PUBLICATIONS (to be updated)
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Books
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Selected Conference Publications
H. Dong, Z. Ding, S. Zhang, eds. “Deep Reinforcement Learning: Fundamentals, Research and Applications”, Springer Nature, 2020 Jun 29, (Electronic Edition 140,000 downloads; selectd to Annual High-Impact Publications in Computer Science by Chinese researchers).
Journal Publications
S. Zhou, S. Zhang*, et al. “Active Gradual Domain Adaptation: Dataset and Approach”, IEEE Transactions on Multimedia (TMM IF 8.182), 2022.
A. Dehban, S. Zhang, N. Cauli, L. Jamone, J. Santos-Victor. Learning Deep Features for Robotic Inference from Physical Interactions. IEEE Transactions on Cognitive and Developmental Systems (TCDS IF 4.546). 2022 Feb 17.
S. Zhou, S. Zhang*, et al. “Caching in Dynamic Environments: a Near-optimal Online Learning Approach”, IEEE Transactions on Multimedia (TMM IF 8.182), 2021.
S. Zhao, X. Yue*, S. Zhang*, B. Li, H. Zhao, B. Wu, R. Krishna, JE. Gonzalez, AL. Vincentelli, SA. Seshia, K. Keutzer. “A Review of Single-Source Deep Unsupervised Visual Domain Adaptation”, IEEE Transactions on Neural Networks and Learning Systems (IF 14.255). 2020.
C. Li, X. Peng, S. Zhang, H. Peng, P. Yu, M. He, L. Du, L. Wang, “Modeling relation paths for knowledge base completion via joint adversarial training”, Knowledge-Based Systems (IF 8.038), 2020: 105865.
C. Zhu, H. Jia, S. Zhang, X. Huang, X. Xie and W. Gao, “On a Highly Efficient RDO-based Mode Decision Pipeline Design,” IEEE Transactions on Multimedia (TMM IF 8.182), 15.8 (2013): 1815-1829.
Y Zou, S Zhang, Y Li, R Li, Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation, Neural Information Processing Systems (NeurIPS) 2022.
H Zhou, S Xiao, S Zhang, J Peng, S Zhang, J Li, Jump Self-attention: Capturing High-order Statistics in Transformers, Neural Information Processing Systems (NeurIPS) 2022.
X Wei, Y Zhang, X Zhang, R Gong, S Zhang, Q Zhang, F Yu, X Liu, Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models, Neural Information Processing Systems (NeurIPS) 2022.
J. Yu, J. Liu, X.Wei, H. Zhou, Y. Nakata, D. Gudovskiy, T. Okuno, J. Li, K. Keutzer, S. Zhang*, MTTrans: Cross-Domain Object Detection with Mean Teacher Transformer, 17th European Conference on Computer Vision (ECCV) 2022.
X. Li, J. Liu, S.Wang, C. Lyu, M. Lu, Y. Chen, A. Yao, Y. Guo, S. Zhang*, Efficient Meta-Tuning for Content-aware Neural Video Delivery, 17th European Conference on Computer Vision (ECCV) 2022.
C. Zhang#, M. Zhang#, S. Zhang#, et al. "Delving deep into the generalization of vision transformers under distribution shifts.", Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
T. Li, X. Chen, Z. Dong, K. Keutzer, S. Zhang*. Domain-Adaptive Text Classification with Structured Knowledge from Unlabeled Data, International Joint Conference on Artificial Intelligence (IJCAI), 2022.
M. Liu, Q. Zhou, H. Zhao, L. Du, Y. Du, J. Li, K. Keutzer, S. Zhang*. Prototypical Supervised Contrastive Learning for LiDAR Point Cloud Panoptic Segmentation, International Conference on Robotics and Automation (ICRA), 2022.
S. Zhou, H. Zhao, S. Zhang*, et al. “Online Continual Adaptation with Active Self-Training”, Artificial Intelligence and Statistics Conference (AISTATS), 2022.
CJ . Reed, X. Yue, A. Nrusimha, S. Ebrahimi, V. Vijaykumar, R. Mao, B. Li, S. Zhang, D. Guillory, S. Metzger, K. Keutzer. Self-supervised pretraining improves self-supervised pretraining. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022 (pp. 2584-2594).
Z. Luo, Z. Cai, C. Zhou, G. Zhang, H. Zhao, S. Yi, S. Lu, H. Li, S. Zhang, Z. Liu, “Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency”, International Conference on Computer Vision (ICCV), 2021.
Y. Liu, Q. Fan, S. Zhang, H. Dong, T. Funkhouser, L. Yi, “Contrastive Multimodal Fusion with TupleInfoNCE”, International Conference on Computer Vision (ICCV), 2021.
Y. Zou, S. Zhang, J. Yu. Y. Tian, J. Moura, “Revisiting Mid-Level Patterns for Distant-Domain Few-Shot Recognition”, ACM Multimedia (ACM MM), 2021.
Y. Zou, S. Zhang, G. Chen. Y. Tian, K. Keutzer, J. Moura, “Annotation-Efficient Untrimmed Video Action Recognition”, ACM Multimedia (ACM MM), 2021.
H. Zhou, J. Li, J. Peng, S. Zhang, S. Zhang, “Triplet Attention: Rethinking the similarity in Transformers”, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.
