Our group actively publishes in the fields of machine learning, computer vision, and interdisciplinary data science. Below are a list of recent and selected papers. A mark * denotes the author to be a VITA student or Dr. Wang's mentee. An up-to-date full paper list can be found here.

Journal Paper

  • Z. Wu*, H. Wang*, Z. Wang, H. Jin, and Z. Wang
    “Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset”
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020. [Paper] [Code]
  • Y. Yuan*, W. Yang, W. Ren, J Liu, W. J. Scheirer, and Z. Wang, et. al.
    “Advancing Image Understanding in Poor Visibility Environments: A Collective Benchmark Study”
    IEEE Transactions on Image Processing (TIP), 2020. [Paper]
  • M. Karimi, D. Wu, Z. Wang and Y. Shen
    “DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks”
    Oxford Bioinformatics, 2019. [Paper] [Code]
  • R. G. VidalMata, ... Y. Yuan*, J. Wu*, Z. Wang, ... et. al.
    “Bridging the Gap Between Computational Photography and Visual Recognition”
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020. [Paper]
  • Y. Wang*, J. Shen*, T. Hu*, T. Nguyen, R. Baraniuk, Z. Wang, and Y. Lin
    “Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference”
    IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2020. [Paper]
  • B. Li*, W. Ren, D. Fu, D. Tao, D. Feng, W. Zeng, and Z. Wang
    “Benchmarking Single Image Dehazing and Beyond”
    IEEE Transactions on Image Processing (TIP), vol. 28, no. 1, pp. 492-505, 2019. [Paper] [Project Page]

Conference Paper

  • T. Chen*, W. Zhang, J. Zhou, S. Chang, S. Liu, L. Amini, and Z. Wang
    “Training Stronger Baselines for Learning to Optimize”
    Advances in Neural Information Processing Systems (NeurIPS), 2020. (Spotlight Oral) [Paper] [Code]
  • H. Wang*, T. Chen*, S. Gui, T. Hu*, J. Liu, and Z. Wang
    “Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free”
    Advances in Neural Information Processing Systems (NeurIPS), 2020. [Paper] [Code]
  • T. Chen*, J. Frankle, S. Chang, S. Liu, Y. Zhang, Z. Wang, and M. Carbin
    “The Lottery Ticket Hypothesis for Pre-trained BERT Networks”
    Advances in Neural Information Processing Systems (NeurIPS), 2020. [Paper] [Code]
  • X. Chen*, Z. Wang, S. Tang, and K. Muandet
    “MATE: Plugging in Model Awareness to Task Embedding for Meta Learning”
    Advances in Neural Information Processing Systems (NeurIPS), 2020. [Paper] [Code]
  • Z. Jiang*, T. Chen*, T. Chen, and Z. Wang
    “Robust Pre-Training by Adversarial Contrastive Learning”
    Advances in Neural Information Processing Systems (NeurIPS), 2020. [Paper] [Code]
  • Y. You*, T. Chen*, Y. Sui, T. Chen, Z. Wang, and Y. Shen
    “Graph Contrastive Learning with Augmentations”
    Advances in Neural Information Processing Systems (NeurIPS), 2020. [Paper] [Code]
  • H. You, X. Chen*, Y. Zhang, C. Li, S. Li, Z. Liu, Z. Wang, and Y. Lin
    “ShiftAddNet: A Hardware-Inspired Deep Network”
    Advances in Neural Information Processing Systems (NeurIPS), 2020. [Paper] [Code]
  • Y. Fu, H. You, Y. Zhao, Y. Wang, C. Li, K. Gopalakrishnan, Z. Wang, and Y. Lin
    “FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training”
    Advances in Neural Information Processing Systems (NeurIPS), 2020. [Paper] [Code]
  • Z. Wu*, D. Hoang*, S. Lin, Y. Xie, L. Chen, Y. Lin, Z. Wang, and W. Fan
    “MM-Hand: 3D-Aware Multi-Modal Guided Hand Generation for 3D Hand Pose Synthesis”
    ACM International Conference on Multimedia (ACM MM), 2020. [Paper] [Code]
  • H. Wang*, S. Gui, H. Yang, J. Liu, and Z. Wang
    “GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework”
    European Conference on Computer Vision (ECCV), 2020. (Spotlight Oral) [Paper][Code]
  • S. Yang*, Z. Wang, J. Liu, and Z. Guo
