhang:
Sparse Approximation via Penalty Decomposition Methods. SIAM J. Optim. 23(4): 2448-2478 (2013) - 2012
- [j2]Zhaosong Lu, Ting Kei Pong, Yong Zhang:
An alternating direction method for finding Dantzig selectors. Comput. Stat. Data Anal. 56(12): 4037-4046 (2012) - [j1]Zhaosong Lu, Yong Zhang:
An augmented Lagrangian approach for sparse principal component analysis. Math. Program. 135(1-2): 149-193 (2012) - [i3]Zhaosong Lu, Yong Zhang:
Sparse Approximation via Penalty Decomposition Methods. CoRR abs/1205.2334 (2012) - 2011
- [c1]Yong Zhang, Zhaosong Lu:
Penalty Decomposition Methods for Rank Minimization. NIPS 2011: 46-54 - [i2]Yong Zhang, Bin Dong, Zhaosong Lu:
ℓ0 Minimization for Wavelet Frame Based Image Restoration. CoRR abs/1105.2782 (2011) - 2009
- [i1]Zhaosong Lu, Yong Zhang:
An Augmented Lagrangian Approach for Sparse Principal Component Analysis. CoRR abs/0907.2079 (2009)
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