Learning from N-Tuple Data with M Positive Instances: Unbiased Risk Estimation and Theoretical Guarantees
Fuente:
arXiv
Guardado en:
| Autores principales: | Zhang, Miao, Li, Junpeng, HUa, ChangChun, Yang, Yana |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Cost-Sensitive Unbiased Risk Estimation for Multi-Class Positive-Unlabeled Learning
por: Zhang, Miao, et al.
Publicado: (2025)
por: Zhang, Miao, et al.
Publicado: (2025)
Learning from M-Tuple Dominant Positive and Unlabeled Data
por: Qin, Jiahe, et al.
Publicado: (2025)
por: Qin, Jiahe, et al.
Publicado: (2025)
A Unified and Stable Risk Minimization Framework for Weakly Supervised Learning with Theoretical Guarantees
por: Zhang, Miao, et al.
Publicado: (2025)
por: Zhang, Miao, et al.
Publicado: (2025)
A Unified Empirical Risk Minimization Framework for Flexible N-Tuples Weak Supervision
por: Huang, Shuying, et al.
Publicado: (2025)
por: Huang, Shuying, et al.
Publicado: (2025)
An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes
por: Hu, Jiayu, et al.
Publicado: (2024)
por: Hu, Jiayu, et al.
Publicado: (2024)
Minimum Variance Unbiased N:M Sparsity for the Neural Gradients
por: Chmiel, Brian, et al.
Publicado: (2022)
por: Chmiel, Brian, et al.
Publicado: (2022)
Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guarantee
por: Gao, Mengtong, et al.
Publicado: (2024)
por: Gao, Mengtong, et al.
Publicado: (2024)
Active Level Set Estimation for Continuous Search Space with Theoretical Guarantee
por: Ngo, Giang, et al.
Publicado: (2024)
por: Ngo, Giang, et al.
Publicado: (2024)
Revisiting Meta-Learning with Noisy Labels: Reweighting Dynamics and Theoretical Guarantees
por: Zhang, Yiming, et al.
Publicado: (2025)
por: Zhang, Yiming, et al.
Publicado: (2025)
Theoretical Analysis of Meta Reinforcement Learning: Generalization Bounds and Convergence Guarantees
por: Wang, Cangqing, et al.
Publicado: (2024)
por: Wang, Cangqing, et al.
Publicado: (2024)
Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation
por: Akujuobi, Uchenna, et al.
Publicado: (2020)
por: Akujuobi, Uchenna, et al.
Publicado: (2020)
PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation
por: Gella, Blake, et al.
Publicado: (2026)
por: Gella, Blake, et al.
Publicado: (2026)
Learning Unbiased Cluster Descriptors for Interpretable Imbalanced Concept Drift Detection
por: Zhang, Yiqun, et al.
Publicado: (2026)
por: Zhang, Yiqun, et al.
Publicado: (2026)
Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees
por: Kim, Dohyeong, et al.
Publicado: (2024)
por: Kim, Dohyeong, et al.
Publicado: (2024)
Frailty Estimation in Elderly Oncology Patients Using Multimodal Wearable Data and Multi-Instance Learning
por: Kyprakis, Ioannis, et al.
Publicado: (2026)
por: Kyprakis, Ioannis, et al.
Publicado: (2026)
Graph Structure Learning with Privacy Guarantees for Open Graph Data
por: Guo, Muhao, et al.
Publicado: (2025)
por: Guo, Muhao, et al.
Publicado: (2025)
Efficient Quantization of Mixture-of-Experts with Theoretical Generalization Guarantees
por: Chowdhury, Mohammed Nowaz Rabbani, et al.
Publicado: (2026)
por: Chowdhury, Mohammed Nowaz Rabbani, et al.
Publicado: (2026)
GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification
por: Gan, Wangjie, et al.
Publicado: (2026)
por: Gan, Wangjie, et al.
Publicado: (2026)
Learning Unbiased Permutations via Flow Matching
por: Min, Yimeng, et al.
Publicado: (2026)
por: Min, Yimeng, et al.
Publicado: (2026)
ProtoGCD: Unified and Unbiased Prototype Learning for Generalized Category Discovery
por: Ma, Shijie, et al.
Publicado: (2025)
por: Ma, Shijie, et al.
Publicado: (2025)
Live or Lie: Action-Aware Capsule Multiple Instance Learning for Risk Assessment in Live Streaming Platforms
por: Qiao, Yiran, et al.
Publicado: (2026)
por: Qiao, Yiran, et al.
