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Di Wang 0015
Person information
- affiliation: King Abdullah University of Science and Technology (KAUST), Saudi Arabia
- affiliation (former): State University of New York at Buffalo, Department of Computer Science and Engineering, USA
Other persons with the same name
- Di Wang — disambiguation page
- Di Wang 0001 — Khalifa University, EBTIC, Abu Dhabi, UAE (and 2 more)
- Di Wang 0002 — Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, Boca Raton, FL, USA
- Di Wang 0003
— Microsoft Research, Redmond, WA, USA (and 1 more)
- Di Wang 0004
- Di Wang 0005
- Di Wang 0006
- Di Wang 0007
- Di Wang 0008
- Di Wang 0009
- Di Wang 0010
- Di Wang 0011
- Di Wang 0012
- Di Wang 0013
- Di Wang 0014
- Di Wang 0016
- Di Wang 0017
- Di Wang 0018
- Di Wang 0019
- Di Wang 0020
- Di Wang 0021
- Di Wang 0022 — Chinese Academy of Agricultural Sciences, Institute of Agricultural Resources and Regional Planning, Beijing, China
- Di Wang 0023
- Di Wang 0024
- Di Wang 0025
- Di Wang 0026
- Di Wang 0027
- Di Wang 0028 — Plus Inc., Suzhou, China (and 1 more)
- Di Wang 0029
- Di Wang 0030 — Microsoft Research, Redmond, WA, USA (and 1 more)
- Di Wang 0031 — Facebook, Seattle, WA, USA (and 1 more)
- Di Wang 0032
- Di Wang 0033
- Di Wang 0034
- Di Wang 0035 — Chongqing Jiaotong University, School of Information Science and Engineering, China (and 2 more)
- Di Wang 0036 — Northeast Forestry University, College of Information and Computer Engineering, Harbin, China (and 1 more)
- Di Wang 0037
- Di Wang 0038
- Di Wang 0039 — Northwest Minzu University, Key Laboratory of China's Ethnic Languages and Information Technology of Ministry of Education, Lanzhou, Gansu, China (and 1 more)
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2020 – today
- 2024
- [j22]Juexiao Zhou
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI. Comput. Biol. Medicine 169: 107861 (2024) - [j21]Washim Uddin Mondal
Near-Perfect Coverage Manifold Estimation in Cellular Networks via Conditional GAN. IEEE Netw. Lett. 6(2): 97-100 (2024) - [j20]Jinyan Su, Jinhui Xu, Di Wang
PAC learning halfspaces in non-interactive local differential privacy model with public unlabeled data. J. Comput. Syst. Sci. 141: 103496 (2024) - [j19]Jinyan Su, Lijie Hu, Di Wang:
Faster Rates of Differentially Private Stochastic Convex Optimization. J. Mach. Learn. Res. 25: 114:1-114:41 (2024) - [j18]Youming Tao, Cheng-Long Wang
Communication Efficient and Provable Federated Unlearning. Proc. VLDB Endow. 17(5): 1119-1131 (2024) - [j17]Shaowei Wang, Yun Peng, Jin Li, Zikai Wen, Zhipeng Li, Shiyu Yu, Di Wang, Wei Yang:
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened. Proc. VLDB Endow. 17(8): 1870-1883 (2024) - [j16]Di Wang
Gradient complexity and non-stationary views of differentially private empirical risk minimization. Theor. Comput. Sci. 982: 114259 (2024) - [j15]Junren Chen
Quantizing Heavy-Tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery. IEEE Trans. Inf. Theory 70(3): 2003-2038 (2024) - [j14]Minghua Wang, Yan Hu, Ziyun Huang, Di Wang, Jinhui Xu:
Persistent Local Homology in Graph Learning. Trans. Mach. Learn. Res. 2024 (2024) - [c54]Lijie Hu, Ivan Habernal, Lei Shen, Di Wang:
Differentially Private Natural Language Models: Recent Advances and Future Directions. EACL (Findings) 2024: 478-499 - [c53]Muhammad Ali, Yan Hu, Jianbin Qin, Di Wang:
Antonym vs Synonym Distinction using InterlaCed Encoder NETworks (ICE-NET). EACL (Findings) 2024: 1462-1473 - [c52]Liangyu Wang
WiP: Towards Light Adaptation of Large Language Models For Personal Hardware. EdgeFM@MobiSys 2024: 30-32 - [c51]Shaopeng Fu, Di Wang:
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach. ICLR 2024 - [c50]Songning Lai, Lijie Hu, Junxiao Wang, Laure Berti-Équille, Di Wang:
Faithful Vision-Language Interpretation via Concept Bottleneck Models. ICLR 2024 - [c49]Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli:
An LLM can Fool Itself: A Prompt-Based Adversarial Attack. ICLR 2024 - [c48]Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang:
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model. ICLR 2024 - [c47]Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu:
Understanding Forgetting in Continual Learning with Linear Regression. ICML 2024 - [c46]Mudit Gaur, Amrit S. Bedi, Di Wang, Vaneet Aggarwal:
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization. ICML 2024 - [c45]Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang:
Improving Interpretation Faithfulness for Vision Transformers. ICML 2024 - [c44]Zihang Xiang, Tianhao Wang, Di Wang:
Preserving Node-level Privacy in Graph Neural Networks. SP 2024: 4714-4732 - [i67]Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang:
Antonym vs Synonym Distinction using InterlaCed Encoder NETworks (ICE-NET). CoRR abs/2401.10045 (2024) - [i66]Youming Tao, Cheng-Long Wang, Miao Pan, Dongxiao Yu, Xiuzhen Cheng, Di Wang:
Communication Efficient and Provable Federated Unlearning. CoRR abs/2401.11018 (2024) - [i65]Washim Uddin Mondal, Veni Goyal, Satish V. Ukkusuri, Goutam Das, Di Wang, Mohamed-Slim Alouini, Vaneet Aggarwal:
Near-perfect Coverage Manifold Estimation in Cellular Networks via conditional GAN. CoRR abs/2402.06901 (2024) - [i64]Shu Yang, Muhammad Asif Ali, Cheng-Long Wang, Lijie Hu, Di Wang:
MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning. CoRR abs/2402.11260 (2024) - [i63]Shu Yang, Lijie Hu, Lu Yu, Muhammad Asif Ali, Di Wang:
Human-AI Interactions in the Communication Era: Autophagy Makes Large Models Achieving Local Optima. CoRR abs/2402.11271 (2024) - [i62]Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang:
Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models. CoRR abs/2402.11989 (2024) - [i61]Zihang Xiang, Chenglong Wang, Di Wang:
How Does Selection Leak Privacy: Revisiting Private Selection and Improved Results for Hyper-parameter Tuning. CoRR abs/2402.13087 (2024) - [i60]Cheng-Long Wang, Qi Li, Zihang Xiang, Di Wang:
Has Approximate Machine Unlearning been evaluated properly? From Auditing to Side Effects. CoRR abs/2403.12830 (2024) - [i59]Shu Yang, Jiayuan Su, Han Jiang, Mengdi Li, Keyuan Cheng, Muhammad Asif Ali, Lijie Hu, Di Wang:
Dialectical Alignment: Resolving the Tension of 3H and Security Threats of LLMs. CoRR abs/2404.00486 (2024) - [i58]Muhammad Asif Ali, Zhengping Li, Shu Yang, Keyuan Cheng, Yang Cao, Tianhao Huang, Lijie Hu, Lu Yu, Di Wang:
PROMPT-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression. CoRR abs/2404.00489 (2024) - [i57]Keyuan Cheng, Gang Lin, Haoyang Fei, Yuxuan Zhai, Lu Yu, Muhammad Asif Ali, Lijie Hu, Di Wang:
Multi-hop Question Answering under Temporal Knowledge Editing. CoRR abs/2404.00492 (2024) - [i56]Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal:
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization. CoRR abs/2405.01843 (2024) - [i55]Keyuan Cheng, Muhammad Asif Ali, Shu Yang, Gang Lin, Yuxuan Zhai, Haoyang Fei, Ke Xu, Lu Yu, Lijie Hu, Di Wang:
Leveraging Logical Rules in Knowledge Editing: A Cherry on the Top. CoRR abs/2405.15452 (2024) - [i54]Lijie Hu, Chenyang Ren, Zhengyu Hu, Cheng-Long Wang, Di Wang:
Editable Concept Bottleneck Models. CoRR abs/2405.15476 (2024) - [i53]Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu:
Understanding Forgetting in Continual Learning with Linear Regression. CoRR abs/2405.17583 (2024) - [i52]Jia Li, Lijie Hu, Zhixian He, Jingfeng Zhang, Tianhang Zheng, Di Wang:
Text Guided Image Editing with Automatic Concept Locating and Forgetting. CoRR abs/2405.19708 (2024) - [i51]Lijie Hu, Liang Liu, Shu Yang, Xin Chen, Hongru Xiao, Mengdi Li, Pan Zhou, Muhammad Asif Ali, Di Wang:
A Hopfieldian View-based Interpretation for Chain-of-Thought Reasoning. CoRR abs/2406.12255 (2024) - [i50]Shaowei Wang, Changyu Dong, Di Wang, Xiangfu Song:
Beyond Statistical Estimation: Differentially Private Individual Computation in the Shuffle Model. CoRR abs/2406.18145 (2024) - [i49]Lijie Hu, Tianhao Huang, Huanyi Xie, Chenyang Ren, Zhengyu Hu, Lu Yu, Di Wang:
Semi-supervised Concept Bottleneck Models. CoRR abs/2406.18992 (2024) - [i48]Binhao Ma, Tianhang Zheng, Hongsheng Hu, Di Wang, Shuo Wang, Zhongjie Ba, Zhan Qin, Kui Ren:
Releasing Malevolence from Benevolence: The Menace of Benign Data on Machine Unlearning. CoRR abs/2407.05112 (2024) - [i47]Xiaochuan Gou, Ziyue Li, Tian Lan, Junpeng Lin, Zhishuai Li, Bingyu Zhao, Chen Zhang, Di Wang, Xiangliang Zhang:
XTraffic: A Dataset Where Traffic Meets Incidents with Explainability and More. CoRR abs/2407.11477 (2024) - [i46]Shaopeng Fu, Xuexue Sun, Ke Qing, Tianhang Zheng, Di Wang:
Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services. CoRR abs/2408.02814 (2024) - 2023
- [j13]Di Wang, Lijie Hu, Huanyu Zhang, Marco Gaboardi, Jinhui Xu:
Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data. J. Mach. Learn. Res. 24: 132:1-132:57 (2023) - [j12]Zihang Xiang
Practical Differentially Private and Byzantine-resilient Federated Learning. Proc. ACM Manag. Data 1(2): 119:1-119:26 (2023) - [j11]Junren Chen
High Dimensional Statistical Estimation Under Uniformly Dithered One-Bit Quantization. IEEE Trans. Inf. Theory 69(8): 5151-5187 (2023) - [c43]Lijie Hu, Yixin Liu
SEAT: Stable and Explainable Attention. AAAI 2023: 12907-12915 - [c42]Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang:
Privacy-preserving Sparse Generalized Eigenvalue Problem. AISTATS 2023: 5052-5062 - [c41]Di Wang
Finite Sample Guarantees of Differentially Private Expectation Maximization Algorithm. ECAI 2023: 2435-2442 - [c40]Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang
GRI: Graph-based Relative Isomorphism of Word Embedding Spaces. EMNLP (Findings) 2023: 11304-11313 - [c39]Jinyan Su, Terry Yue Zhuo, Di Wang
DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text. EMNLP (Findings) 2023: 12395-12412 - [c38]Xiaochuan Gou
A Fundamental Model with Stable Interpretability for Traffic Forecasting. GeoPrivacy@SIGSPATIAL 2023: 10-13 - [c37]Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang:
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards. ICML 2023: 37880-37918 - [c36]Rui Chen
EEFL: High-Speed Wireless Communications Inspired Energy Efficient Federated Learning over Mobile Devices. MobiSys 2023: 544-556 - [c35]Yulian Wu, Xingyu Zhou, Youming Tao, Di Wang:
On Private and Robust Bandits. NeurIPS 2023 - [c34]Hanshen Xiao, Zihang Xiang, Di Wang
A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction. SP 2023: 2170-2189 - [c33]Jinyan Su, Changhong Zhao, Di Wang:
Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited. UAI 2023: 2026-2035 - [c32]Cheng-Long Wang
Inductive Graph Unlearning. USENIX Security Symposium 2023: 3205-3222 - [c31]Muhammad Asif Ali, Maha Alshmrani, Jianbin Qin, Yan Hu, Di Wang
GARI: Graph Attention for Relative Isomorphism of Arabic Word Embeddings. ArabicNLP 2023: 181-190 - [i45]Lijie Hu, Ivan Habernal, Lei Shen, Di Wang:
Differentially Private Natural Language Models: Recent Advances and Future Directions. CoRR abs/2301.09112 (2023) - [i44]Yulian Wu, Chaowen Guan, Vaneet Aggarwal, Di Wang:
Quantum Heavy-tailed Bandits. CoRR abs/2301.09680 (2023) - [i43]Yulian Wu, Xingyu Zhou, Youming Tao, Di Wang:
On Private and Robust Bandits. CoRR abs/2302.02526 (2023) - [i42]Bhargav Ganguly, Yulian Wu, Di Wang, Vaneet Aggarwal:
Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning. CoRR abs/2302.08617 (2023) - [i41]Juexiao Zhou
