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Yiren Zhao
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2020 – today
- 2024
- [j2]Le Yu
, Zhiheng Liang
, Yaqi Li, Shiwei Zhang, Yiren Zhao, Peter Y. K. Cheung:
Verification and Fault Injection Platform Based on MTB Stimulus Generation Method for L2 Deep Market Quote Decoder. IEEE Access 12: 54272-54284 (2024) - [j1]Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao
, Nicolas Papernot, Ross J. Anderson
, Yarin Gal
:
AI models collapse when trained on recursively generated data. Nat. 631(8022): 755-759 (2024) - [c26]Eleanor Clifford, Ilia Shumailov, Yiren Zhao, Ross J. Anderson, Robert D. Mullins:
ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks. SaTML 2024: 344-357 - [i47]Cheng Zhang, Jianyi Cheng, George A. Constantinides, Yiren Zhao:
LQER: Low-Rank Quantization Error Reconstruction for LLMs. CoRR abs/2402.02446 (2024) - [i46]Zehui Li, Yuhao Ni, William A. V. Beardall, Guoxuan Xia, Akashaditya Das, Guy-Bart Stan, Yiren Zhao:
DiscDiff: Latent Diffusion Model for DNA Sequence Generation. CoRR abs/2402.06079 (2024) - [i45]Harry Langford, Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Nicolas Papernot:
Architectural Neural Backdoors from First Principles. CoRR abs/2402.06957 (2024) - [i44]Xiangyu Zhao, Zehui Li, Mingzhu Shen, Guy-Bart Stan, Pietro Liò, Yiren Zhao:
Enhancing Real-World Complex Network Representations with Hyperedge Augmentation. CoRR abs/2402.13033 (2024) - [i43]Eleanor Clifford, Adhithya Saravanan, Harry Langford, Cheng Zhang, Yiren Zhao, Robert D. Mullins, Ilia Shumailov, Jamie Hayes:
Locking Machine Learning Models into Hardware. CoRR abs/2405.20990 (2024) - [i42]Pengtao Chen, Mingzhu Shen, Peng Ye, Jianjian Cao, Chongjun Tu, Christos-Savvas Bouganis, Yiren Zhao, Tao Chen:
Δ-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers. CoRR abs/2406.01125 (2024) - [i41]Zhewen Yu, Sudarshan Sreeram, Krish Agrawal, Junyi Wu, Alexander Montgomerie-Corcoran, Cheng Zhang, Jianyi Cheng, Christos-Savvas Bouganis, Yiren Zhao:
HASS: Hardware-Aware Sparsity Search for Dataflow DNN Accelerator. CoRR abs/2406.03088 (2024) - [i40]Zixi Zhang, Cheng Zhang, Xitong Gao, Robert D. Mullins, George A. Constantinides, Yiren Zhao:
Unlocking the Global Synergies in Low-Rank Adapters. CoRR abs/2406.14956 (2024) - [i39]Yuang Chen, Cheng Zhang, Xitong Gao, Robert D. Mullins, George A. Constantinides, Yiren Zhao:
Optimised Grouped-Query Attention Mechanism for Transformers. CoRR abs/2406.14963 (2024) - [i38]Zehui Li, Vallijah Subasri, Guy-Bart Stan, Yiren Zhao, Bo Wang:
GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning. CoRR abs/2407.16940 (2024) - 2023
- [c25]Yulin Zhou, Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Yarin Gal:
Revisiting Automated Prompting: Are We Actually Doing Better? ACL (2) 2023: 1822-1832 - [c24]Yiren Zhao, Oluwatomisin Dada, Robert D. Mullins, Xitong Gao:
Revisiting Structured Dropout. ACML 2023: 1699-1714 - [c23]Dongping Liao, Xitong Gao, Yiren Zhao, Chengzhong Xu:
Adaptive Channel Sparsity for Federated Learning under System Heterogeneity. CVPR 2023: 20432-20441 - [c22]Mikel Bober-Irizar, Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Nicolas Papernot:
Architectural Backdoors in Neural Networks. CVPR 2023: 24595-24604 - [c21]Guo Yang, Daniel Lo, Robert D. Mullins, Yiren Zhao:
Dynamic Stashing Quantization for Efficient Transformer Training. EMNLP (Findings) 2023: 7329-7336 - [c20]Cheng Zhang, Jianyi Cheng, Ilia Shumailov, George A. Constantinides, Yiren Zhao:
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference? EMNLP 2023: 9988-10006 - [c19]Xiandong Zou, Xiangyu Zhao, Pietro Lio, Yiren Zhao:
Will More Expressive Graph Neural Networks Do Better on Generative Tasks? LoG 2023: 21 - [c18]Han Cui, Shu Zhong, Jiacheng Wu, Zichao Shen, Naim Dahnoun, Yiren Zhao:
MiliPoint: A Point Cloud Dataset for mmWave Radar. NeurIPS 2023 - [c17]Congcong Miao
, Zhizhen Zhong
, Ying Zhang
, Kunling He
, Fangchao Li
, Minggang Chen
, Yiren Zhao
, Xiang Li
, Zekun He
, Xianneng Zou
, Jilong Wang
:
FlexWAN: Software Hardware Co-design for Cost-Effective and Resilient Optical Backbones. SIGCOMM 2023: 319-332 - [i37]Xiangyu Zhao, Hannes Stärk, Dominique Beaini, Pietro Liò, Yiren Zhao:
Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration. CoRR abs/2301.11517 (2023) - [i36]Guo Yang, Daniel Lo, Robert D. Mullins, Yiren Zhao:
Dynamic Stashing Quantization for Efficient Transformer Training. CoRR abs/2303.05295 (2023) - [i35]Yulin Zhou, Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Yarin Gal:
Revisiting Automated Prompting: Are We Actually Doing Better? CoRR abs/2304.03609 (2023) - [i34]Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, Ross J. Anderson:
The Curse of Recursion: Training on Generated Data Makes Models Forget. CoRR abs/2305.17493 (2023) - [i33]Zehui Li, Xiangyu Zhao, Mingzhu Shen, Guy-Bart Stan, Pietro Liò, Yiren Zhao:
Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs. CoRR abs/2306.05108 (2023) - [i32]Zehui Li, Akashaditya Das, William A. V. Beardall, Yiren Zhao, Guy-Bart Stan:
Genomic Interpreter: A Hierarchical Genomic Deep Neural Network with 1D Shifted Window Transformer. CoRR abs/2306.05143 (2023) - [i31]Jianyi Cheng, Cheng Zhang, Zhewen Yu, Alexander Montgomerie-Corcoran, Can Xiao, Christos-Savvas Bouganis, Yiren Zhao:
Fast Prototyping Next-Generation Accelerators for New ML Models using MASE: ML Accelerator System Exploration. CoRR abs/2307.15517 (2023) - [i30]Xiandong Zou, Xiangyu Zhao, Pietro Liò, Yiren Zhao:
Will More Expressive Graph Neural Networks do Better on Generative Tasks? CoRR abs/2308.11978 (2023) - [i29]Han Cui, Shu Zhong, Jiacheng Wu, Zichao Shen, Naim Dahnoun, Yiren Zhao:
MiliPoint: A Point Cloud Dataset for mmWave Radar. CoRR abs/2309.13425 (2023) - [i28]Zixi Zhang, Greg Chadwick, Hugo McNally, Yiren Zhao, Robert D. Mullins:
LLM4DV: Using Large Language Models for Hardware Test Stimuli Generation. CoRR abs/2310.04535 (2023) - [i27]Cheng Zhang, Jianyi Cheng, Ilia Shumailov, George A. Constantinides, Yiren Zhao:
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference? CoRR abs/2310.05079 (2023) - [i26]Zehui Li, Yuhao Ni, Tim August B. Huygelen, Akashaditya Das, Guoxuan Xia, Guy-Bart Stan, Yiren Zhao:
Latent Diffusion Model for DNA Sequence Generation. CoRR abs/2310.06150 (2023) - 2022
- [c16]Robert Hönig, Yiren Zhao, Robert D. Mullins:
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning. ICML 2022: 8852-8866 - [c15]Yiren Zhao, Xitong Gao, Ilia Shumailov, Nicolò Fusi, Robert D. Mullins:
Rapid Model Architecture Adaption for Meta-Learning. NeurIPS 2022 - [i25]Duo Wang, Yiren Zhao, Ilia Shumailov, Robert D. Mullins:
