Results 91 to 100 of about 5,739,313 (302)

FAMF: Robust Feature-Level Adversarial Attack on Metric-Based Few-Shot Learning Models

IEEE Access
Few-shot learning has emerged as the primary approach for tasks with extremely limited training data. In particular, metric-based few-shot learning has been highlighted for enabling effective generalization to new tasks by comparing feature similarity ...
Gwang-Nam Kim, Han-Ju Lee, In-Woong Jeong, Jin-Myeong Shin, Seok-Hwan Choi   +4 more
doaj   +1 more source

RLXSS: Optimizing XSS Detection Model to Defend Against Adversarial Attacks Based on Reinforcement Learning

Future Internet, 2019
With the development of artificial intelligence, machine learning algorithms and deep learning algorithms are widely applied to attack detection models. Adversarial attacks against artificial intelligence models become inevitable problems when there is a
Yong Fang, Cheng Huang, Yijia Xu, Yang Li   +3 more
doaj   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Adversarial sample generation algorithm for vertical federated learning

Tongxin xuebao, 2023
To adapt to the scenario characteristics of vertical federated learning (VFL) applications regarding high communication cost, fast model iteration, and decentralized data storage, a generalized adversarial sample generation algorithm named VFL-GASG was ...
Xiaolin CHEN, Daoguang ZAN, Bingchao WU, Bei GUAN, Yongji WANG   +4 more
doaj   +2 more sources

Breaking Machine Learning Models with Adversarial Attacks and its Variants

Proceedings of the International Florida Artificial Intelligence Research Society Conference
Machine learning models can be by adversarial attacks, subtle, imperceptible perturbations to inputs that cause the model to produce erroneous outputs.
Pavan Reddy
doaj   +1 more source

Scalable Adversarial Online Continual Learning

, 2023
has been accepted for publication at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2022 (ECML PKDD 2022)
Dam, Tanmoy, Pratama, Mahardhika, Ferdaus, MD Meftahul, Anavatti, Sreenatha, Abbas, Hussein   +4 more
openaire   +3 more sources

Engineering Immune Cell to Counteract Aging and Aging‐Associated Diseases

Advanced Science, EarlyView.
This review highlights a paradigm shift in which advanced immune cell therapies, initially developed for cancer, are now being harnessed to combat aging. By engineering immune cells to selectively clear senescent cells and remodel pro‐inflammatory tissue microenvironments, these strategies offer a novel and powerful approach to delay age‐related ...
Jianhua Guo, Lanjie Lei, Ying Jin, Lan Su, Shumao Cui, Liyun Shi   +5 more
wiley   +1 more source

Cycles in Adversarial Regularized Learning [PDF]

, 2018
22 pages, 4 ...
Mertikopoulos, Panayotis, Papadimitriou, Christos Harilaos, Piliouras, Georgios   +2 more
openaire   +3 more sources

Urea‐Formaldehyde Resin Confined Silicon Nanodots Composites: High‐Performance and Ultralong Persistent Luminescence for Dynamic AI Information Encryption

Advanced Science, EarlyView.
Schematic illustration of SiNDs composite materials synthesis and its internal photophysical process mechanism. And an AI‐assisted dynamic information encryption process. ABSTRACT Persistent luminescence materials typically encounter an intrinsic trade‐off between high phosphorescence quantum yield (PhQY) and ultralong phosphorescence lifetime.
Yulu Liu, Lei Cao, Lele Gao, Panyong Wang, Qiannan You, Xinpei Pang, Li Li, Mingzheng Jia, Wen‐Fei Dong, Minghui Zan   +9 more
wiley   +1 more source

Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare

Advanced Science, EarlyView.
Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu, Haolin Fan, Minwoo Kim, Tong Zhou, Pinyi Yang, Lingdi Zhao, Yiran Wang, Ziyuan Che, Chia‐Wei Liu, Bingbing Li, Yangzhi Zhu   +10 more
wiley   +1 more source