Publicado: (2026)
Optimizing Feature Selection in Causal Inference: A Three-Stage Computational Framework for Unbiased Estimation
por: Yang, Tianyu, et al.
Publicado: (2025)
por: Yang, Tianyu, et al.
Publicado: (2025)
Unbiased Gradient Low-Rank Projection
por: Pan, Rui, et al.
Publicado: (2025)
por: Pan, Rui, et al.
Publicado: (2025)
DSAI: Unbiased and Interpretable Latent Feature Extraction for Data-Centric AI
por: Cho, Hyowon, et al.
Publicado: (2024)
por: Cho, Hyowon, et al.
Publicado: (2024)
Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees
por: Tao, Lue, et al.
Publicado: (2023)
por: Tao, Lue, et al.
Publicado: (2023)
Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion
por: Alchihabi, Abdullah, et al.
Publicado: (2024)
por: Alchihabi, Abdullah, et al.
Publicado: (2024)
Unbiased Online Curvature Approximation for Regularized Graph Continual Learning
por: Yin, Jie, et al.
Publicado: (2025)
por: Yin, Jie, et al.
Publicado: (2025)
Unbiased Dynamic Pruning for Efficient Group-Based Policy Optimization
por: Zhu, Haodong, et al.
Publicado: (2026)
por: Zhu, Haodong, et al.
Publicado: (2026)
On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
por: Ma, Shaocong, et al.
Publicado: (2025)
por: Ma, Shaocong, et al.
Publicado: (2025)
Tail-Risk-Safe Monte Carlo Tree Search under PAC-Level Guarantees
por: Zhang, Zuyuan, et al.
Publicado: (2025)
por: Zhang, Zuyuan, et al.
Publicado: (2025)
RegimeNAS: Regime-Aware Differentiable Architecture Search With Theoretical Guarantees for Financial Trading
por: Devadiga, Prathamesh, et al.
Publicado: (2025)
por: Devadiga, Prathamesh, et al.
Publicado: (2025)
Robust Heterogeneous Analog-Digital Computing for Mixture-of-Experts Models with Theoretical Generalization Guarantees
por: Chowdhury, Mohammed Nowaz Rabbani, et al.
Publicado: (2026)
por: Chowdhury, Mohammed Nowaz Rabbani, et al.
Publicado: (2026)
Debiasing Reward Models by Representation Learning with Guarantees
por: Ng, Ignavier, et al.
Publicado: (2025)
por: Ng, Ignavier, et al.
Publicado: (2025)
Stress Estimation in Elderly Oncology Patients Using Visual Wearable Representations and Multi-Instance Learning
por: Kyprakis, Ioannis, et al.
Publicado: (2026)
por: Kyprakis, Ioannis, et al.
Publicado: (2026)
Class Unbiasing for Generalization in Medical Diagnosis
por: Zuo, Lishi, et al.
Publicado: (2025)
por: Zuo, Lishi, et al.
Publicado: (2025)
MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization
por: Do, Nguyen, et al.
Publicado: (2024)
por: Do, Nguyen, et al.
Publicado: (2024)
Investigating the Privacy Risk of Using Robot Vacuum Cleaners in Smart Environments
por: Ulsmaag, Benjamin, et al.
Publicado: (2024)
por: Ulsmaag, Benjamin, et al.
Publicado: (2024)
Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training
por: Wang, Kevin, et al.
Publicado: (2026)
por: Wang, Kevin, et al.
Publicado: (2026)
FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation
por: Peng, Zihao, et al.
Publicado: (2025)
por: Peng, Zihao, et al.
Publicado: (2025)
From Reward Shaping to Q-Shaping: Achieving Unbiased Learning with LLM-Guided Knowledge
por: Wu, Xiefeng
Publicado: (2024)
por: Wu, Xiefeng
Publicado: (2024)
Ejemplares similares
-
Cost-Sensitive Unbiased Risk Estimation for Multi-Class Positive-Unlabeled Learning
por: Zhang, Miao, et al.
Publicado: (2025) -
Learning from M-Tuple Dominant Positive and Unlabeled Data
por: Qin, Jiahe, et al.
Publicado: (2025) -
A Unified and Stable Risk Minimization Framework for Weakly Supervised Learning with Theoretical Guarantees
por: Zhang, Miao, et al.
Publicado: (2025) -
A Unified Empirical Risk Minimization Framework for Flexible N-Tuples Weak Supervision
por: Huang, Shuying, et al.
Publicado: (2025) -
An Unbiased Risk Estimator for Partial Label Learning with Augmented Classes
por: Hu, Jiayu, et al.
Publicado: (2024)