B. Li#, Y. Wang#, S. Zhang#, D. Li, T. Darrell, K. Keutzer, H. Zhao, “Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation”, Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
X. Yue, Z. Zheng, S. Zhang, Y. Gao, T. Darrell, K. Keutzer, AL. Vincentelli, “Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation”, Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
X Ma, X Kong, S Zhang, E Hovy, “Decoupling Global and Local Representations via Invertible Generative Flows”, Accepted by International Conference on Learning Representations (ICLR), 2021.
T. Li, X. Chen, S. Zhang*, Z. Dong*, K. Keutzer, “Cross-Domain Sentiment Classification With Contrastive Learning and Mutual Information Maximization”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.
H. Zhou, S. Zhang, J. Peng, S. Zhang, J. Li, H. Xiong, W. Zhang, “Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting”, Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021. AAAI Best Paper Award. (1st place of Trending Research on PaperWithCode, Github Star 1,600+, Visit 60,000+, Integrated into Mindspore Platform of Huawei, Applied to 1,400+ Transformer in Shandong and Anhui)
Y. Zou, S. Zhang, K. Chen, Y. Wang, J. Moura, Y. Tian, “Compositional Few-Shot Recognition with Primitive Discovery and Enhancing”, ACM Multimedia (ACM MM), 2020, Oral presentation.
X. Sun, Y. Xu, P. Cao, Y. Kong*, L. Hu, S. Zhang*, Y.Wang, “TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning”, 16th European Conference on Computer Vision (ECCV) 2020, Oral presentation (Top 2%).
K. Mei, C. Zhu, J. Zou, S. Zhang, “Instance Adaptive Self-Training for Unsupervised Domain Adaptation”, 16th European Conference on Computer Vision (ECCV), 2020.
C. Song, S. Zhang, N. Sadoughi, P. Xie, and E. Xing. "Generalized Zero-shot Text Classification for ICD Coding", International Joint Conference on Artificial Intelligence (IJCAI), 2020.
S. Zhao#, G. Wang#, S. Zhang#, Y. Gu, Y. Li, Z. Song, P. Xu, R. Hu, H. Chai, K. Keutzer, “Multi-source Distilling Domain Adaptation”, Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI) 2020, Oral presentation (Top 3%).
J. Ni, S. Zhang, H, Xie, “Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning”, Advances in Neural Information Processing Systems (NeurIPS), 2019.
X. Ma, X. Kong, S. Zhang, E. Hovy, “MaCow: Masked Convolutional Generative Flow”, Advances in Neural Information Processing Systems (NeurIPS), 2019.
H. Zhao#, S. Zhang#, G. Wu, J. Costeira, J. Moura, G. J. Gordon, “Adversarial Multiple Source Domain Adaptation”, Advances in Neural Information Processing Systems (NeurIPS), 2018.
S. Zhang, X. Shen, Z. Lin, R. Mech, J. Costeira, J. Moura, “Learning to Understand Image Blur”, Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
H. Zhao#, S. Zhang#, G. Wu, J. Costeira, J. Moura, G. J. Gordon, “Multiple Source Domain Adaptation with Adversarial Learning”, International Conference on Learning Representations (ICLR), invited to workshop, 2018.
R. Das, A. Gadre, S. Zhang, S. Kumar, and J. Moura, “A Deep Learning Approach to IoT Authentication”, accepted by IEEE International Conference on Communications (ICC), 2018.
S. Zhang#, G. Wu#, J. Costeira, J. Moura, “FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting in City Cameras”, International Conference on Computer Vision (ICCV), 2017.
S. Zhang, G. Wu, J. Costeira, J. Moura, “Understanding Traffic Density from Large-Scale Web Camera Data”, accepted by Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
F. Xia#, S. Zhang#, “Block-Coordinate Frank-Wolfe Optimization for Counting Objects in Images”, Advances in Neural Information Processing Systems (NIPS) Workshop, 2016.
E.Toropov, L. Gui, S. Zhang, S. Kottur, J. M. F. Moura, “Traffic Flow from a Low Frame Rate City Camera,” IEEE International Conference on Image Processing (ICIP), 2015.
S. Zhang, X. Li, R.D. Blanton, J. Silva, J. M. Carulli, K. M. Butler, “Bayesian Model Fusion: Enabling Test Cost Reduction of Analog/RF Circuits via Wafer-level Spatial Variation Modeling,” International Test Conference (ITC), 2014.
Y. Li, S. Zhang, H. Jia, X. Xie, and W. Gao, “A High-throughput Low-latency Arithmetic Encoder Design for HDTV,” The IEEE International Symposium on Circuits and Systems (ISCAS), 2013.
S Zhang, K Wei, H Jia, X Xie, W Gao. "An efficient foreground-based surveillance video coding scheme in low bit-rate compression" Visual Communications and Image Processing (VCIP), 2012 IEEE, 1-6
K. Wei, R. Zhou, S. Zhang, H. Jia, D. Xie, and W. Gao, “An Optimized Hardware Video Encoder For AVS With Level C+ Data Reuse Scheme For Motion Estimation,” IEEE International Conference on Multimedia & Expo (ICME), 2012.