Publications

C. Liu, Z. Zhou, J. Pei, Y. Zhang, and Y. Shi. "Decentralized composite optimization in stochastic networks: a dual averaging approach with linear convergence".  IEEE Transactions on Automatic Control, 2022.

M. Seyfi, A. Banitalebi-Dehkordi, and Y. Zhang. "Extending momentum contrast with cross similarity consistency regularization".  IEEE Transactions on Circuits and Systems for Video Technology, 2022

Z. Cong, X. Luo, J. Pei, F. Zhu, and Y. Zhang. "Data pricing in machine learning pipelines".  Knowledge and Information Systems, Springer-Verlag, 2022.

E. Adeli, X. Li, D. Kwon, Y. Zhang and Kilian Pohl. "Logistic regression confined by cardinality-constrained sample and feature selection". IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(7):1713-1728, 2020.

G. Chen, D. Bing, Y. Zhang, W. Lin, D. Shen, and P. T. Yap. "XQ-SR: Joint x-q space super-resolution with application to infant diffusion MRI". Medical Image Analysis, 57:44-55, 2019.

G. Chen, D. Bing, Y. Zhang, W. Lin, D. Shen, and P. T. Yap. "Denoising of diffusion MRI data via graph framelet matching in x-q space." IEEE Transactions on Medical Imaging, 38(12):2838-2848, 2019.

 G. Chen, J. Zhang, Y. Zhang, D. Bing, D. Shen, and P. T. Yap. "Multi-channel framelet denoising of diffusion-weighted images". PloS One, 2019.

S. H. Park, Y. Zhang, D. Kwon, Q. Zhao, N. M. Zahr, A. Pfefferbaum, E. V. Sullivan and K. M. Pohl. "Alcohol use effects on adolescent brain development revealed by simultaneously removing confounding factors, identifying morphometric patterns, and classifying individuals".  Scientific reports, 8:8297, 2018.

  G. Chen, B. Dong, Y. Zhang, W. Lin, D. Shen, and P. T. Yap. "Angular upsampling in infant diffusion MRI using neighborhood matching in x-q space". Frontiers in neuroinformatics, 12:57, 2018.

Z. Lu, Y. Zhang, and J. Lu. "Lp regularized low-rank approximation via iterative reweighted singular value minimization". Journal of Computational Optimization and Applications, 68(3):619--642, 2017.

E. Bernardis, Y. Zhang, B. Desjardins, E. Konukoglu, Y. Ou, H. S. Javitz, D. Metaxas, and  K. M. Pohl. "eCurves: A temporal shape encoding". IEEE Transactions on Biomedical Engineering, 65(4):733-744, 2017.

Y. Zhang, D. Kwon, P. Esmaeili-Firidouni, A. Pfefferbaum, E. V. Sullivan, H. Javitz, V. Valcour and K. M. Pohl. "Extracting Patterns of Morphometry Distinguishing HIV Associated Neurodegeneration from Mild Cognitive Impairment via Group Cardinality Constrained Classification". Human Brain Mapping, 37(12):4523--4538, 2016.

P. T. Yap, Y. Zhang, and D. Shen. "Diffusion Signal Compartmentalization via L0 Sparse-Group Estimation". IEEE Transactions on Image Processing, 25(9): 4340--4353, 2016.

Y. Zhang, D. Kwon and K. M. Pohl. "Computing group cardinality constraint solutions for logistic regression problems". Medical Image Analysis, 35:58–69, 2016.

 K. M. Pohl, E. V. Sullivan, T. Rohlfing, W. Chu, D. Kwon, B. N. Nichols, Y. Zhang, S. A. Brown, S. F. Tapert, K. Cummins, W. K. Thompson, T. Brumback, I. M. Colrain, F. C. Baker, D. Prouty, M. D. De Bellis, J. T. Voyvodic, D. B. Clark, C. Schirda, B. J. Nagel, A. 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.

Z. Lu, Y. Zhang, and X. Li. "Penalty decomposition methods for rank minimization". Optimization Methods and Software, 30(3):431–558, 2014. PDF

Z. Lu and Y. Zhang. "Sparse approximation via penalty decomposition methods". SIAM Journal on Optimization, 23(4):2448-2478, 2013. PDF

B. Dong and Y. Zhang. "An efficient algorithm for l0 minimization in wavelet frame based image restoration". Journal of Scientific Computing, 54(2–3): 350–368, 2013. PDF

Y. Zhang, B. Dong and Z. Lu. "l0 minimization of wavelet frame based image restoration". Mathematics of Computation, 82: 995–1015, 2013. PDF

Z. Lu, T. K. Pong, and Y. Zhang. "An alternating direction method for finding Dantzig selectors". Computational Statistics & Data Analysis, 56(12): 4037–4946, 2012. PDF

Z. Lu and Y. Zhang. "An augmented Lagrangian approach for sparse principal component analysis". Mathematical Programming, 135: 149–193, 2012. PDF

M. Gholami, M. Akbari, T. Hu, V. Masrani, Z. J. Wang, Y. Zhang. "GOLD: Generalized Knowledge Distillation via Out-of-Distribution-Guided Language Data Generation". Accepted by NAACL 2024.

