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2020 – today
- 2025
[j11]Yihua Zhang
, Christian Stöhr, Susanne Strömberg Jämsvi, Jens Kabo, Johan Malmqvist:
Student Experiences of Hybrid and Online Engineering Labs in a Logic Control Course. Comput. Appl. Eng. Educ. 33(3) (2025)- [c41]Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen:
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. AAAI 2025: 4111-4119 - [c40]Hongkang Li, Yihua Zhang, Shuai Zhang, Pin-Yu Chen, Sijia Liu, Meng Wang:
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers. ICLR 2025 - [i36]Chongyu Fan, Jinghan Jia, Yihua Zhang, Anil Ramakrishna, Mingyi Hong, Sijia Liu:
Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond. CoRR abs/2502.05374 (2025) - [i35]Yiwei Chen, Yuguang Yao, Yihua Zhang, Bingquan Shen, Gaowen Liu, Sijia Liu:
Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-tuning. CoRR abs/2503.11832 (2025) - [i34]Hongkang Li, Yihua Zhang, Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen:
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers. CoRR abs/2504.10957 (2025) - 2024
- [j10]Yihua Zhang, Prashant Khanduri, Ioannis C. Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu:
An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning. IEEE Signal Process. Mag. 41(1): 38-59 (2024) - [c39]Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu:
To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy to Generate Unsafe Images ... For Now. ECCV (57) 2024: 385-403 - [c38]Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu:
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. EMNLP 2024: 4276-4292 - [c37]Mohammad Jafari, Yimeng Zhang, Yihua Zhang, Sijia Liu:
The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection. ICASSP 2024: 7100-7104 - [c36]Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu:
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training. ICLR 2024 - [c35]Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu:
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. ICLR 2024 - [c34]Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen:
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. ICML 2024 - [c33]Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu:
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. NeurIPS 2024 - [c32]Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu:
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models. NeurIPS 2024 - [c31]Yihua Zhang, Chongyu Fan, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Gaoyuan Zhang, Gaowen Liu, Ramana Kompella, Xiaoming Liu, Sijia Liu:
UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models. NeurIPS 2024 - [i33]Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen:
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. CoRR abs/2402.11592 (2024) - [i32]Yihua Zhang, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Xiaoming Liu, Sijia Liu:
UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models. CoRR abs/2402.11846 (2024) - [i31]Hongkang Li, Shuai Zhang, Yihua Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen:
How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance. CoRR abs/2403.07310 (2024) - [i30]Mohammad Jafari, Yimeng Zhang, Yihua Zhang, Sijia Liu:
The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection. CoRR abs/2403.12166 (2024) - [i29]Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu:
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. CoRR abs/2404.18239 (2024) - [i28]Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu:
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models. CoRR abs/2405.15234 (2024) - [i27]Yize Li, Yihua Zhang, Sijia Liu, Xue Lin:
Pruning then Reweighting: Towards Data-Efficient Training of Diffusion Models. CoRR abs/2409.19128 (2024) - [i26]Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu:
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. CoRR abs/2410.17509 (2024) - [i25]Hanhui Wang, Yihua Zhang, Ruizheng Bai, Yue Zhao, Sijia Liu, Zhengzhong Tu:
Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative Editing. CoRR abs/2411.16832 (2024) - [i24]Haomin Zhuang, Yihua Zhang, Kehan Guo, Jinghan Jia, Gaowen Liu, Sijia Liu, Xiangliang Zhang:
UOE: Unlearning One Expert Is Enough For Mixture-of-experts LLMS. CoRR abs/2411.18797 (2024) - [i23]Changchang Sun, Ren Wang, Yihua Zhang, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Sijia Liu, Yan Yan:
Forget Vectors at Play: Universal Input Perturbations Driving Machine Unlearning in Image Classification. CoRR abs/2412.16780 (2024) - 2023
- [c30]Haomin Zhuang, Yihua Zhang, Sijia Liu:
A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion. CVPR Workshops 2023: 2385-2392 - [c29]Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, Sijia Liu:
Understanding and Improving Visual Prompting: A Label-Mapping Perspective. CVPR 2023: 19133-19143 - [c28]Jinghan Jia, Yihua Zhang, Dogyoon Song, Sijia Liu, Alfred O. Hero III:
Robustness-Preserving Lifelong Learning Via Dataset Condensation. ICASSP 2023: 1-5 - [c27]Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu:
Robust Mixture-of-Expert Training for Convolutional Neural Networks. ICCV 2023: 90-101 - [c26]Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang:
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. ICLR 2023 - [c25]Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu:
What Is Missing in IRM Training and Evaluation? Challenges and Solutions. ICLR 2023 - [c24]Prashant Khanduri, Ioannis C. Tsaknakis, Yihua Zhang, Jia Liu, Sijia Liu, Jiawei Zhang, Mingyi Hong:
Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach. ICML 2023: 16291-16325 - [c23]Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu:
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. NeurIPS 2023 - [i22]Yihua Zhang, Pranay Sharma, Parikshit Ram, Mingyi Hong, Kush R. Varshney, Sijia Liu:
What Is Missing in IRM Training and Evaluation? Challenges and Solutions. CoRR abs/2303.02343 (2023) - [i21]Jinghan Jia, Yihua Zhang, Dogyoon Song, Sijia Liu, Alfred O. Hero III:
Robustness-preserving Lifelong Learning via Dataset Condensation. CoRR abs/2303.04183 (2023) - [i20]Haomin Zhuang, Yihua Zhang, Sijia Liu:
A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion. CoRR abs/2303.16378 (2023) - [i19]Yihua Zhang, Prashant Khanduri, Ioannis C. Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu:
An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning. CoRR abs/2308.00788 (2023) - [i18]Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu:
Robust Mixture-of-Expert Training for Convolutional Neural Networks. CoRR abs/2308.10110 (2023) - [i17]Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu:
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training. CoRR abs/2310.02025 (2023) - [i16]Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu:
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. CoRR abs/2310.08782 (2023) - [i15]Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu:
To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now. CoRR abs/2310.11868 (2023) - [i14]Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, Sijia Liu:
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. CoRR abs/2310.12508 (2023) - [i13]Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen:
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR abs/2312.01397 (2023) - 2022
- [c22]Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang:
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free. CVPR 2022: 588-599 - [c21]Yihua Zhang, Christian Stöhr, Susanne Strömberg Jämsvi, Jens Kabo:
Considering the Community of Inquiry Framework in Online Engineering Education. FIE 2022: 1-9 - [c20]Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu:
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. ICML 2022: 26693-26712 - [c19]Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu:
Advancing Model Pruning via Bi-level Optimization. NeurIPS 2022 - [c18]Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang:
Fairness Reprogramming. NeurIPS 2022 - [c17]Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu:
Distributed adversarial training to robustify deep neural networks at scale. UAI 2022: 2353-2363 - [i12]Tianlong Chen, Zhenyu Zhang, Yihua Zhang, Shiyu Chang, Sijia Liu, Zhangyang Wang:
Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free. CoRR abs/2205.11819 (2022) - [i11]Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu:
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale. CoRR abs/2206.06257 (2022) - [i10]Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang:
Fairness Reprogramming. CoRR abs/2209.10222 (2022) - [i9]Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu:
Advancing Model Pruning via Bi-level Optimization. CoRR abs/2210.04092 (2022) - [i8]Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, Sijia Liu:
Understanding and Improving Visual Prompting: A Label-Mapping Perspective. CoRR abs/2211.11635 (2022) - [i7]Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang:
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. CoRR abs/2212.09254 (2022) - 2021
- [i6]Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu:
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. CoRR abs/2112.12376 (2021) - 2020
- [c16]Xiangwen Liu, Yihua Zhang, Chuangji Zhou, Dan Li, Xiaoyan Gui, Li Geng:
A 16Gb/s Triple-Mode Driver in 0.18μm CMOS Technology. ICTA 2020: 96-97
2010 – 2019
- 2019
- [j9]Wan Li, Yihua Zhang, Yuehan He, Yahui Wang, Shanshan Guo, Xilei Zhao, Yuyan Feng, Zhaona Song, Yuqing Zou, Weiming He, Lina Chen:
Candidate gene prioritization for non-communicable diseases based on functional information: Case studies. J. Biomed. Informatics 93 (2019) - [j8]Xiao Fu, Zhijian Wang, Yunfeng Chen, Yihua Zhang, Hao Wu:
Bead Strand Model: a high-efficiency storage structure for self-destructing data in cloud environment. Serv. Oriented Comput. Appl. 13(2): 95-103 (2019) - [j7]Dan Li, Ming Liu, Shengwei Gao, Yongjun Shi, Yihua Zhang, Zhiyong Li, Patrick Yin Chiang, Franco Maloberti, Li Geng:
Low-Noise Broadband CMOS TIA Based on Multi-Stage Stagger-Tuned Amplifier for High-Speed High-Sensitivity Optical Communication. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(10): 3676-3689 (2019) - [c15]Yihua Zhang, Zhuoqi Guo, Yang Xie, Dan Li, Shiquan Fan, Xiaoyan Gui, Li Geng:
A Stacked 4×25 Gb/s Optical Receiver in 28 nm CMOS with 0.154 mW/Gb/s Power Efficiency. ISCAS 2019: 1-4 - 2018
- [j6]Yihua Zhang, Marina Blanton, Ghada Almashaqbeh:
Implementing Support for Pointers to Private Data in a General-Purpose Secure Multi-Party Compiler. ACM Trans. Priv. Secur. 21(2): 6:1-6:34 (2018) - [c14]Jun Chen, Yihua Zhang, Yuan Wang, Ruoli Ma:
Research on Interaction Modeling of Cross-border E-commerce and Import and Export Trade. ICSEB 2018: 15-19 - [c13]Yang Xie, Dan Li, Yiqun Liu, Ming Liu, Yihua Zhang, Xiaoli Wang, Li Geng:
Low-Noise High-Linearity 56Gb/s PAM-4 Optical Receiver in 45nm SOI CMOS. ISCAS 2018: 1-4 - 2017
- [c12]Yihua Zhang, Marina Blanton, Fattaneh Bayatbabolghani:
Enforcing Input Correctness via Certification in Garbled Circuit Evaluation. ESORICS (2) 2017: 552-569 - [i5]Yihua Zhang, Marina Blanton, Fattaneh Bayatbabolghani:
Enforcing Input Correctness via Certification in Garbled Circuit Evaluation. IACR Cryptol. ePrint Arch. 2017: 569 (2017) - 2016
- [j5]Yihua Zhang, Marina Blanton:
Efficient Dynamic Provable Possession of Remote Data via Update Trees. ACM Trans. Storage 12(2): 9:1-9:45 (2016) - [c11]Rui Xing, Ning Dai, Yicheng Zhong, Yihua Zhang, Yi Liu:
A modeling method of customized brackets and individualized trays for orthodontic treatment. CISP-BMEI 2016: 1562-1566 - 2015
- [j4]Yihua Zhang, Marina Blanton, Ghada Almashaqbeh:
Secure distributed genome analysis for GWAS and sequence comparison computation. BMC Medical Informatics Decis. Mak. 15-S(5): S4 (2015) - [i4]Yihua Zhang, Marina Blanton, Ghada Almashaqbeh:
Implementing Support for Pointers to Private Data in a General-Purpose Secure Multi-Party Compiler. CoRR abs/1509.01763 (2015) - 2014
- [j3]Shengping Zhang, Jiani Tan, Zhonghui Lai, Ying Li, Junxia Pang, Jianhu Xiao, Zhangjian Huang, Yihua Zhang, Hui Ji, Yisheng Lai:
Effective Virtual Screening Strategy toward Covalent Ligands: Identification of Novel NEDD8-Activating Enzyme Inhibitors. J. Chem. Inf. Model. 54(6): 1785-1797 (2014) - [c10]Yihua Zhang, Marina Blanton:
Efficient Secure and Verifiable Outsourcing of Matrix Multiplications. ISC 2014: 158-178 - [i3]Yihua Zhang, Marina Blanton:
Efficient Secure and Verifiable Outsourcing of Matrix Multiplications. IACR Cryptol. ePrint Arch. 2014: 133 (2014) - 2013
- [j2]Liang Gao, Dongming Li, Yihua Zhang:
Research of Weeds Classification System Based on Shape Feature. J. Softw. 8(7): 1736-1742 (2013) - [j1]Marina Blanton, Yihua Zhang, Keith B. Frikken:
Secure and verifiable outsourcing of large-scale biometric computations. ACM Trans. Inf. Syst. Secur. 16(3): 11 (2013) - [c9]Yihua Zhang, Marina Blanton:
Efficient dynamic provable possession of remote data via balanced update trees. AsiaCCS 2013: 183-194 - [c8]Yihua Zhang, Aaron Steele, Marina Blanton:
PICCO: a general-purpose compiler for private distributed computation. CCS 2013: 813-826 - [c7]Mehrdad Aliasgari, Marina Blanton, Yihua Zhang, Aaron Steele:
Secure Computation on Floating Point Numbers. NDSS 2013 - 2012
- [i2]Yihua Zhang, Marina Blanton:
Efficient Dynamic Provable Possession of Remote Data via Update Trees. IACR Cryptol. ePrint Arch. 2012: 291 (2012) - [i1]Mehrdad Aliasgari, Marina Blanton, Yihua Zhang, Aaron Steele:
Secure Computation on Floating Point Numbers. IACR Cryptol. ePrint Arch. 2012: 405 (2012) - 2011
- [c6]Yihua Zhang, Jia Peng, Di Huang, Fang Li:
Design of Automatic Mapping System between DDC and CLC. ICADL 2011: 357-366 - [c5]Marina Blanton, Yihua Zhang, Keith B. Frikken:
Secure and Verifiable Outsourcing of Large-Scale Biometric Computations. SocialCom/PASSAT 2011: 1185-1191 - 2010
- [c4]Keith B. Frikken, Yihua Zhang:
Sum Aggregation in Sensor Networks While Preserving Confidentiality and Integrity. ICETE (Selected Papers) 2010: 172-187 - [c3]Keith B. Frikken, Yihua Zhang:
Confidentiality and Integrity for SUM Aggregation in Sensor Networks. SECRYPT 2010: 231-240
2000 – 2009
- 2008
- [c2]Keith B. Frikken, Yihua Zhang:
Yet another privacy metric for publishing micro-data. WPES 2008: 117-122 - 2000
- [c1]Fan Mo, Yihua Zhang, Jun Yu, Qianling Zhang:
An algorithm for VLSI implementation of highly efficient cubic-polynomial evaluation. ASP-DAC 2000: 13-14
Coauthor Index
[c41] [c40] [i36] [i34] [j10] [c39] [c38] [c36] [c35] [c34] [c33] [c32] [c31] [i33] [i32] [i31] [i29] [i28] [i27] [i26] [i24] [i23] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [i15] [i14] [i13] [c22] [c20] [c19] [c18] [c17] [i12] [i11] [i10] [i9] [i8] [i7] [i6]
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