    “Deep Plastic Surgery: Robust and Controllable Image Editing with Human-Drawn Sketches”
    European Conference on Computer Vision (ECCV), 2020. [Paper] [Code]
  • C. Li, T. Chen*, H. You, Z. Wang, and Y Lin
    “HALO: Hardware-Aware Learning to Optimize”
    European Conference on Computer Vision (ECCV), 2020. [Paper] [Code]
  • Z. Huo, A. PakBin, X. Chen*, N. Hurley, Y. Yuan*, X. Qian, Z. Wang, S. Huang, and B. Mortazavi
    “Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery”
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2020. [Paper] [Code]
  • W. Chen*, Z. Yu, Z. Wang, and A. Anandkumar
    “Automated Synthetic-to-Real Generalization”
    International Conference on Machine Learning (ICML), 2020. [Paper] [Code]
  • X. Chen*, W. Chen*, T. Chen*, Y. Yuan*, C. Gong, K. Chen, and Z. Wang
    “Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training”
    International Conference on Machine Learning (ICML), 2020. [Paper] [Code]
  • Y. You*, T. Chen*, Z. Wang, and Y. Shen
    “When Does Self-Supervision Help Graph Convolutional Networks?”
    International Conference on Machine Learning (ICML), 2020. [Paper] [Code]
  • R. Oftadeh, J. Shen*, Z. Wang, and D. Shell
    “Eliminating the Invariance on the Loss Landscape of Linear Autoencoders”
    International Conference on Machine Learning (ICML), 2020. [Paper] [Code]
  • Y. Fu, W. Chen*, H. Wang*, H. Li, Y. Lin, and Z. Wang
    “AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks”
    International Conference on Machine Learning (ICML), 2020. [Paper] [Code]
  • R. Ardywibowo, S. Boluki, X. Gong*, Z. Wang, and X. Qian
    “NADS: Neural Architecture Distribution Search for Uncertainty Awareness”
    International Conference on Machine Learning (ICML), 2020. [Paper] [Code]
  • Y. Zhao, X. Chen*, Y. Wang, C. Li, Y. Xie, Z. Wang, and Y. Lin
    “SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation”
    IEEE/ACM International Symposium on Computer Architecture (ISCA), 2020. [Paper] [Code]
  • T. Chen*, S. Liu, S. Chang, Y. Cheng, L. Amini, and Z. Wang
    “Adversarial Robustness: From Self-Supervised Pretraining to Fine-Tuning”
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [Paper] [Code]
  • Z. Jiang*, B. Liu, S. Schulter, Z. Wang, and M. Chandraker
    “Peek-a-boo: Occlusion Reasoning in Indoor Scenes with Plane Representations”
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. (Oral) [Paper] [Code]
  • Y. You*, T. Chen*, Z. Wang, and Y. Shen
    “L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks”
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [Paper] [Code]
  • T. Hu*, T. Chen*, H. Wang*, and Z. Wang
    "Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference"
    International Conference on Learning Representations (ICLR), 2020. [Paper] [Code]
  • W. Chen*, X. Gong*, X. Liu, Q. Zhang, Y. Liu and Z. Wang
    "FasterSeg: Searching for Faster Real-time Semantic Segmentation"
    International Conference on Learning Representations (ICLR), 2020. [Paper] [Code]
  • H. Wang*, T. Chen*, Z. Wang, and K. Ma
    "I am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively"
    International Conference on Learning Representations (ICLR), 2020. [Paper] [Code]
  • H. You, C. Li, P. Xu, Y. Fu, Y. Wang, X. Chen*, R. Baraniuk, Z. Wang, and Y. Lin
    “Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks"
    International Conference on Learning Representations (ICLR), 2020. (Spotlight Oral) [Paper] [Code]
  • J. Shen*, Y. Wang*, P. Xu, Y. Fu, Z. Wang, and Y. Lin
    “Fractional Skipping: Toward Finer-Grained Dynamic Inference”
    AAAI Conference on Artificial Intelligence (AAAI), 2020. [Paper] [Code]
  • S. Mohseni*, M. Pitale, J. Yadawa, and Z. Wang
    “Self-Supervised Learning for Generalizable Out-of-Distribution Detection”
