Saved in:
| Main Author: | Xu, Yanhua |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.05222 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MC-NN: An End-to-End Multi-Channel Neural Network Approach for Predicting Influenza A Virus Hosts and Antigenic Types
by: Xu, Yanhua, et al.
Published: (2023)
by: Xu, Yanhua, et al.
Published: (2023)
Dive into Machine Learning Algorithms for Influenza Virus Host Prediction with Hemagglutinin Sequences
by: Xu, Yanhua, et al.
Published: (2022)
by: Xu, Yanhua, et al.
Published: (2022)
Semi-supervised Concept Bottleneck Models
by: Hu, Lijie, et al.
Published: (2024)
by: Hu, Lijie, et al.
Published: (2024)
Robust Semi-supervised Learning by Wisely Leveraging Open-set Data
by: Yang, Yang, et al.
Published: (2024)
by: Yang, Yang, et al.
Published: (2024)
Exploring Probabilistic Models for Semi-supervised Learning
by: Wang, Jianfeng
Published: (2024)
by: Wang, Jianfeng
Published: (2024)
Towards the Mitigation of Confirmation Bias in Semi-supervised Learning: a Debiased Training Perspective
by: Wang, Yu, et al.
Published: (2024)
by: Wang, Yu, et al.
Published: (2024)
SemiReward: A General Reward Model for Semi-supervised Learning
by: Li, Siyuan, et al.
Published: (2023)
by: Li, Siyuan, et al.
Published: (2023)
Semi-supervised Batch Learning From Logged Data
by: Aminian, Gholamali, et al.
Published: (2022)
by: Aminian, Gholamali, et al.
Published: (2022)
Feature Space Renormalization for Semi-supervised Learning
by: Sun, Jun, et al.
Published: (2023)
by: Sun, Jun, et al.
Published: (2023)
Probability-density-aware Semi-supervised Learning
by: Liu, Shuyang, et al.
Published: (2024)
by: Liu, Shuyang, et al.
Published: (2024)
Incremental Self-training for Semi-supervised Learning
by: Guo, Jifeng, et al.
Published: (2024)
by: Guo, Jifeng, et al.
Published: (2024)
Semi-supervised Regression Analysis with Model Misspecification and High-dimensional Data
by: Tian, Ye, et al.
Published: (2024)
by: Tian, Ye, et al.
Published: (2024)
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators
by: Bai, Sikai, et al.
Published: (2023)
by: Bai, Sikai, et al.
Published: (2023)
Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data
by: Roy, Shuvendu, et al.
Published: (2023)
by: Roy, Shuvendu, et al.
Published: (2023)
Semi-supervised Instruction Tuning for Large Language Models on Text-Attributed Graphs
by: Song, Zixing, et al.
Published: (2026)
by: Song, Zixing, et al.
Published: (2026)
Semi-supervised Clustering Through Representation Learning of Large-scale EHR Data
by: Wang, Linshanshan, et al.
Published: (2025)
by: Wang, Linshanshan, et al.
Published: (2025)
Semantic Graph Neural Network with Multi-measure Learning for Semi-supervised Classification
by: Lin, Junchao, et al.
Published: (2022)
by: Lin, Junchao, et al.
Published: (2022)
A Semi-supervised CART Model for Covariate Shift
by: Cai, Mingyang, et al.
Published: (2024)
by: Cai, Mingyang, et al.
Published: (2024)
Semi-supervised Domain Adaptation in Graph Transfer Learning
by: Qiao, Ziyue, et al.
Published: (2023)
by: Qiao, Ziyue, et al.
Published: (2023)
A Unified Framework for Heterogeneous Semi-supervised Learning
by: Heidari, Marzi, et al.
Published: (2025)
by: Heidari, Marzi, et al.
Published: (2025)
Meta-Semi: A Meta-learning Approach for Semi-supervised Learning
by: Wang, Yulin, et al.
Published: (2020)
by: Wang, Yulin, et al.
Published: (2020)
Adversarial Graph Fusion for Incomplete Multi-view Semi-supervised Learning with Tensorial Imputation
by: Jiang, Zhangqi, et al.