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI. CoRR abs/2302.11571 (2023) - [i40]Jinyan Su, Changhong Zhao, Di Wang:
Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited. CoRR abs/2303.18047 (2023) - [i39]Cheng-Long Wang, Mengdi Huai, Di Wang:
Inductive Graph Unlearning. CoRR abs/2304.03093 (2023) - [i38]Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang:
Practical Differentially Private and Byzantine-resilient Federated Learning. CoRR abs/2304.09762 (2023) - [i37]Puyu Wang, Yunwen Lei, Di Wang, Yiming Ying, Ding-Xuan Zhou:
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks. CoRR abs/2305.16891 (2023) - [i36]Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang:
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards. CoRR abs/2306.01121 (2023) - [i35]Jinyan Su, Terry Yue Zhuo, Di Wang, Preslav Nakov:
DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text. CoRR abs/2306.05540 (2023) - [i34]Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal:
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization. CoRR abs/2306.10486 (2023) - [i33]Jinyan Su, Terry Yue Zhuo, Jonibek Mansurov, Di Wang, Preslav Nakov:
Fake News Detectors are Biased against Texts Generated by Large Language Models. CoRR abs/2309.08674 (2023) - [i32]Shaopeng Fu, Di Wang:
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach. CoRR abs/2310.06112 (2023) - [i31]Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang:
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model. CoRR abs/2310.07367 (2023) - [i30]Hanpu Shen, Cheng-Long Wang, Zihang Xiang, Yiming Ying, Di Wang:
Differentially Private Non-convex Learning for Multi-layer Neural Networks. CoRR abs/2310.08425 (2023) - [i29]Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang:
GRI: Graph-based Relative Isomorphism of Word Embedding Spaces. CoRR abs/2310.12360 (2023) - [i28]Muhammad Asif Ali, Maha Alshmrani, Jianbin Qin, Yan Hu, Di Wang:
GARI: Graph Attention for Relative Isomorphism of Arabic Word Embeddings. CoRR abs/2310.13068 (2023) - [i27]Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli:
An LLM can Fool Itself: A Prompt-Based Adversarial Attack. CoRR abs/2310.13345 (2023) - [i26]Zihang Xiang, Tianhao Wang, Di Wang:
Preserving Node-level Privacy in Graph Neural Networks. CoRR abs/2311.06888 (2023) - [i25]Jia Li, Lijie Hu, Jingfeng Zhang, Tianhang Zheng, Hua Zhang, Di Wang:
Fair Text-to-Image Diffusion via Fair Mapping. CoRR abs/2311.17695 (2023) - [i24]Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang:
Improving Faithfulness for Vision Transformers. CoRR abs/2311.17983 (2023) - 2022
- [c30]Jinyan Su, Jinhui Xu, Di Wang:
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data. ACML 2022: 927-941 - [c29]Youming Tao, Yulian Wu, Peng Zhao, Di Wang:
Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits. AISTATS 2022: 1546-1574 - [c28]Vincent Cohen-Addad, Yunus Esencayi, Chenglin Fan, Marco Gaboardi, Shi Li, Di Wang:
On Facility Location Problem in the Local Differential Privacy Model. AISTATS 2022: 3914-3929 - [c27]Jinyan Su, Lijie Hu, Di Wang:
Faster Rates of Private Stochastic Convex Optimization. ALT 2022: 995-1002 - [c26]Youming Tao, Yulian Wu, Xiuzhen Cheng, Di Wang:
Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited. IJCAI 2022: 3947-3953 - [c25]Di Wang, Jinhui Xu:
Differentially Private ℓ1-norm Linear Regression with Heavy-tailed Data. ISIT 2022: 1856-1861 - [c24]Lijie Hu
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data. PODS 2022: 227-236 - [c23]Yuan Qiu, Jinyan Liu, Di Wang:
Truthful Generalized Linear Models. WINE 2022: 369-370 - [i23]Di Wang
Differentially Private 𝓁1-norm Linear Regression with Heavy-tailed Data. CoRR abs/2201.03204 (2022) - [i22]Junren Chen, Cheng-Long Wang, Michael K. Ng, Di Wang
