Performance Analysis
Trap-MID: Trapdoor-based Defense against Model Inversion Attacks
While existing defenses often rely on regularization techniques to reduce information leakage, they remain vulnerable to recent attacks.
Hyper-opinion Evidential Deep Learning for Out-of-Distribution Detection
Evidential Deep Learning (EDL), grounded in Evidence Theory and Subjective Logic (SL), provides a robust framework to estimate uncertainty for out-of-distribution (OOD) detection alongside traditional classification probabilities.
Dissect Black Box: Interpreting for Rule-Based Explanations in Unsupervised Anomaly Detection Yu Zhang, Ruoyu Li, Nengwu Wu, Qing Li, Xinhan Lin, Y ang Hu, Tao Li, Yong Jiang
Delineation (GBD) algorithm is employed to define boundaries within each segmented distribution, effectively delineating normal from anomalous data points.
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models
In this paper, we introduce a new type of model backdoor: the privacy backdoor attack .
Conjugated Semantic Pool Improves OOD Detection with Pre-trained Vision-Language Models
Observing that the original semantic pool is comprised of unmodified specific class names, we correspondingly construct a conjugated semantic pool (CSP) consisting of modified superclass names, each serving as a cluster center for samples sharing similar properties across different categories.
realSEUDO for real-time calcium imaging analysis
One challenging modality for real-time processing is multi-photon calcium imaging (CI).
Differentially Private Set Representations
The authors are listed in alphabetical order.
