Description
CPE is an effective collaborative metric learning to effectively address the problem of sparse and insufficient preference supervision from the margin distribution point-of-view.
Papers Using This Method
VulCPE: Context-Aware Cybersecurity Vulnerability Retrieval and Management2025-05-20CoE: Chain-of-Explanation via Automatic Visual Concept Circuit Description and Polysemanticity Quantification2025-03-19Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimation2025-03-14Weakly Supervised Semantic Segmentation via Progressive Confidence Region Expansion2025-01-01Enhancing 5G-NR mmWave : Phase Noise Models Evaluation with MMSE for CPE Compensation2024-12-08Temperature Optimization for Bayesian Deep Learning2024-10-08Conversational Prompt Engineering2024-08-08CPE-Identifier: Automated CPE identification and CVE summaries annotation with Deep Learning and NLP2024-05-22Human Mesh Recovery from Arbitrary Multi-view Images2024-03-19Three Heads Are Better Than One: Complementary Experts for Long-Tailed Semi-supervised Learning2023-12-25Addressing GAN Training Instabilities via Tunable Classification Losses2023-10-27If there is no underfitting, there is no Cold Posterior Effect2023-10-02FedEdge AI-TC: A Semi-supervised Traffic Classification Method based on Trusted Federated Deep Learning for Mobile Edge Computing2023-08-14A Fast Algorithm for the Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit2023-06-15Biomarker Discovery with Quantum Neural Networks: A Case-study in CTLA4-Activation Pathways2023-05-15In-Season Crop Progress in Unsurveyed Regions using Networks Trained on Synthetic Data2022-12-13$α$-GAN: Convergence and Estimation Guarantees2022-05-12A Fast Algorithm for PAC Combinatorial Pure Exploration2021-12-08Contrastive Proposal Extension with LSTM Network for Weakly Supervised Object Detection2021-10-14Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect2021-06-11