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2020 – today
- 2024
[j6]Utkarsh Nath, Yancheng Wang, Pavan K. Turaga, Yingzhen Yang
:
RNAS-CL: Robust Neural Architecture Search by Cross-Layer Knowledge Distillation. Int. J. Comput. Vis. 132(12): 5698-5717 (2024)- [c39]Lulu Xie, Yancheng Wang, Hong Guan, Soham Nag, Rajeev Goel, Niranjan Erappa Narayana Swamy, Yingzhen Yang, Chaowei Xiao, Jonathan Prisby, Ross Maciejewski, Jia Zou:
IDNet: A Novel Identity Document Dataset via Few-Shot and Quality-Driven Synthetic Data Generation. IEEE Big Data 2024: 2244-2253 - [c38]Yancheng Wang, Ping Li, Yingzhen Yang:
Visual Transformer with Differentiable Channel Selection: An Information Bottleneck Inspired Approach. ICML 2024 - [c37]Yancheng Wang, Ziyan Jiang, Zheng Chen, Fan Yang, Yingxue Zhou, Eunah Cho, Xing Fan, Yanbin Lu, Xiaojiang Huang, Yingzhen Yang:
RecMind: Large Language Model Powered Agent For Recommendation. NAACL-HLT (Findings) 2024: 4351-4364 - [c36]Yancheng Wang, Rajeev Goel, Utkarsh Nath, Alvin C. Silva, Teresa Wu, Yingzhen Yang:
Learning Low-Rank Feature for Thorax Disease Classification. NeurIPS 2024 - [i35]Hong Guan, Summer Gautier, Deepti Gupta, Rajan Hari Ambrish, Yancheng Wang, Harsha Lakamsani, Dhanush Giriyan, Saajan Maslanka, Chaowei Xiao, Yingzhen Yang, Jia Zou:
A Learning-based Declarative Privacy-Preserving Framework for Federated Data Management. CoRR abs/2401.12393 (2024) - [i34]Yancheng Wang, Yingzhen Yang:
Low-Rank Graph Contrastive Learning for Node Classification. CoRR abs/2402.09600 (2024) - [i33]Rajeev Goel, Utkarsh Nath, Yancheng Wang, Alvin C. Silva, Teresa Wu, Yingzhen Yang:
Learning Low-Rank Feature for Thorax Disease Classification. CoRR abs/2404.18933 (2024) - [i32]Yingzhen Yang:
Preconditioned Gradient Descent Finds Over-Parameterized Neural Networks with Sharp Generalization for Nonparametric Regression. CoRR abs/2407.11353 (2024) - [i31]Yancheng Wang, Yingzhen Yang:
Efficient Visual Transformer by Learnable Token Merging. CoRR abs/2407.15219 (2024) - [i30]Hong Guan, Yancheng Wang, Lulu Xie, Soham Nag, Rajeev Goel, Niranjan Erappa Narayana Swamy, Yingzhen Yang, Chaowei Xiao, Jonathan Prisby, Ross Maciejewski, Jia Zou:
IDNet: A Novel Dataset for Identity Document Analysis and Fraud Detection. CoRR abs/2408.01690 (2024) - [i29]Utkarsh Nath, Rajeev Goel, Eun Som Jeon, Changhoon Kim, Kyle Min, Yezhou Yang, Yingzhen Yang, Pavan K. Turaga:
Deep Geometric Moments Promote Shape Consistency in Text-to-3D Generation. CoRR abs/2408.05938 (2024) - [i28]Dongfang Sun, Yingzhen Yang:
Locally Regularized Sparse Graph by Fast Proximal Gradient Descent. CoRR abs/2409.17090 (2024) - [i27]Yingzhen Yang, Ping Li:
Gradient Descent Finds Over-Parameterized Neural Networks with Sharp Generalization for Nonparametric Regression: A Distribution-Free Analysis. CoRR abs/2411.02904 (2024) - 2023
- [c35]Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu:
Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning. AAAI 2023: 7378-7386 - [c34]Yingzhen Yang, Ping Li:
Projective Proximal Gradient Descent for Nonconvex Nonsmooth Optimization: Fast Convergence Without Kurdyka-Lojasiewicz (KL) Property. ICLR 2023 - [c33]Dongfang Sun, Yingzhen Yang:
Locally Regularized Sparse Graph by Fast Proximal Gradient Descent. UAI 2023: 2069-2077 - [i26]Utkarsh Nath, Yancheng Wang, Yingzhen Yang:
RNAS-CL: Robust Neural Architecture Search by Cross-Layer Knowledge Distillation. CoRR abs/2301.08092 (2023) - [i25]Yancheng Wang, Ziyan Jiang, Zheng Chen, Fan Yang, Yingxue Zhou, Eunah Cho, Xing Fan, Xiaojiang Huang, Yanbin Lu, Yingzhen Yang:
RecMind: Large Language Model Powered Agent For Recommendation. CoRR abs/2308.14296 (2023) - [i24]Yingzhen Yang:
Sharp Generalization of Transductive Learning: A Transductive Local Rademacher Complexity Approach. CoRR abs/2309.16858 (2023) - [i23]Yingzhen Yang, Ping Li:
Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees. CoRR abs/2311.01806 (2023) - 2022
- [c32]Utkarsh Nath, Shrinu Kushagra, Yingzhen Yang:
Adjoined Networks: A Training Paradigm With Applications to Network Compression. AAAI Spring Symposium: MAKE 2022 - [c31]Yingzhen Yang, Ping Li:
Discriminative Similarity for Data Clustering. ICLR 2022 - [c30]Lixi Zhou, Arindam Jain, Zijie Wang, Amitabh Das, Yingzhen Yang, Jia Zou:
Benchmark of DNN Model Search at Deployment Time. SSDBM 2022: 10:1-10:12 - [c29]Yingzhen Yang, Ping Li:
Noisy L0-sparse subspace clustering on dimensionality reduced data. UAI 2022: 2235-2245 - [i22]Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu:
Structural and Semantic Contrastive Learning for Self-supervised Node Representation Learning. CoRR abs/2202.08480 (2022) - [i21]Yancheng Wang, Ning Xu, Chong Chen, Yingzhen Yang:
Adaptive Cross-Layer Attention for Image Restoration. CoRR abs/2203.03619 (2022) - [i20]Yancheng Wang, Yingzhen Yang:
Bayesian Robust Graph Contrastive Learning. CoRR abs/2205.14109 (2022) - [i19]Lixi Zhou, Arindam Jain, Zijie Wang, Amitabh Das, Yingzhen Yang, Jia Zou:
Benchmark of DNN Model Search at Deployment Time. CoRR abs/2206.00188 (2022) - [i18]Yingzhen Yang, Ping Li:
Noisy 𝓁0-Sparse Subspace Clustering on Dimensionality Reduced Data. CoRR abs/2206.11079 (2022) - 2021
- [c28]Yingzhen Yang, Ping Li:
FROS: Fast Regularized Optimization by Sketching. ISIT 2021: 2780-2785 - [i17]Yingzhen Yang, Ping Li:
Discriminative Similarity for Data Clustering. CoRR abs/2109.08675 (2021) - 2020
- [c27]Yingzhen Yang, Jiahui Yu, Nebojsa Jojic, Jun Huan, Thomas S. Huang:
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary. ICLR 2020
2010 – 2019
- 2019
- [c26]Yingzhen Yang, Jiahui Yu:
Fast Proximal Gradient Descent for A Class of Non-convex and Non-smooth Sparse Learning Problems. UAI 2019: 1253-1262 - [i16]Yingzhen Yang, Xingjian Li, Jun Huan:
An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity. CoRR abs/1902.00873 (2019) - [i15]Yingzhen Yang, Nebojsa Jojic, Jun Huan:
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary. CoRR abs/1902.03264 (2019) - 2018
- [j5]Yingzhen Yang, Jiashi Feng, Nebojsa Jojic, Jianchao Yang, Thomas S. Huang:
Subspace Learning by ℓ0-Induced Sparsity. Int. J. Comput. Vis. 126(10): 1138-1156 (2018) - [c25]Yingzhen Yang:
Dimensionality Reduced $\ell^{0}$-Sparse Subspace Clustering. AISTATS 2018: 2065-2074 - [c24]Yingzhen Yang, Jianchao Yang, Ning Xu, Wei Han, Nebojsa Jojic, Thomas S. Huang:
3D-FilterMap: A Compact Architecture for Deep Convolutional Neural Networks. ICLR (Workshop) 2018 - [c23]Xiaojie Jin, Yingzhen Yang, Ning Xu, Jianchao Yang, Nebojsa Jojic, Jiashi Feng, Shuicheng Yan:
WSNet: Compact and Efficient Networks Through Weight Sampling. ICML 2018: 2357-2366 - [i14]Yingzhen Yang, Jianchao Yang, Ning Xu, Wei Han:
Learning 3D-FilterMap for Deep Convolutional Neural Networks. CoRR abs/1801.01609 (2018) - 2017