Published: (2025)
by: Jiang, Zhangqi, et al.
Published: (2025)
Conformalized Semi-supervised Random Forest for Classification and Abnormality Detection
by: Han, Yujin, et al.
Published: (2023)
by: Han, Yujin, et al.
Published: (2023)
Semantic Consistency Regularization with Large Language Models for Semi-supervised Sentiment Analysis
by: Li, Kunrong, et al.
Published: (2025)
by: Li, Kunrong, et al.
Published: (2025)
Inference-Time Toxicity Mitigation in Protein Language Models
by: Burda, Manuel Fernández, et al.
Published: (2026)
by: Burda, Manuel Fernández, et al.
Published: (2026)
Joint-stochastic-approximation Autoencoders with Application to Semi-supervised Learning
by: He, Wenbo, et al.
Published: (2025)
by: He, Wenbo, et al.
Published: (2025)
Semi-supervised Contrastive Learning Using Partial Label Information
by: Hansen, Colin B., et al.
Published: (2020)
by: Hansen, Colin B., et al.
Published: (2020)
Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins
by: Dreyer, Frédéric A., et al.
Published: (2025)
by: Dreyer, Frédéric A., et al.
Published: (2025)
Enhancing Semi-supervised Learning with Zero-shot Pseudolabels
by: Chung, Jichan, et al.
Published: (2025)
by: Chung, Jichan, et al.
Published: (2025)
Graph Neural Diffusion Networks for Semi-supervised Learning
by: Ye, Wei, et al.
Published: (2022)
by: Ye, Wei, et al.
Published: (2022)
A Semi-supervised Generative Model for Incomplete Multi-view Data Integration with Missing Labels
by: Shen, Yiyang, et al.
Published: (2025)
by: Shen, Yiyang, et al.
Published: (2025)
Semi-supervised Fréchet Regression
by: Qiu, Rui, et al.
Published: (2024)
by: Qiu, Rui, et al.
Published: (2024)
Activity Recognition from Smart Insole Sensor Data Using a Circular Dilated CNN
by: Zhao, Yanhua
Published: (2026)
by: Zhao, Yanhua
Published: (2026)
Joint-stochastic-approximation Random Fields with Application to Semi-supervised Learning
by: Song, Yunfu, et al.
Published: (2025)
by: Song, Yunfu, et al.
Published: (2025)
CaliMatch: Adaptive Calibration for Improving Safe Semi-supervised Learning
by: Bae, Jinsoo, et al.
Published: (2025)
by: Bae, Jinsoo, et al.
Published: (2025)
Semi-supervised Graph Anomaly Detection via Robust Homophily Learning
by: Ai, Guoguo, et al.
Published: (2025)
by: Ai, Guoguo, et al.
Published: (2025)
Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax Entropy
by: Xiao, Jiaren, et al.
Published: (2023)
by: Xiao, Jiaren, et al.
Published: (2023)
Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization
by: Persiianov, Mikhail, et al.
Published: (2024)
by: Persiianov, Mikhail, et al.
Published: (2024)
Shaping Sparse Rewards in Reinforcement Learning: A Semi-supervised Approach
by: Li, Wenyun, et al.
Published: (2025)
by: Li, Wenyun, et al.
Published: (2025)
Graph Concept Bottleneck Models
by: Xu, Haotian, et al.
Published: (2025)
by: Xu, Haotian, et al.
Published: (2025)
Similar Items
-
MC-NN: An End-to-End Multi-Channel Neural Network Approach for Predicting Influenza A Virus Hosts and Antigenic Types
by: Xu, Yanhua, et al.
Published: (2023) -
Dive into Machine Learning Algorithms for Influenza Virus Host Prediction with Hemagglutinin Sequences
by: Xu, Yanhua, et al.
Published: (2022) -
Semi-supervised Concept Bottleneck Models
by: Hu, Lijie, et al.
Published: (2024) -
Robust Semi-supervised Learning by Wisely Leveraging Open-set Data
by: Yang, Yang, et al.
Published: (2024) -
Exploring Probabilistic Models for Semi-supervised Learning
by: Wang, Jianfeng
Published: (2024)