Követés
Pin-Yu Chen
Pin-Yu Chen
Principal Research Scientist, IBM Research AI; MIT-IBM Watson AI Lab; RPI-IBM AIRC
E-mail megerősítve itt: ibm.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models
PY Chen*, H Zhang*, Y Sharma, J Yi, CJ Hsieh
ACM Workshop on AI and Security (*equal contribution, best paper award finalist), 2017
22772017
Efficient Neural Network Robustness Certification with General Activation Functions
H Zhang, TW Weng, PY Chen, CJ Hsieh, L Daniel
NeurIPS 2018, 2018
9292018
DBA: Distributed Backdoor Attacks against Federated Learning
C Xie, K Huang, PY Chen, B Li
ICLR 2020, 2019
8272019
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives
A Dhurandhar*, PY Chen*, R Luss, CC Tu, P Ting, K Shanmugam, P Das
NeurIPS 2018 (*equal contribution), 2018
7582018
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
PY Chen*, Y Sharma*, H Zhang, J Yi, CJ Hsieh
AAAI 2018 (*equal contribution), 2017
7182017
One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques
V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ...
arXiv preprint arXiv:1909.03012, 2019
6012019
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
TW Weng, H Zhang, PY Chen, J Yi, D Su, Y Gao, CJ Hsieh, L Daniel
ICLR 2018, 2018
5762018
Query-efficient hard-label black-box attack: An optimization-based approach
M Cheng, T Le, PY Chen, J Yi, H Zhang, CJ Hsieh
ICLR 2019, 2018
5012018
Is Robustness the Cost of Accuracy?--A Comprehensive Study on the Robustness of 18 Deep Image Classification Models
D Su, H Zhang, H Chen, J Yi, PY Chen, Y Gao
ECCV 2018, 2018
4772018
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective
K Xu, H Chen, S Liu, PY Chen, TW Weng, M Hong, X Lin
IJCAI 2019, 2019
4732019
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
CC Tu*, P Ting*, PY Chen*, S Liu, H Zhang, J Yi, CJ Hsieh, SM Cheng
AAAI 2019 (oral presentation, *equal contribution), 2018
4692018
Fine-tuning aligned language models compromises safety, even when users do not intend to!
X Qi, Y Zeng, T Xie, PY Chen, R Jia, P Mittal, P Henderson
ICLR 2024 (oral), 2023
4512023
Adversarial t-shirt! evading person detectors in a physical world
K Xu, G Zhang, S Liu, Q Fan, M Sun, H Chen, PY Chen, Y Wang, X Lin
ECCV 2020 (spotlight), 2019
4462019
Time-LLM: Time series forecasting by reprogramming large language models
M Jin, S Wang, L Ma, Z Chu, JY Zhang, X Shi, PY Chen, Y Liang, YF Li, ...
ICLR 2024, 2023
4342023
Variational Quantum Circuits for Deep Reinforcement Learning
S Yen-Chi Chen, CH Huck Yang, J Qi, PY Chen, X Ma, HS Goan
IEEE ACCESS, 2020
3982020
Vision transformers are robust learners
S Paul*, PY Chen*
AAAI 2022 (*equal contribution), 2021
3632021
Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
P Das, T Sercu, K Wadhawan, I Padhi, S Gehrmann, F Cipcigan, ...
Nature Biomedical Engineering 5 (6), 613-623, 2021
3402021
TrustLLM: Trustworthiness in Large Language Models
L Sun, Y Huang, H Wang, S Wu, Q Zhang, C Gao, Y Huang, W Lyu, ...
Technical Report, 2024
303*2024
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
M Cheng, S Singh, P Chen, PY Chen, S Liu, CJ Hsieh
ICLR 2020, 2019
2902019
Seq2sick: Evaluating the robustness of sequence-to-sequence models with adversarial examples
M Cheng, J Yi, PY Chen, H Zhang, CJ Hsieh
AAAI 2020, 2018
2692018
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Cikkek 1–20