- [c22]Yingzhen Yang, Jiahui Yu, Pushmeet Kohli, Jianchao Yang, Thomas S. Huang:
Support Regularized Sparse Coding and Its Fast Encoder. ICLR (Poster) 2017 - [c21]Yingzhen Yang, Jiashi Feng, Jiahui Yu, Jianchao Yang, Thomas S. Huang:
Neighborhood Regularized l^1-Graph. UAI 2017 - [i13]Yingzhen Yang, Jiashi Feng, Nebojsa Jojic, Jianchao Yang, Thomas S. Huang:
On the Suboptimality of Proximal Gradient Descent for $\ell^{0}$ Sparse Approximation. CoRR abs/1709.01230 (2017) - [i12]Yingzhen Yang, Feng Liang, Nebojsa Jojic, Shuicheng Yan, Jiashi Feng, Thomas S. Huang:
Discriminative Similarity for Clustering and Semi-Supervised Learning. CoRR abs/1709.01231 (2017) - [i11]Xiaojie Jin, Yingzhen Yang, Ning Xu, Jianchao Yang, Jiashi Feng, Shuicheng Yan:
WSNet: Compact and Efficient Networks with Weight Sampling. CoRR abs/1711.10067 (2017) - 2016
- [b2]Yingzhen Yang:
Similarity modeling for machine learning. University of Illinois Urbana-Champaign, USA, 2016 - [j4]Shiyu Chang, Guo-Jun Qi, Yingzhen Yang, Charu C. Aggarwal, Jiayu Zhou, Meng Wang, Thomas S. Huang:
Large-scale supervised similarity learning in networks. Knowl. Inf. Syst. 48(3): 707-740 (2016) - [c20]Zhiding Yu, Weiyang Liu, Wenbo Liu, Yingzhen Yang, Ming Li, B. V. K. Vijaya Kumar:
On Order-Constrained Transitive Distance Clustering. AAAI 2016: 2293-2299 - [c19]Yingzhen Yang, Zhangyang Wang, Zhaowen Wang, Shiyu Chang, Ding Liu, Honghui Shi, Thomas S. Huang:
Epitomic Image Super-Resolution. AAAI 2016: 4278-4279 - [c18]Zhangyang Wang, Ding Liu, Shiyu Chang, Qing Ling, Yingzhen Yang, Thomas S. Huang:
D3: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images. CVPR 2016: 2764-2772 - [c17]Zhangyang Wang, Shiyu Chang, Yingzhen Yang, Ding Liu, Thomas S. Huang:
Studying Very Low Resolution Recognition Using Deep Networks. CVPR 2016: 4792-4800 - [c16]Yingzhen Yang, Jiashi Feng, Nebojsa Jojic, Jianchao Yang, Thomas S. Huang:
ℓ ^0 ℓ 0 -Sparse Subspace Clustering. ECCV (2) 2016: 731-747 - [c15]Zhangyang Wang, Yingzhen Yang, Shiyu Chang, Qing Ling, Thomas S. Huang:
Learning A Deep ℓ∞ Encoder for Hashing. IJCAI 2016: 2174-2180 - [i10]Zhangyang Wang, Shiyu Chang, Yingzhen Yang, Ding Liu, Thomas S. Huang:
Studying Very Low Resolution Recognition Using Deep Networks. CoRR abs/1601.04153 (2016) - [i9]Zhangyang Wang, Yingzhen Yang, Shiyu Chang, Qing Ling, Thomas S. Huang:
Learning A Deep ℓ∞ Encoder for Hashing. CoRR abs/1604.01475 (2016) - [i8]Zhangyang Wang, Liang Zhang, Yingzhen Yang, Jiayu Zhou, Georgios B. Giannakis, Thomas S. Huang:
Deep Double Sparsity Encoder: Learning to Sparsify Not Only Features But Also Parameters. CoRR abs/1608.06374 (2016) - 2015
- [b1]Zhaowen Wang, Jianchao Yang, Haichao Zhang, Zhangyang Wang, Yingzhen Yang, Ding Liu, Thomas S. Huang:
Sparse Coding and its Applications in Computer Vision. WorldScientific 2015, ISBN 9789814725040, pp. 1-240 - [j3]Zhangyang Wang, Yingzhen Yang, Zhaowen Wang, Shiyu Chang, Jianchao Yang, Thomas S. Huang:
Learning Super-Resolution Jointly From External and Internal Examples. IEEE Trans. Image Process. 24(11): 4359-4371 (2015) - [c14]Zhangyang Wang, Yingzhen Yang, Zhaowen Wang, Shiyu Chang, Wei Han, Jianchao Yang, Thomas S. Huang:
Self-tuned deep super resolution. CVPR Workshops 2015: 1-8 - [c13]Zhangyang Wang, Yingzhen Yang, Shiyu Chang, Jinyan Li, Simon Fong, Thomas S. Huang:
