[HTML][HTML] A survey on membership inference attacks and defenses in Machine Learning
Membership inference (MI) attacks mainly aim to infer whether a data record was used to
train a target model or not. Due to the serious privacy risks, MI attacks have been attracting a …
train a target model or not. Due to the serious privacy risks, MI attacks have been attracting a …
A Unified Membership Inference Method for Visual Self-supervised Encoder via Part-aware Capability
Self-supervised learning shows promise in harnessing extensive unlabeled data, but it also
confronts significant privacy concerns, especially in vision. In this paper, we aim to perform …
confronts significant privacy concerns, especially in vision. In this paper, we aim to perform …
Balancing Performance, Efficiency and Robustness in Open-World Machine Learning via Evolutionary Multi-objective Model Compression
When deploying machine learning models on resource-constrained hardware, reducing the
memory footprint required by the model without compromising its performance is critical …
memory footprint required by the model without compromising its performance is critical …
[PDF][PDF] EXPLORING COMPRESSION STRATEGIES FOR LARGE LANGUAGE MODELS TOWARDS EFFICIENT ARTIFICIAL INTELLIGENCE IMPLEMENTATIONS
DM Petroşanu, A Pîrjan - Journal of Information Systems & Operations …, 2024 - rau.ro
The rapid advancements of Artificial Intelligence (AI) technologies, particularly Large
Language Models (LLMs), have brought and accelerated significant innovations across …
Language Models (LLMs), have brought and accelerated significant innovations across …