Model Architecture Adaption for Bayesian Neural Networks. CoRR abs/2202.04392 (2022) - [i24]Mikel Bober-Irizar, Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Nicolas Papernot:
Architectural Backdoors in Neural Networks. CoRR abs/2206.07840 (2022) - [i23]Maximilian Kaufmann, Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Nicolas Papernot:
Efficient Adversarial Training With Data Pruning. CoRR abs/2207.00694 (2022) - [i22]Joseph Rance, Yiren Zhao, Ilia Shumailov, Robert D. Mullins:
Augmentation Backdoors. CoRR abs/2209.15139 (2022) - [i21]Tim Clifford
, Ilia Shumailov, Yiren Zhao, Ross J. Anderson, Robert D. Mullins:
ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks. CoRR abs/2210.00108 (2022) - [i20]Jason Ross Brown, Yiren Zhao, Ilia Shumailov, Robert D. Mullins:
Wide Attention Is The Way Forward For Transformers. CoRR abs/2210.00640 (2022) - [i19]Jason Ross Brown, Yiren Zhao, Ilia Shumailov, Robert D. Mullins:
DARTFormer: Finding The Best Type Of Attention. CoRR abs/2210.00641 (2022) - [i18]Yiren Zhao, Oluwatomisin Dada, Xitong Gao
, Robert D. Mullins:
Revisiting Structured Dropout. CoRR abs/2210.02570 (2022) - [i17]Tianrui Qin, Xianghuan He, Xitong Gao
, Yiren Zhao, Kejiang Ye, Cheng-Zhong Xu:
Flareon: Stealthy any2any Backdoor Injection via Poisoned Augmentation. CoRR abs/2212.09979 (2022) - 2021
- [c14]Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert D. Mullins, Ross Anderson:
Sponge Examples: Energy-Latency Attacks on Neural Networks. EuroS&P 2021: 212-231 - [c13]David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross J. Anderson:
Markpainting: Adversarial Machine Learning meets Inpainting. ICML 2021: 5409-5419 - [c12]Ilia Shumailov, Zakhar Shumaylov, Dmitry Kazhdan, Yiren Zhao, Nicolas Papernot, Murat A. Erdogdu, Ross J. Anderson:
Manipulating SGD with Data Ordering Attacks. NeurIPS 2021: 18021-18032 - [i16]Ilia Shumailov, Zakhar Shumaylov, Dmitry Kazhdan, Yiren Zhao, Nicolas Papernot, Murat A. Erdogdu, Ross J. Anderson:
Manipulating SGD with Data Ordering Attacks. CoRR abs/2104.09667 (2021) - [i15]David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross J. Anderson:
Markpainting: Adversarial Machine Learning meets Inpainting. CoRR abs/2106.00660 (2021) - [i14]Yiren Zhao, Xitong Gao, Ilia Shumailov, Nicolò Fusi, Robert D. Mullins:
Rapid Model Architecture Adaption for Meta-Learning. CoRR abs/2109.04925 (2021) - [i13]Robert Hönig, Yiren Zhao, Robert D. Mullins:
DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning. CoRR abs/2111.00465 (2021) - 2020
- [c11]Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Ross J. Anderson:
Towards Certifiable Adversarial Sample Detection. AISec@CCS 2020: 13-24 - [c10]Yiren Zhao, Ilia Shumailov, Han Cui
, Xitong Gao
, Robert D. Mullins, Ross J. Anderson:
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information. DSN Workshops 2020: 16-24 - [c9]Kafeng Wang, Xitong Gao, Yiren Zhao, Xingjian Li
, Dejing Dou, Cheng-Zhong Xu:
Pay Attention to Features, Transfer Learn Faster CNNs. ICLR 2020 - [i12]Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Ross J. Anderson:
Towards Certifiable Adversarial Sample Detection. CoRR abs/2002.08740 (2020) - [i11]Yiren Zhao, Duo Wang, Xitong Gao, Robert D. Mullins, Pietro Liò, Mateja Jamnik:
Probabilistic Dual Network Architecture Search on Graphs. CoRR abs/2003.09676 (2020) - [i10]Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert D. Mullins, Ross J. Anderson:
Sponge Examples: Energy-Latency Attacks on Neural Networks. CoRR abs/2006.03463 (2020) - [i9]Yiren Zhao, Duo Wang, Daniel Bates, Robert D. Mullins, Mateja Jamnik, Pietro Liò:
Learned Low Precision Graph Neural Networks. CoRR abs/2009.09232 (2020) - [i8]Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Ross J. Anderson:
Nudge Attacks on Point-Cloud DNNs. CoRR abs/2011.11637 (2020)
2010 – 2019
- 2019
- [c8]Yiren Zhao, Xitong Gao
, Xuan Guo, Junyi Liu, Erwei Wang, Robert D. Mullins, Peter Y. K. Cheung, George A. Constantinides, Cheng-Zhong Xu
:
Automatic Generation of Multi-Precision Multi-Arithmetic CNN Accelerators for FPGAs. FPT 2019: 45-53 - [c7]Xitong Gao, Yiren Zhao, Lukasz Dudziak, Robert D. Mullins, Cheng-Zhong Xu:
Dynamic Channel Pruning: Feature Boosting and Suppression. ICLR (Poster) 2019 - [c6]Milos Nikolic, Mostafa Mahmoud, Andreas Moshovos, Yiren Zhao, Robert D. Mullins:
Characterizing Sources of Ineffectual Computations in Deep Learning Networks. ISPASS 2019: 165-176 - [c5]Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Ross Anderson:
To Compress Or Not To Compress: Understanding The Interactions Between Adversarial Attacks And Neural Network Compression. SysML 2019 - [c4]Yiren Zhao, Xitong Gao, Daniel Bates, Robert D. Mullins, Cheng-Zhong Xu:
Focused Quantization for Sparse CNNs. NeurIPS 2019: 5585-5594 - [i7]Ilia Shumailov, Xitong Gao, Yiren Zhao, Robert D. Mullins, Ross Anderson, Cheng-Zhong Xu:
Sitatapatra: Blocking the Transfer of Adversarial Samples. CoRR abs/1901.08121 (2019) - [i6]Yiren Zhao, Xitong Gao, Daniel Bates
, Robert D. Mullins, Cheng-Zhong Xu:
Efficient and Effective Quantization for Sparse DNNs. CoRR abs/1903.03046 (2019) - [i5]Yiren Zhao, Ilia Shumailov, Han Cui, Xitong Gao, Robert D. Mullins, Ross J. Anderson:
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information. CoRR abs/1909.02918 (2019) - [i4]Yiren Zhao, Xitong Gao, Xuan Guo, Junyi Liu, Erwei Wang, Robert D. Mullins, Peter Y. K. Cheung, George A. Constantinides, Cheng-Zhong Xu:
Automatic Generation of Multi-precision Multi-arithmetic CNN Accelerators for FPGAs. CoRR abs/1910.10075 (2019) - 2018
- [c3]Jiang Su, Julian Faraone, Junyi Liu, Yiren Zhao, David B. Thomas
, Philip Heng Wai Leong
, Peter Y. K. Cheung:
Redundancy-Reduced MobileNet Acceleration on Reconfigurable Logic for ImageNet Classification. ARC 2018: 16-28 - [c2]Yiren Zhao, Xitong Gao
, Robert D. Mullins, Chengzhong Xu
:
Mayo: A Framework for Auto-generating Hardware Friendly Deep Neural Networks. EMDL@MobiSys 2018: 25-30 - [i3]Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Ross Anderson:
To compress or not to compress: Understanding the Interactions between Adversarial Attacks and Neural Network Compression. CoRR abs/1810.00208 (2018) - [i2]Xitong Gao, Yiren Zhao, Lukasz Dudziak, Robert D. Mullins, Cheng-Zhong Xu:
Dynamic Channel Pruning: Feature Boosting and Suppression. CoRR abs/1810.05331 (2018) - [i1]Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Ross Anderson:
The Taboo Trap: Behavioural Detection of Adversarial Samples. CoRR abs/1811.07375 (2018) - 2016
- [c1]Yiren Zhao, John Wickerson, George A. Constantinides:
An efficient implementation of online arithmetic. FPT 2016: 69-76
Coauthor Index
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last updated on 2024-08-23 19:26 CEST by the dblp team
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