L. Xing, X. Wang, Y. Feng, Z. Fan, J. Xiong, Z. Guo, X. Fu, R. Ramamonjison, M. Mostajabdaveh, X. Han, Z. Zhou and Y. Zhang. "Towards Human-aligned Evaluation for Linear Programming Word Problems". Accepted by LREC-COLING 2024.

Z. Fan, H. Fang, Z. Zhou, J. Pei, M. Friedlander, Y. Zhang. "Fair and Efficient Contribution Valuation for Vertical Federated Learning". Accepted by ICLR2024.

M. Akbari, S. Ranjbar Alvar, B. Kamranian, A. Banitalebi-Dehkordi, Y. Zhang. "ArchBERT: Bi-Modal Understanding of Neural Architectures and Natural Languages". Accepted by CoNLL2023.

M. Gholami, M. Akbari, X. Wang, B. Kamranian, Y. Zhang. "ETran: Energy-Based Transferability Estimation". Accepted by ICCV2023.

X. Lyu, A. Banitalebi-Dehkordi, M. Chen, Y. Zhang. "Asynchronous, Option-Based Multi-Agent Policy Gradient: A Conditional Reasoning Approach". Accepted by IROS2023.

M. Seyfi, A. Banitalebi-Dehkordi, Z. Zhou and Y. Zhang. "Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks". Accepted by ECML2023.

Z. Fan, X. Wang, O. Yakovenko, A. Ali Sivas, O. Ren, Y. Zhang, and Z. Zhou. "Smart Initial Basis Selection for Linear Programs". Accepted by ICML2023.

S. Ranjbar Alvar, M. Akbari, D. Yue, and Y. Zhang. "NFT-Based Data Marketplace with Digital Watermarking". Accepted by KDD ADS Track, 2023.

R. Ramamonjison, T. Yu, L. Xing, M. Mostajabdaveh, X. Li, X. Fu, X. Han, Y. Chen, R. Li, K. Mao and Y. Zhang. "TeX2Solver: a Hierarchical Semantic Parsing of TeX Document into Code for an Assistive Optimization Modeling Application". Accepted by ACL Demo Track, 2023.

R. Ramamonjison, H. Li, T. Yu, S. He, V. Rengan, A. Banitalebi-Dehkordi, Z. Zhou and Y. Zhang. "Augmenting Operations Research with Auto-Formulation of Optimization Models From Problem Descriptions". Accepted by EMNLP2022 Industry Track.

M. Heisler, A. Banitalebi-Dehkordi and Y. Zhang. "SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding". Accepted by ECCV2022.

T. Zhang, A. Banitalebi-Dehkordi and Y. Zhang. "Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch". Accepted by ICPR 2022 (Oral acceptance).

A. Banitalebi-Dehkordi, P. Gujjar and Y. Zhang.  "AuxMix: Semi-Supervised Learning With Unconstrained Unlabeled Data". In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, New Orleans, Louisiana, June 19-24 2022.

G. Singh, L. Chu, L. Wang, J. Pei, and Y. Zhang. "Mining Minority-class Examples with Uncertainty Estimates". In Proceedings of the Twenty-eighth International Conference on Multimedia Modeling (MMM'22), Qui Nhon, Vietnam, June 6-10, 2022.  Link  (Free registration is required)

M. Akbari, A. Banitalebi-Dehkordi, and Y. Zhang. "E-LANG: Energy-based Joint Inferencing of Super and Swift Language Models". In Proceedings of 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022), Dublin, Ireland, May 22-27, 2022 (Oral acceptance)  Link  (Free registration is required)

Z. Fan, H. Fang, Z. Zhou, J. Pei, M. Friedlander, C. Liu and Y.Zhang. "Improving Fairness for Data Valuation in Horizontal Federated Learning". In Proceedings of 38th IEEE International Conference on Data Engineering (ICDE 2022), May 9-12, 2022.

L. Charette, L. Chu, Y. Chen, J. Pei, L. Wang, and Y. Zhang. "Cosine Model Watermarking Against Ensemble Distillation". In Proceedings of the Thirty-sixth AAAI Conference on Artificial Intelligence (AAAI’22), Vancouver, BC, Canada, February 22 - March 1, 2022. (Acceptance rate: 15%)  Link  (Free registration is required) (Oral acceptance)

A. Banitalebi-Dehkordi and Y. Zhang.  "Repaint: Improving the Generalization of Down-Stream Visual Tasks by Generating Multiple Instances of Training Examples". In Proceedings of  British Machine Vision Conference 2021. (Acceptance rate: 437/1206)

M. Akbari, A. Banitalebi-Dehkordi and Y. Zhang.  "EBJR: Energy-Based Joint Reasoning for Adaptive Inference". In Proceedings of  British Machine Vision Conference 2021. (Acceptance rate: 437/1206)  Link  (Free registration is required)

A. Banitalebi-Dehkordi, X. Kang and Y. Zhang."Model Composition: Can Multiple Neural Networks Be Combined into a Single Network Using Only Unlabeled Data?". In Proceedings of  British Machine Vision Conference 2021. (Acceptance rate: 437/1206) 

M. Bajaj, L. Chu,Z. Y. Xue, J. Pei, L. Wang, C. H. Lam, Y. Zhang. "Robust Counterfactual Explanations on Graph Neural Networks". In Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS’21), December 6-14, 2021. (Acceptance rate:  26%)  Link  (Free registration is required)

L. Hu, L. Wang, Z. Zhou, Z. Sheng, Y. Zhang. "Network-wide Traffic Signal Optimization under Connected Vehicles".  In Proceedings of the 24th IEEE Intelligent Transportation Systems Conference (ITSC 2021), September 19-22, 2021.