High Dimensional Statistical Estimation under One-bit Quantization. CoRR abs/2202.13157 (2022) - [i21]Yuan Qiu, Jinyan Liu, Di Wang:
Truthful Generalized Linear Models. CoRR abs/2209.07815 (2022) - [i20]Jinyan Su, Jinhui Xu, Di Wang:
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data. CoRR abs/2209.08319 (2022) - [i19]Hao Wang, Wanyu Lin, Hao He, Di Wang, Chengzhi Mao, Muhan Zhang:
1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct). CoRR abs/2210.03612 (2022) - [i18]Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun
SEAT: Stable and Explainable Attention. CoRR abs/2211.13290 (2022) - [i17]Junren Chen, Michael Kwok-Po Ng, Di Wang:
Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery. CoRR abs/2212.14562 (2022) - 2021
- [j10]Di Wang
Inferring ground truth from crowdsourced data under local attribute differential privacy. Theor. Comput. Sci. 865: 85-98 (2021) - [j9]Di Wang
Differentially private high dimensional sparse covariance matrix estimation. Theor. Comput. Sci. 865: 119-130 (2021) - [j8]Di Wang
On Sparse Linear Regression in the Local Differential Privacy Model. IEEE Trans. Inf. Theory 67(2): 1182-1200 (2021) - [c22]Di Wang, Huangyu Zhang, Marco Gaboardi, Jinhui Xu:
Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data. ALT 2021: 1207-1213 - [c21]Zhiyu Xue, Shaoyang Yang, Mengdi Huai, Di Wang:
Differentially Private Pairwise Learning Revisited. IJCAI 2021: 3242-3248 - [i16]Youming Tao
Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits. CoRR abs/2106.02575 (2021) - [i15]Lijie Hu, Shuo Ni, Hanshen Xiao, Di Wang
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data. CoRR abs/2107.11136 (2021) - [i14]Jinyan Su, Di Wang:
Faster Rates of Differentially Private Stochastic Convex Optimization. CoRR abs/2108.00331 (2021) - 2020
- [j7]Di Wang
Estimating stochastic linear combination of non-linear regressions efficiently and scalably. Neurocomputing 399: 129-140 (2020) - [j6]Hongjiang Lei
Safeguarding UAV IoT Communication Systems Against Randomly Located Eavesdroppers. IEEE Internet Things J. 7(2): 1230-1244 (2020) - [j5]Di Wang, Marco Gaboardi, Adam D. Smith, Jinhui Xu:
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy. J. Mach. Learn. Res. 21: 200:1-200:39 (2020) - [j4]Di Wang
Robust high dimensional expectation maximization algorithm via trimmed hard thresholding. Mach. Learn. 109(12): 2283-2311 (2020) - [j3]Di Wang, Jinhui Xu:
Principal Component Analysis in the local differential privacy model. Theor. Comput. Sci. 809: 296-312 (2020) - [j2]Di Wang, Jinhui Xu:
Tight lower bound of sparse covariance matrix estimation in the local differential privacy model. Theor. Comput. Sci. 815: 47-59 (2020) - [c20]Mengdi Huai, Di Wang, Chenglin Miao
Pairwise Learning with Differential Privacy Guarantees. AAAI 2020: 694-701 - [c19]Mengdi Huai, Di Wang, Chenglin Miao
Towards Interpretation of Pairwise Learning. AAAI 2020: 4166-4173 - [c18]Di Wang, Xiangyu Guo, Chaowen Guan, Shi Li, Jinhui Xu:
Estimating Stochastic Linear Combination of Non-Linear Regressions. AAAI 2020: 6137-6144 - [c17]Mengdi Huai, Chenglin Miao, Jinduo Liu, Di Wang, Jingyuan Chou, Aidong Zhang:
Global Interpretation for Patient Similarity Learning. BIBM 2020: 589-594 - [c16]Di Wang, Hanshen Xiao, Srinivas Devadas, Jinhui Xu:
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data. ICML 2020: 10081-10091 - [c15]Di Wang
Escaping Saddle Points of Empirical Risk Privately and Scalably via DP-Trust Region Method. ECML/PKDD (3) 2020: 90-106 - [i13]Tianhang Zheng, Di Wang, Baochun Li, Jinhui Xu:
Towards Assessment of Randomized Mechanisms for Certifying Adversarial Robustness. CoRR abs/2005.07347 (2020) - [i12]Di Wang, Xiangyu Guo, Chaowen Guan, Shi Li, Jinhui Xu:
Estimating Stochastic Linear Combination of Non-linear Regressions Efficiently and Scalably. CoRR abs/2010.09265 (2020) - [i11]Di Wang, Xiangyu Guo, Shi Li, Jinhui Xu:
Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding. CoRR abs/2010.09576 (2020) - [i10]Di Wang, Hanshen Xiao, Srini Devadas, Jinhui Xu:
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data. CoRR abs/2010.11082 (2020) - [i9]Di Wang, Jiahao Ding, Zejun Xie, Miao Pan, Jinhui Xu:
Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees. CoRR abs/2010.13520 (2020) - [i8]Di Wang, Marco Gaboardi, Adam D. Smith, Jinhui Xu:
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy. CoRR abs/2011.05934 (2020)
2010 – 2019
- 2019
- [j1]Di Wang
Faster constrained linear regression via two-step preconditioning. Neurocomputing 364: 280-296 (2019) - [c14]Di Wang, Jinhui Xu:
Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View. AAAI 2019: 1182-1189 - [c13]Di Wang, Adam D. Smith, Jinhui Xu:
Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations. ALT 2019: 897-902 - [c12]Di Wang, Jinhui Xu, Yang He:
Estimating Sparse Covariance Matrix Under Differential Privacy via Thresholding. CISS 2019: 1-5 - [c11]Hongjiang Lei, Di Wang
On Secure UAV Communication Systems with Randomly Located Eavesdroppers. ICCC 2019: 201-206 - [c10]Di Wang, Changyou Chen, Jinhui Xu:
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions. ICML 2019: 6526-6535 - [c9]Di Wang, Jinhui Xu:
On Sparse Linear Regression in the Local Differential Privacy Model. ICML 2019: 6628-6637 - [c8]Mengdi Huai, Di Wang, Chenglin Miao
Privacy-aware Synthesizing for Crowdsourced Data. IJCAI 2019: 2542-2548 - [c7]Di Wang, Jinhui Xu:
Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation. IJCAI 2019: 4788-4794 - [c6]Di Wang, Jinhui Xu:
Principal Component Analysis in the Local Differential Privacy Model. IJCAI 2019: 4795-4801 - [c5]Yunus Esencayi, Marco Gaboardi, Shi Li, Di Wang:
Facility Location Problem in Differential Privacy Model Revisited. NeurIPS 2019: 8489-8498 - [i7]Di Wang
Differentially Private High Dimensional Sparse Covariance Matrix Estimation. CoRR abs/1901.06413 (2019) - [i6]Di Wang, Huanyu Zhang, Marco Gaboardi, Jinhui Xu:
Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data. CoRR abs/1910.00482 (2019) - [i5]Yunus Esencayi, Marco Gaboardi, Shi Li, Di Wang:
Facility Location Problem in Differential Privacy Model Revisited. CoRR abs/1910.12050 (2019) - 2018
- [c4]Di Wang, Jinhui Xu:
Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning. AAAI 2018: 1439-1446 - [c3]Di Wang, Mengdi Huai, Jinhui Xu:
Differentially Private Sparse Inverse Covariance Estimation. GlobalSIP 2018: 1139-1143 - [c2]Di Wang, Marco Gaboardi, Jinhui Xu:
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited. NeurIPS 2018: 973-982 - [i4]Di Wang, Jinhui Xu:
Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning. CoRR abs/1802.03337 (2018) - [i3]Di Wang, Marco Gaboardi, Jinhui Xu:
Efficient Empirical Risk Minimization with Smooth Loss Functions in Non-interactive Local Differential Privacy. CoRR abs/1802.04085 (2018) - [i2]Di Wang, Minwei Ye, Jinhui Xu:
Differentially Private Empirical Risk Minimization Revisited: Faster and More General. CoRR abs/1802.05251 (2018) - [i1]Di Wang, Adam D. Smith, Jinhui Xu:
Differentially Private Empirical Risk Minimization in Non-interactive Local Model via Polynomial of Inner Product Approximation. CoRR abs/1812.06825 (2018) - 2017
- [c1]Di Wang, Minwei Ye, Jinhui Xu:
Differentially Private Empirical Risk Minimization Revisited: Faster and More General. NIPS 2017: 2722-2731
Coauthor Index
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Unpaywalled article links
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Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-24 00:21 CEST by the dblp team
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