    AAAI Conference on Artificial Intelligence (AAAI), 2020. [Paper] [Code]
  • Z. Jiang*, Y. Wang*, X. Chen*, P. Xu, Y. Zhao, Y. Lin, and Z. Wang
    “E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings”
    Advances in Neural Information Processing Systems (NeurIPS), 2019. [Paper] [Code]
  • S. Gui, H. Wang*, H. Yang, C. Yu, Z. Wang, and J. Liu
    “Model Compression with Adversarial Robustness: A Unified Optimization Framework”
    Advances in Neural Information Processing Systems (NeurIPS), 2019. [Paper] [Code]
  • Y. Cao, T. Chen*, Z. Wang, and Y. Shen
    “Learning to Optimize in Swarms”
    Advances in Neural Information Processing Systems (NeurIPS), 2019. [Paper] [Code]
  • X. Jia, S. Wang*, X. Liang, A. Balagopal, D. Nguyen, M. Yang, Z. Wang, X. Qian, X. Ji, and S. Jiang
    “Cone-Beam Computed Tomography (CBCT) Segmentation by Adversarial Learning Domain Adaptation”
    Medical Image Computing and Computer Assisted Interventions (MICCAI), 2019 [Paper] [Code]
  • S. Yang*, Z. Wang, Z Wang, N. Xu, J. Liu, and Z. Guo
    “Controllable Artistic Text Style Transfer via Shape-Matching GAN”
    IEEE International Conference on Computer Vision (ICCV), 2019. (Oral) [Paper] [Code]
  • Z. Wu*, K. Suresh*, P. Narayanan, H. Xu, H. Kwon, and Z. Wang
    “Delving into Robust Object Detection from Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement Approach”
    IEEE International Conference on Computer Vision (ICCV), 2019. [Paper] [Code]
  • X. Gong*, S. Chang, Y. Jiang*, and Z. Wang
    “AutoGAN: Neural Architecture Search for Generative Adversarial Networks”
    IEEE International Conference on Computer Vision (ICCV), 2019. [Paper] [Code]
  • T. Chen*, S. Ding, J. Xie, Y. Yuan*, W. Chen*, Y. Yang, Z. Ren, and Z. Wang
    “ABD-Net: Attentive but Diverse Person Re-Identification”
    IEEE International Conference on Computer Vision (ICCV), 2019. [Paper] [Code]
  • O. Kupyn, T. Martyniuk, J. Wu*, and Z. Wang
    “DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better”
    IEEE International Conference on Computer Vision (ICCV), 2019. [Paper] [Code]
  • E. Ryu, J. Liu, S. Wang*, X. Chen*, Z. Wang, and W. Yin
    “Plug-and-Play Methods Provably Converge with Properly Trained Denoisers”
    International Conference on Machine Learning (ICML), 2019. [Paper] [Code]
  • W. Chen*, Z. Jiang*, Z. Wang, K. Cui, and X. Qian
    “Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-high Resolution Images”
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. (Oral) [Paper] [Code]
  • S. Li, I. B. Araujo*, W. Ren, Z. Wang, E. K. Tokuda*, R. Hirata, R. Cesar, J. Zhang, X. Guo, and X. Cao
    “Single Image Deraining: A Comprehensive Benchmark Analysis”
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [Paper] [Code]
  • J. Liu, X. Chen*, Z. Wang, and W. Yin
    “ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA”
    International Conference on Learning Representations (ICLR), 2019. [Paper] [Code]
  • X. Chen*, J. Liu, Z. Wang, and W. Yin
    “Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds”
    Advances in Neural Information Processing Systems (NeurIPS), 2018. (Spotlight Oral) [Paper] [Code]
  • N. Bansal*, X. Chen*, and Z. Wang
    “Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?”
    Advances in Neural Information Processing Systems (NeurIPS), 2018. [Paper] [Code]
  • Z. Wu*, Z. Wang, Z. Wang, and H. Jin
    “Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study”
    European Conference on Computer Vision (ECCV), 2018. [paper] [Code]
  • J. Wu*, Y. Wang*, Z. Wu*, Z. Wang, A. Veeraraghavan, and Y. Lin
    “Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions”
    International Conference on Machine Learning (ICML), 2018. [Paper] [Code]