C. H. Lam, L. Chu, M. Torgonskiy, J. Pei, Y. Zhang, and L. Wang. "Finding Representative Interpretations on Convolutional Neural Networks". In Proceedings of the 2021 IEEE International Conference on Computer Vision (ICCV’21), Virtual, October 11-17, 2021. (Acceptance rate: 1617/6236)  Link  (Free registration is required)

R.  Ramamonjison,  A. Banitalebi-Dehkordi, X. Kang, X. Bai, and Y. Zhang.  "SimROD: A Simple Adaptation Method for Robust Object Detection". In Proceedings of the 2021 IEEE International Conference on Computer Vision (ICCV’21), Virtual, October 11-17, 2021. (Oral acceptance rate: 210/6236)  Link  (Free registration is required)

A. Banitalebi-Dehkordi, N. Vedula, J. Pei, F. Xia, L. Wang, and Y. Zhang. "Auto-Split: A General Framework of Collaborative Edge-Cloud AI". In Proceedings of the Twenty-seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’21), Singapore, August 14-18, 2021.  (Acceptance rate: 138/705)   Link  (Free registration is required)

Y. Huang, L. Chu, Z. Zhou, L. Wang, J. Liu, J. Pei, and Y. Zhang. "Personalized Cross-Silo Federated Learning on Non-IID Data". In Proceedings of the Thirty-fifth AAAI Conference on Artificial Intelligence (AAAI’21), Online, February 2-9, 2021.  (Acceptance rate: 1692/9034)  Link  (Free registration is required)

B. Banerjee, L. Chu, Y. Zhang, L. Lakshmanan and L. Wang. "Stealthy targeted data poisoning attack on knowledge graphs". The annual IEEE International Conference on Data Engineering  (ICDE), 2021.

G. Chen, B. Dong, Y. Zhang, D. Shen, and  P. T. Yap. "q-Space upsampling using x-q space regularization". Medical Image Computing and Computer-Assisted Intervention Conference  (MICCAI), 2017.

G. Chen, B. Dong, Y. Zhang, D. Shen, and  P. T. Yap. "Neighborhood matching of unstructured manifold-distributed data with application to denoising in diffusion MRI". Medical Image Computing and Computer-Assisted Intervention Conference  (MICCAI), 2017.

Y. Zhang, S. H. Park and K. Pohl. "Joint data harmonization and group cardinality constrained classification". Medical Image Computing and Computer-Assisted Intervention Conference (MICCAI), 2016. 

P. T. Yap, B. Dong, Y. Zhang and D. Shen. "Tight graph framelets for sparse diffusion MRI q-space representation". Medical Image Computing and Computer-Assisted Intervention Conference (MICCAI), 2016.

Y. Zhang and K. Pohl. "Solving logistic regression with group cardinality constraints for time series analysis". Medical Image Computing and Computer-Assisted Intervention Conference (MICCAI), 2015. Link

P. T. Yap, Y. Zhang and D. Shen. "Brain tissue segmentation based on diffusion MRI using L0 sparse-group representation classification". Medical Image Computing and Computer-Assisted Intervention Conference (MICCAI), 2015.

P. T. Yap, Y. Zhang and D. Shen. "Diffusion compartmentalization using response function groups with cardinality penalization". Medical Image Computing and Computer-Assisted Intervention Conference (MICCAI), 2015.

P. T. Yap, Y. Zhang and D. Shen. "Iterative subspace screening for rapid sparse estimation of micro-structural properties". Medical Image Computing and Computer-Assisted Intervention Conference (MICCAI), 2015.

Z. Lu and Y. Zhang, "Penalty decomposition methods for rank minimization". Proceedings of Neural Information Processing Systems (NeurIPS), 46–54, 2011. Link

J. Wang, G. Carenini, D. D'Ambrosio, B. Ghaddar, Y. Zhang, Z. Zhou, Z. Fan. " Artificial Intelligence for Operations Research". AAAI 2024 Workshop, Vancouver, Canada. Link 

Z. Zhou, L. Chu, C. Liu, L. Wang, J Pei,  and Y. Zhang. "Towards Fair Federated Learning". In Proceedings of the Twenty-seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’21), Singapore, August 14-18, 2021.   Link

R. Ramamonjison, T. Yu, R. Li, H. Li, G. Carenini, B. Ghaddar, S. He, M. Mostajabdaveh, A. Banitalebi-Dehkordi, Z. Zhou, Y. Zhang. "NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions". Competition in  Neural Information Processing Systems, New Orleans, November 28 - December 4, 2022.  Link