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Ruoxi Jia 0001
Person information
- affiliation: Virginia Tech, Blacksburg, VA, USA
- affiliation (PhD 2018): University of California at Berkeley, Berkeley, CA, USA
Other persons with the same name
- Ruoxi Jia 0002 — University of Southern California, Los Angeles, CA, USA
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2020 – today
- 2024
- [c57]Bilgehan Sel, Priya Shanmugasundaram, Mohammad Kachuee, Kun Zhou, Ruoxi Jia, Ming Jin:
Skin-in-the-Game: Decision Making via Multi-Stakeholder Alignment in LLMs. ACL (1) 2024: 13921-13959 - [c56]Yi Zeng, Hongpeng Lin, Jingwen Zhang, Diyi Yang, Ruoxi Jia, Weiyan Shi:
How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs. ACL (1) 2024: 14322-14350 - [c55]Jiachen T. Wang, Prateek Mittal, Ruoxi Jia:
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms. AISTATS 2024: 2557-2565 - [c54]Myeongseob Ko, Feiyang Kang, Weiyan Shi, Ming Jin, Zhou Yu, Ruoxi Jia:
The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes. CVPR 2024: 26276-26285 - [c53]Si Chen, Feiyang Kang, Ning Yu, Ruoxi Jia:
FASTTRACK: Reliable Fact Tracing via Clustering and LLM-Powered Evidence Validation. EMNLP (Findings) 2024: 5821-5836 - [c52]Yi Zeng, Weiyu Sun, Tran Ngoc Huynh, Dawn Song, Bo Li, Ruoxi Jia:
BEEAR: Embedding-based Adversarial Removal of Safety Backdoors in Instruction-tuned Language Models. EMNLP 2024: 13189-13215 - [c51]Jianfeng He, Runing Yang, Linlin Yu, Changbin Li, Ruoxi Jia, Feng Chen, Ming Jin, Chang-Tien Lu:
Can We Trust the Performance Evaluation of Uncertainty Estimation Methods in Text Summarization? EMNLP 2024: 16514-16575 - [c50]Feiyang Kang, Hoang Anh Just, Yifan Sun, Himanshu Jahagirdar, Yuanzhi Zhang, Rongxing Du, Anit Kumar Sahu, Ruoxi Jia:
Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs. ICLR 2024 - [c49]Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson:
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! ICLR 2024 - [c48]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
Position: A Safe Harbor for AI Evaluation and Red Teaming. ICML 2024 - [c47]Elena Orlova, Aleksei Ustimenko, Ruoxi Jia, Peter Y. Lu, Rebecca Willett:
Deep Stochastic Mechanics. ICML 2024 - [c46]Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar, Ruoxi Jia, Ming Jin:
Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models. ICML 2024 - [c45]Jiachen T. Wang, Tianji Yang, James Zou, Yongchan Kwon, Ruoxi Jia:
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits. ICML 2024 - [c44]Zhuowen Yuan, Zidi Xiong, Yi Zeng, Ning Yu, Ruoxi Jia, Dawn Song, Bo Li:
RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content. ICML 2024 - [i76]Yi Zeng, Hongpeng Lin, Jingwen Zhang, Diyi Yang, Ruoxi Jia, Weiyan Shi:
How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs. CoRR abs/2401.06373 (2024) - [i75]Jiachen T. Wang, Prateek Mittal, Ruoxi Jia:
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms. CoRR abs/2401.11103 (2024) - [i74]Myeongseob Ko, Feiyang Kang, Weiyan Shi, Ming Jin, Zhou Yu, Ruoxi Jia:
The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes. CoRR abs/2402.08922 (2024) - [i73]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
A Safe Harbor for AI Evaluation and Red Teaming. CoRR abs/2403.04893 (2024) - [i72]Chenguang Wang, Ruoxi Jia, Xin Liu, Dawn Song:
Benchmarking Zero-Shot Robustness of Multimodal Foundation Models: A Pilot Study. CoRR abs/2403.10499 (2024) - [i71]Zhuowen Yuan, Zidi Xiong, Yi Zeng, Ning Yu, Ruoxi Jia, Dawn Song, Bo Li:
RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content. CoRR abs/2403.13031 (2024) - [i70]Si Chen, Feiyang Kang, Ning Yu, Ruoxi Jia:
FASTTRACK: Fast and Accurate Fact Tracing for LLMs. CoRR abs/2404.15157 (2024) - [i69]Feiyang Kang, Hoang Anh Just, Yifan Sun, Himanshu Jahagirdar, Yuanzhi Zhang, Rongxing Du, Anit Kumar Sahu, Ruoxi Jia:
Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs. CoRR abs/2405.02774 (2024) - [i68]Jiachen T. Wang, Tianji Yang, James Zou, Yongchan Kwon, Ruoxi Jia:
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits. CoRR abs/2405.03875 (2024) - [i67]Bilgehan Sel, Priya Shanmugasundaram, Mohammad Kachuee, Kun Zhou, Ruoxi Jia, Ming Jin:
Skin-in-the-Game: Decision Making via Multi-Stakeholder Alignment in LLMs. CoRR abs/2405.12933 (2024) - [i66]Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal:
AI Risk Management Should Incorporate Both Safety and Security. CoRR abs/2405.19524 (2024) - [i65]Minzhou Pan, Yi Zeng, Xue Lin, Ning Yu, Cho-Jui Hsieh, Peter Henderson, Ruoxi Jia:
JIGMARK: A Black-Box Approach for Enhancing Image Watermarks against Diffusion Model Edits. CoRR abs/2406.03720 (2024) - [i64]Yi Zeng, Xuelin Yang, Li Chen, Cristian Canton Ferrer, Ming Jin, Michael I. Jordan, Ruoxi Jia:
Fairness-Aware Meta-Learning via Nash Bargaining. CoRR abs/2406.07029 (2024) - [i63]Jiachen T. Wang, Prateek Mittal, Dawn Song, Ruoxi Jia:
Data Shapley in One Training Run. CoRR abs/2406.11011 (2024) - [i62]Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal:
SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors. CoRR abs/2406.14598 (2024) - [i61]Yi Zeng, Weiyu Sun, Tran Ngoc Huynh, Dawn Song, Bo Li, Ruoxi Jia:
BEEAR: Embedding-based Adversarial Removal of Safety Backdoors in Instruction-tuned Language Models. CoRR abs/2406.17092 (2024) - [i60]Jianfeng He, Runing Yang, Linlin Yu, Changbin Li, Ruoxi Jia, Feng Chen, Ming Jin, Chang-Tien Lu:
Can We Trust the Performance Evaluation of Uncertainty Estimation Methods in Text Summarization? CoRR abs/2406.17274 (2024) - [i59]Yi Zeng, Kevin Klyman, Andy Zhou, Yu Yang, Minzhou Pan, Ruoxi Jia, Dawn Song, Percy Liang, Bo Li:
AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies. CoRR abs/2406.17864 (2024) - [i58]Hoang Anh Just, Ming Jin, Anit Kumar Sahu, Huy Phan, Ruoxi Jia:
Data-Centric Human Preference Optimization with Rationales. CoRR abs/2407.14477 (2024) - [i57]Yi Zeng, Yu Yang, Andy Zhou, Jeffrey Ziwei Tan, Yuheng Tu, Yifan Mai, Kevin Klyman, Minzhou Pan, Ruoxi Jia, Dawn Song, Percy Liang, Bo Li:
AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies. CoRR abs/2407.17436 (2024) - [i56]Mengmeng Wu, Zhihong Liu, Xiang Li, Ruoxi Jia, Xiangyu Chang:
Uncertainty Quantification of Data Shapley via Statistical Inference. CoRR abs/2407.19373 (2024) - [i55]Feiyang Kang, Yifan Sun, Bingbing Wen, Si Chen, Dawn Song, Rafid Mahmood, Ruoxi Jia:
AutoScale: Automatic Prediction of Compute-optimal Data Composition for Training LLMs. CoRR abs/2407.20177 (2024) - [i54]Hoang Anh Just, Mahavir Dabas, Lifu Huang, Ming Jin, Ruoxi Jia:
DiPT: Enhancing LLM reasoning through diversified perspective-taking. CoRR abs/2409.06241 (2024) - [i53]Xi Zheng, Xiangyu Chang, Ruoxi Jia, Yong Tan:
Towards Data Valuation via Asymmetric Data Shapley. CoRR abs/2411.00388 (2024) - 2023
- [j11]Mengmeng Wu, Ruoxi Jia, Changle Lin, Wei Huang, Xiangyu Chang:
Variance reduced Shapley value estimation for trustworthy data valuation. Comput. Oper. Res. 159: 106305 (2023) - [j10]Runing Yang, Ruoxi Jia, Xiangyu Zhang, Ming Jin:
Certifiably Robust Neural ODE With Learning-Based Barrier Function. IEEE Control. Syst. Lett. 7: 1634-1639 (2023) - [j9]Si Chen, Yi Zeng, Won Park, Jiachen T. Wang, Xun Chen, Lingjuan Lyu, Zhuoqing Mao, Ruoxi Jia:
Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion. Trans. Mach. Learn. Res. 2023 (2023) - [j8]Jiachen T. Wang, Si Chen, Ruoxi Jia:
One-Round Active Learning through Data Utility Learning and Proxy Models. Trans. Mach. Learn. Res. 2023 (2023) - [c43]Ming Jin, Vanshaj Khattar, Harshal Kaushik, Bilgehan Sel, Ruoxi Jia:
On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds. AAAI 2023: 8123-8131 - [c42]Jiachen T. Wang, Ruoxi Jia:
Data Banzhaf: A Robust Data Valuation Framework for Machine Learning. AISTATS 2023: 6388-6421 - [c41]Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, Ruoxi Jia:
Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information. CCS 2023: 771-785 - [c40]Myeongseob Ko, Ming Jin, Chenguang Wang, Ruoxi Jia:
Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study. ICCV 2023: 4848-4858 - [c39]Hoang Anh Just, Feiyang Kang, Tianhao Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia:
LAVA: Data Valuation without Pre-Specified Learning Algorithms. ICLR 2023 - [c38]Yi Zeng, Zhouxing Shi, Ming Jin, Feiyang Kang, Lingjuan Lyu, Cho-Jui Hsieh, Ruoxi Jia:
Towards Robustness Certification Against Universal Perturbations. ICLR 2023 - [c37]Junyuan Hong, Yi Zeng, Shuyang Yu, Lingjuan Lyu, Ruoxi Jia, Jiayu Zhou:
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers. ICML 2023: 13199-13212 - [c36]Zhihong Liu, Hoang Anh Just, Xiangyu Chang, Xi Chen, Ruoxi Jia:
2D-Shapley: A Framework for Fragmented Data Valuation. ICML 2023: 21730-21755 - [c35]Bilgehan Sel, Ahmad Al-Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, Ming Jin:
Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold. L4DC 2023: 38-50 - [c34]Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia:
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources. NeurIPS 2023 - [c33]Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal:
A Privacy-Friendly Approach to Data Valuation. NeurIPS 2023 - [c32]Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal:
A Randomized Approach to Tight Privacy Accounting. NeurIPS 2023 - [c31]Myeongseob Ko, Xinyu Yang, Zhengjie Ji, Hoang Anh Just, Peng Gao, Anoop Kumar, Ruoxi Jia:
PrivMon: A Stream-Based System for Real-Time Privacy Attack Detection for Machine Learning Models. RAID 2023: 264-281 - [c30]Yingyan Zeng, Jiachen T. Wang, Si Chen, Hoang Anh Just, Ran Jin, Ruoxi Jia:
ModelPred: A Framework for Predicting Trained Model from Training Data. SaTML 2023: 432-449 - [c29]Yi Zeng, Minzhou Pan, Himanshu Jahagirdar, Ming Jin, Lingjuan Lyu, Ruoxi Jia:
Meta-Sift: How to Sift Out a Clean Subset in the Presence of Data Poisoning? USENIX Security Symposium 2023: 1667-1684 - [c28]Minzhou Pan, Yi Zeng, Lingjuan Lyu, Xue Lin, Ruoxi Jia:
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms. USENIX Security Symposium 2023: 2725-2742 - [i52]Minzhou Pan, Yi Zeng, Lingjuan Lyu, Xue Lin, Ruoxi Jia:
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms. CoRR abs/2302.11408 (2023) - [i51]Jiachen T. Wang, Ruoxi Jia:
A Note on "Towards Efficient Data Valuation Based on the Shapley Value". CoRR abs/2302.11431 (2023) - [i50]Jiachen T. Wang, Ruoxi Jia:
A Note on "Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms". CoRR abs/2304.04258 (2023) - [i49]Jiachen T. Wang, Saeed Mahloujifar, Tong Wu, Ruoxi Jia, Prateek Mittal:
A Randomized Approach for Tight Privacy Accounting. CoRR abs/2304.07927 (2023) - [i48]Hoang Anh Just, Feiyang Kang, Jiachen T. Wang, Yi Zeng, Myeongseob Ko, Ming Jin, Ruoxi Jia:
LAVA: Data Valuation without Pre-Specified Learning Algorithms. CoRR abs/2305.00054 (2023) - [i47]Junyuan Hong, Yi Zeng, Shuyang Yu, Lingjuan Lyu, Ruoxi Jia, Jiayu Zhou:
Revisiting Data-Free Knowledge Distillation with Poisoned Teachers. CoRR abs/2306.02368 (2023) - [i46]Zhihong Liu, Hoang Anh Just, Xiangyu Chang, Xi Chen, Ruoxi Jia:
2D-Shapley: A Framework for Fragmented Data Valuation. CoRR abs/2306.10473 (2023) - [i45]Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia:
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources. CoRR abs/2307.02460 (2023) - [i44]Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar, Lu Wang, Ruoxi Jia, Ming Jin:
Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models. CoRR abs/2308.10379 (2023) - [i43]Jiachen T. Wang, Yuqing Zhu, Yu-Xiang Wang, Ruoxi Jia, Prateek Mittal:
Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation. CoRR abs/2308.15709 (2023) - [i42]Myeongseob Ko, Ming Jin, Chenguang Wang, Ruoxi Jia:
Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study. CoRR abs/2310.00108 (2023) - [i41]Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson:
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! CoRR abs/2310.03693 (2023) - [i40]Zixin Ding, Si Chen, Ruoxi Jia, Yuxin Chen:
Learning to Rank for Active Learning via Multi-Task Bilevel Optimization. CoRR abs/2310.17044 (2023) - [i39]Lingjiao Chen, Bilge Acun, Newsha Ardalani, Yifan Sun, Feiyang Kang, Hanrui Lyu, Yongchan Kwon, Ruoxi Jia, Carole-Jean Wu, Matei Zaharia, James Zou:
Data Acquisition: A New Frontier in Data-centric AI. CoRR abs/2311.13712 (2023) - [i38]Shuyang Yu, Junyuan Hong, Yi Zeng, Fei Wang, Ruoxi Jia, Jiayu Zhou:
Who Leaked the Model? Tracking IP Infringers in Accountable Federated Learning. CoRR abs/2312.03205 (2023) - 2022
- [c27]Mostafa Kahla, Si Chen, Hoang Anh Just, Ruoxi Jia:
Label-Only Model Inversion Attacks via Boundary Repulsion. CVPR 2022: 15025-15033 - [c26]Weiyan Shi, Ryan Shea, Si Chen, Chiyuan Zhang, Ruoxi Jia, Zhou Yu:
Just Fine-tune Twice: Selective Differential Privacy for Large Language Models. EMNLP 2022: 6327-6340 - [c25]Yi Zeng, Si Chen, Won Park, Zhuoqing Mao, Ming Jin, Ruoxi Jia:
Adversarial Unlearning of Backdoors via Implicit Hypergradient. ICLR 2022 - [c24]Weiyan Shi, Aiqi Cui, Evan Li, Ruoxi Jia, Zhou Yu:
Selective Differential Privacy for Language Modeling. NAACL-HLT 2022: 2848-2859 - [c23]Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia:
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks. NeurIPS 2022 - [c22]Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal:
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning. NeurIPS 2022 - [i37]Mostafa Kahla, Si Chen, Hoang Anh Just, Ruoxi Jia:
Label-Only Model Inversion Attacks via Boundary Repulsion. CoRR abs/2203.01925 (2022) - [i36]Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, Ruoxi Jia:
Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information. CoRR abs/2204.05255 (2022) - [i35]Weiyan Shi, Si Chen, Chiyuan Zhang, Ruoxi Jia, Zhou Yu:
Just Fine-tune Twice: Selective Differential Privacy for Large Language Models. CoRR abs/2204.07667 (2022) - [i34]Jie Zhang, Chen Chen, Jiahua Dong, Ruoxi Jia, Lingjuan Lyu:
QEKD: Query-Efficient and Data-Free Knowledge Distillation from Black-box Models. CoRR abs/2205.11158 (2022) - [i33]Tianhao Wang, Ruoxi Jia:
Data Banzhaf: A Data Valuation Framework with Maximal Robustness to Learning Stochasticity. CoRR abs/2205.15466 (2022) - [i32]Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal:
Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning. CoRR abs/2209.07716 (2022) - [i31]Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia:
CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks. CoRR abs/2209.08773 (2022) - [i30]Yi Zeng, Minzhou Pan, Himanshu Jahagirdar, Ming Jin, Lingjuan Lyu, Ruoxi Jia:
How to Sift Out a Clean Data Subset in the Presence of Data Poisoning? CoRR abs/2210.06516 (2022) - [i29]Zhihua Tian, Jian Liu, Jingyu Li, Xinle Cao, Ruoxi Jia, Kui Ren:
Private Data Valuation and Fair Payment in Data Marketplaces. CoRR abs/2210.08723 (2022) - [i28]Mengmeng Wu, Ruoxi Jia, Changle Lin, Wei Huang, Xiangyu Chang:
Robust Data Valuation via Variance Reduced Data Shapley. CoRR abs/2210.16835 (2022) - [i27]Ming Jin, Vanshaj Khattar, Harshal Kaushik, Bilgehan Sel, Ruoxi Jia:
On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds. CoRR abs/2212.01314 (2022) - 2021
- [j7]Yi Zhao, Ke Xu, Haiyang Wang, Bo Li, Ruoxi Jia:
Stability-Based Analysis and Defense against Backdoor Attacks on Edge Computing Services. IEEE Netw. 35(1): 163-169 (2021) - [j6]Wenxiao Wang, Tianhao Wang, Lun Wang, Nanqing Luo, Pan Zhou, Dawn Song, Ruoxi Jia:
DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing. Proc. Priv. Enhancing Technol. 2021(4): 163-183 (2021) - [c21]Tianhao Wang, Yuheng Zhang, Ruoxi Jia:
Improving Robustness to Model Inversion Attacks via Mutual Information Regularization. AAAI 2021: 11666-11673 - [c20]Xinyun Chen, Wenxiao Wang, Chris Bender, Yiming Ding, Ruoxi Jia, Bo Li, Dawn Song:
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data. AsiaCCS 2021: 321-335 - [c19]Ruoxi Jia, Fan Wu, Xuehui Sun, Jiacen Xu, David Dao, Bhavya Kailkhura, Ce Zhang, Bo Li, Dawn Song:
Scalability vs. Utility: Do We Have To Sacrifice One for the Other in Data Importance Quantification? CVPR 2021: 8239-8247 - [c18]Si Chen, Mostafa Kahla, Ruoxi Jia, Guo-Jun Qi:
Knowledge-Enriched Distributional Model Inversion Attacks. ICCV 2021: 16158-16167 - [c17]Yi Zeng, Won Park, Z. Morley Mao, Ruoxi Jia:
Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective. ICCV 2021: 16453-16461 - [c16]Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu:
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective. ICLR 2021 - [i26]Wenxiao Wang, Tianhao Wang, Lun Wang, Nanqing Luo, Pan Zhou, Dawn Song, Ruoxi Jia:
DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing. CoRR abs/2103.01496 (2021) - [i25]Yi Zeng, Won Park, Z. Morley Mao, Ruoxi Jia:
Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective. CoRR abs/2104.03413 (2021) - [i24]Tianhao Wang, Si Chen, Ruoxi Jia:
One-Round Active Learning. CoRR abs/2104.11843 (2021) - [i23]Tianhao Wang, Yi Zeng, Ming Jin, Ruoxi Jia:
A Unified Framework for Task-Driven Data Quality Management. CoRR abs/2106.05484 (2021) - [i22]Tianhao Wang, Yu Yang, Ruoxi Jia:
Learnability of Learning Performance and Its Application to Data Valuation. CoRR abs/2107.06336 (2021) - [i21]Si Chen, Tianhao Wang, Ruoxi Jia:
Zero-Round Active Learning. CoRR abs/2107.06703 (2021) - [i20]Weiyan Shi, Aiqi Cui, Evan Li, Ruoxi Jia, Zhou Yu:
Selective Differential Privacy for Language Modeling. CoRR abs/2108.12944 (2021) - [i19]Yi Zeng, Si Chen, Won Park, Z. Morley Mao, Ming Jin, Ruoxi Jia:
Adversarial Unlearning of Backdoors via Implicit Hypergradient. CoRR abs/2110.03735 (2021) - [i18]Yingyan Zeng, Tianhao Wang, Si Chen, Hoang Anh Just, Ran Jin, Ruoxi Jia:
Learning to Refit for Convex Learning Problems. CoRR abs/2111.12545 (2021) - 2020
- [c15]Yuheng Zhang, Ruoxi Jia, Hengzhi Pei, Wenxiao Wang, Bo Li, Dawn Song:
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks. CVPR 2020: 250-258 - [c14]Min Du, Ruoxi Jia, Dawn Song:
Robust anomaly detection and backdoor attack detection via differential privacy. ICLR 2020 - [c13]Gerald Friedland, Ruoxi Jia, Jingkang Wang, Bo Li, T. Nathan Mundhenk:
On the Impact of Perceptual Compression on Deep Learning. MIPR 2020: 219-224 - [p1]Tianhao Wang, Johannes Rausch, Ce Zhang, Ruoxi Jia, Dawn Song:
A Principled Approach to Data Valuation for Federated Learning. Federated Learning 2020: 153-167 - [i17]Lun Wang, Ruoxi Jia:
Private Distributed Mean Estimation. CoRR abs/2006.13039 (2020) - [i16]Tianhao Wang, Yuheng Zhang, Ruoxi Jia:
Improving Robustness to Model Inversion Attacks via Mutual Information Regularization. CoRR abs/2009.05241 (2020) - [i15]Tianhao Wang, Johannes Rausch, Ce Zhang, Ruoxi Jia, Dawn Song:
A Principled Approach to Data Valuation for Federated Learning. CoRR abs/2009.06192 (2020) - [i14]Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu:
InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective. CoRR abs/2010.02329 (2020) - [i13]Si Chen, Ruoxi Jia, Guo-Jun Qi:
Improved Techniques for Model Inversion Attacks. CoRR abs/2010.04092 (2020)
2010 – 2019
- 2019
- [j5]Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song:
Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms. Proc. VLDB Endow. 12(11): 1610-1623 (2019) - [c12]Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos:
Towards Efficient Data Valuation Based on the Shapley Value. AISTATS 2019: 1167-1176 - [i12]Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nick Hynes, Nezihe Merve Gürel, Bo Li, Ce Zhang, Dawn Song, Costas J. Spanos:
Towards Efficient Data Valuation Based on the Shapley Value. CoRR abs/1902.10275 (2019) - [i11]Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gürel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song:
Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms. CoRR abs/1908.08619 (2019) - [i10]Min Du, Ruoxi Jia, Dawn Song:
Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy. CoRR abs/1911.07116 (2019) - [i9]Ruoxi Jia, Xuehui Sun, Jiacen Xu, Ce Zhang, Bo Li, Dawn Song:
An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms. CoRR abs/1911.07128 (2019) - [i8]Yuheng Zhang, Ruoxi Jia, Hengzhi Pei, Wenxiao Wang, Bo Li, Dawn Song:
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks. CoRR abs/1911.07135 (2019) - [i7]Xinyun Chen, Wenxiao Wang, Chris Bender, Yiming Ding, Ruoxi Jia, Bo Li, Dawn Song:
REFIT: a Unified Watermark Removal Framework for Deep Learning Systems with Limited Data. CoRR abs/1911.07205 (2019) - 2018
- [b1]Ruoxi Jia:
Accountable Data Fusion and Privacy Preservation Techniques in Cyber-Physical Systems. University of California, Berkeley, USA, 2018 - [j4]Ruoxi Jia, Baihong Jin, Ming Jin, Yuxun Zhou, Ioannis C. Konstantakopoulos, Han Zou, Joyce Kim, Dan Li, Weixi Gu, Reza Arghandeh, Pierluigi Nuzzo, Stefano Schiavon, Alberto L. Sangiovanni-Vincentelli, Costas J. Spanos:
Design Automation for Smart Building Systems. Proc. IEEE 106(9): 1680-1699 (2018) - [j3]Fisayo Caleb Sangogboye, Ruoxi Jia, Tianzhen Hong, Costas J. Spanos, Mikkel Baun Kjærgaard:
A Framework for Privacy-Preserving Data Publishing with Enhanced Utility for Cyber-Physical Systems. ACM Trans. Sens. Networks 14(3-4): 30:1-30:22 (2018) - [c11]Ruoxi Jia, Ioannis C. Konstantakopoulos, Bo Li, Costas J. Spanos:
Poisoning Attacks on Data-Driven Utility Learning in Games. ACC 2018: 5774-5780 - [i6]Gerald Friedland, Jingkang Wang, Ruoxi Jia, Bo Li:
The Helmholtz Method: Using Perceptual Compression to Reduce Machine Learning Complexity. CoRR abs/1807.10569 (2018) - [i5]Jingkang Wang, Ruoxi Jia, Gerald Friedland, Bo Li, Costas J. Spanos:
One Bit Matters: Understanding Adversarial Examples as the Abuse of Redundancy. CoRR abs/1810.09650 (2018) - 2017
- [j2]Ming Jin, Ruoxi Jia, Costas J. Spanos:
Virtual Occupancy Sensing: Using Smart Meters to Indicate Your Presence. IEEE Trans. Mob. Comput. 16(11): 3264-3277 (2017) - [c10]Ruoxi Jia, Roy Dong, Prashanth Ganesh, Shankar Sastry, Costas J. Spanos:
Towards a theory of free-lunch privacy in cyber-physical systems. Allerton 2017: 902-910 - [c9]Ruoxi Jia, Roy Dong, Shankar Sastry, Costas J. Spanos:
Optimal sensor-controller codesign for privacy in dynamical systems. CDC 2017: 4004-4011 - [c8]Ruoxi Jia, Roy Dong, S. Shankar Sastry, Costas J. Spanos:
Privacy-enhanced architecture for occupancy-based HVAC Control. ICCPS 2017: 177-186 - [c7]Ruoxi Jia, Fisayo Caleb Sangogboye, Tianzhen Hong, Costas J. Spanos, Mikkel Baun Kjærgaard:
PAD: protecting anonymity in publishing building related datasets. BuildSys 2017: 4:1-4:10 - [c6]Ruoxi Jia, Fisayo Caleb Sangogboye, Tianzhen Hong, Costas J. Spanos, Mikkel Baun Kjærgaard:
Privacy-preserving building-related data publication using PAD. BuildSys 2017: 32:1-32:2 - 2016
- [j1]Ruoxi Jia, Ming Jin, Han Zou, Yigitcan Yesilata, Lihua Xie, Costas J. Spanos:
MapSentinel: Can the Knowledge of Space Use Improve Indoor Tracking Further? Sensors 16(4): 472 (2016) - [i4]Ruoxi Jia, Roy Dong, S. Shankar Sastry, Costas J. Spanos:
Privacy-Enhanced Architecture for Occupancy-based HVAC Control. CoRR abs/1607.03140 (2016) - 2015
- [c5]Ruoxi Jia, Ming Jin, Zilong Chen, Costas J. Spanos:
SoundLoc: Accurate room-level indoor localization using acoustic signatures. CASE 2015: 186-193 - [c4]Ruoxi Jia, Ming Jin, Han Zou, Yigitcan Yesilata, Lihua Xie, Costas J. Spanos:
Poster Abstract: MapSentinel: Map-Aided Non-intrusive Indoor Tracking in Sensor-Rich Environments. BuildSys 2015: 109-110 - [c3]Ruoxi Jia, Yang Gao, Costas J. Spanos:
A fully unsupervised non-intrusive load monitoring framework. SmartGridComm 2015: 872-878 - 2014
- [c2]Ming Jin, Han Zou, Kevin Weekly, Ruoxi Jia, Alexandre M. Bayen, Costas J. Spanos:
Environmental sensing by wearable device for indoor activity and location estimation. IECON 2014: 5369-5375 - [c1]Ming Jin, Ruoxi Jia, Zhaoyi Kang, Ioannis C. Konstantakopoulos, Costas J. Spanos:
PresenceSense: zero-training algorithm for individual presence detection based on power monitoring. BuildSys 2014: 1-10 - [i3]Ming Jin, Han Zou, Kevin Weekly, Ruoxi Jia, Alexandre M. Bayen, Costas J. Spanos:
Environmental Sensing by Wearable Device for Indoor Activity and Location Estimation. CoRR abs/1406.5765 (2014) - [i2]Ming Jin, Ruoxi Jia, Zhaoyi Kang, Ioannis C. Konstantakopoulos, Costas J. Spanos:
PresenceSense: Zero-training Algorithm for Individual Presence Detection based on Power Monitoring. CoRR abs/1407.4395 (2014) - [i1]Ruoxi Jia, Ming Jin, Costas J. Spanos:
SoundLoc: Acoustic Method for Indoor Localization without Infrastructure. CoRR abs/1407.4409 (2014)
Coauthor Index
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