A Joint Optimization Framework of Sparse Coding and Discriminative Clustering. IJCAI 2015: 3932-3938 - [c12]Zhangyang Wang, Yingzhen Yang, Jianchao Yang, Thomas S. Huang:
Designing a composite dictionary adaptively from joint examples. VCIP 2015: 1-4 - [i7]Zhangyang Wang, Yingzhen Yang, Zhaowen Wang, Shiyu Chang, Jianchao Yang, Thomas S. Huang:
Learning Super-Resolution Jointly from External and Internal Examples. CoRR abs/1503.01138 (2015) - [i6]Zhangyang Wang, Yingzhen Yang, Jianchao Yang, Thomas S. Huang:
Designing A Composite Dictionary Adaptively From Joint Examples. CoRR abs/1503.03621 (2015) - [i5]Zhangyang Wang, Yingzhen Yang, Zhaowen Wang, Shiyu Chang, Wei Han, Jianchao Yang, Thomas S. Huang:
Self-Tuned Deep Super Resolution. CoRR abs/1504.05632 (2015) - [i4]Yingzhen Yang, Jiashi Feng, Jianchao Yang, Thomas S. Huang:
Learning ℓ0-Graph for Data Clustering. CoRR abs/1510.08520 (2015) - [i3]Weiyang Liu, Zhiding Yu, Yingzhen Yang, Meng Yang:
Jointly Learning Non-negative Projection and Dictionary with Discriminative Graph Constraints for Classification. CoRR abs/1511.04601 (2015) - 2014
- [c11]Yingzhen Yang, Zhangyang Wang, Jianchao Yang, Jiangping Wang, Shiyu Chang, Thomas S. Huang:
Data Clustering by Laplacian Regularized L1-Graph. AAAI 2014: 3148-3149 - [c10]Yingzhen Yang, Zhangyang Wang, Jianchao Yang, Jiawei Han, Thomas S. Huang:
Regularized l1-Graph for Data Clustering. BMVC 2014 - [c9]Yingzhen Yang, Xinqi Chu, Tian-Tsong Ng, Alex Yong Sang Chia, Jianchao Yang, Hailin Jin, Thomas S. Huang:
Epitomic image colorization. ICASSP 2014: 2470-2474 - [c8]Yingzhen Yang, Feng Liang, Thomas S. Huang:
Discriminative Exemplar clustering. ICASSP 2014: 6771-6775 - [c7]Yingzhen Yang, Feng Liang, Shuicheng Yan, Zhangyang Wang, Thomas S. Huang:
On a Theory of Nonparametric Pairwise Similarity for Clustering: Connecting Clustering to Classification. NIPS 2014: 145-153 - 2013
- [c6]Yingzhen Yang, Xinqi Chu, Thomas S. Huang:
Pairwise Clustering by Minimizing the Error of Unsupervised Nearest Neighbor Classification. ICMLA (2) 2013: 182-187 - 2012
- [c5]Yingzhen Yang, Xinqi Chu, Feng Liang, Thomas S. Huang:
Pairwise Exemplar Clustering. AAAI 2012: 1204-1211 - [i2]Yingzhen Yang, Xinqi Chu, Thomas S. Huang:
Generalization Analysis for Classification. CoRR abs/1210.0645 (2012) - [i1]Yingzhen Yang, Xinqi Chu, Tian-Tsong Ng, Alex Yong Sang Chia, Shuicheng Yan, Thomas S. Huang:
Epitome for Automatic Image Colorization. CoRR abs/1210.4481 (2012) - 2010
- [c4]Yingzhen Yang, Yang Cai:
Virtual gazing in video surveillance. SMVC@MM 2010: 15-20 - [c3]Peter Liang, Yingzhen Yang, Yang Cai:
Pattern mining from saccadic motion data. ICCS 2010: 2529-2538
2000 – 2009
- 2009
- [j2]Yingzhen Yang, Yichen Wei, Chunxiao Liu, Qunsheng Peng, Yasuyuki Matsushita:
An improved belief propagation method for dynamic collage. Vis. Comput. 25(5-7): 431-439 (2009) - [c2]Yingzhen Yang, Yin Zhu, Chunxiao Liu, Chengfang Song, Qunsheng Peng:
Entertaining video warping. CAD/Graphics 2009: 174-177 - [c1]Yingzhen Yang, Yin Zhu, Qunsheng Peng:
Image completion using structural priority belief propagation. ACM Multimedia 2009: 717-720 - 2008
- [j1]Chunxiao Liu, Yingzhen Yang, Qunsheng Peng, Jin Wang, Wei Chen:
Distortion Optimization based Image Completion from a Large Displacement View. Comput. Graph. Forum 27(7): 1755-1764 (2008)
Coauthor Index
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