Orthogonal Activation with Implicit Group-Aware Bias Learning for Class Imbalance
Fuente:
arXiv
Guardado en:
| Autores principales: | Kishanthan, Sukumar, Hevapathige, Asela |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Deep Learning Meets Oversampling: A Learning Framework to Handle Imbalanced Classification
por: Kishanthan, Sukumar, et al.
Publicado: (2025)
por: Kishanthan, Sukumar, et al.
Publicado: (2025)
AxelSMOTE: An Agent-Based Oversampling Algorithm for Imbalanced Classification
por: Kishanthan, Sukumar, et al.
Publicado: (2025)
por: Kishanthan, Sukumar, et al.
Publicado: (2025)
Large Language Models for Math Education in Low-Resource Languages: A Study in Sinhala and Tamil
por: Kishanthan, Sukumar, et al.
Publicado: (2026)
por: Kishanthan, Sukumar, et al.
Publicado: (2026)
Bridging Computational Social Science and Deep Learning: Cultural Dissemination-Inspired Graph Neural Networks
por: Hevapathige, Asela
Publicado: (2025)
por: Hevapathige, Asela
Publicado: (2025)
Permutation-Invariant Graph Partitioning:How Graph Neural Networks Capture Structural Interactions?
por: Hevapathige, Asela, et al.
Publicado: (2023)
por: Hevapathige, Asela, et al.
Publicado: (2023)
From Specification to Architecture: A Theory Compiler for Knowledge-Guided Machine Learning
por: Hevapathige, Asela, et al.
Publicado: (2026)
por: Hevapathige, Asela, et al.
Publicado: (2026)
Graph Neural Diffusion via Generalized Opinion Dynamics
por: Hevapathige, Asela, et al.
Publicado: (2025)
por: Hevapathige, Asela, et al.
Publicado: (2025)
Beyond Fixed Depth: Adaptive Graph Neural Networks for Node Classification Under Varying Homophily
por: Hevapathige, Asela, et al.
Publicado: (2025)
por: Hevapathige, Asela, et al.
Publicado: (2025)
Depth-Adaptive Graph Neural Networks via Learnable Bakry-'Emery Curvature
por: Hevapathige, Asela, et al.
Publicado: (2025)
por: Hevapathige, Asela, et al.
Publicado: (2025)
DeepSN: A Sheaf Neural Framework for Influence Maximization
por: Hevapathige, Asela, et al.
Publicado: (2024)
por: Hevapathige, Asela, et al.
Publicado: (2024)
Invariant-Stratified Propagation for Expressive Graph Neural Networks
por: Hevapathige, Asela, et al.
Publicado: (2026)
por: Hevapathige, Asela, et al.
Publicado: (2026)
Arch-VQ: Discrete Architecture Representation Learning with Autoregressive Priors
por: Poddenige, Deshani Geethika, et al.
Publicado: (2025)
por: Poddenige, Deshani Geethika, et al.
Publicado: (2025)
Mildly Overparameterized ReLU Networks on Orthogonal Data: Incremental Learning and Implicit Bias
por: Town, James, et al.
Publicado: (2026)
por: Town, James, et al.
Publicado: (2026)
Hyperbolic Aware Minimization: Implicit Bias for Sparsity
por: Jacobs, Tom, et al.
Publicado: (2025)
por: Jacobs, Tom, et al.
Publicado: (2025)
Class-Imbalanced Graph Learning without Class Rebalancing
por: Liu, Zhining, et al.
Publicado: (2023)
por: Liu, Zhining, et al.
Publicado: (2023)
Bias-Corrected Data Synthesis for Imbalanced Learning
por: Lyu, Pengfei, et al.
Publicado: (2025)
por: Lyu, Pengfei, et al.
Publicado: (2025)
An Analytical Model for Overparameterized Learning Under Class Imbalance
por: Mor, Eliav, et al.
Publicado: (2025)
por: Mor, Eliav, et al.
Publicado: (2025)
Boundary-Aware Adversarial Filtering for Reliable Diagnosis under Extreme Class Imbalance
por: Yu, Yanxuan, et al.
Publicado: (2025)
por: Yu, Yanxuan, et al.
Publicado: (2025)
Implementation of an Asymmetric Adjusted Activation Function for Class Imbalance Credit Scoring
por: Li, Xia, et al.
Publicado: (2025)
por: Li, Xia, et al.
Publicado: (2025)
Few-Shot Learning with Class Imbalance
por: Ochal, Mateusz, et al.
Publicado: (2021)
por: Ochal, Mateusz, et al.
Publicado: (2021)
A Theoretical Analysis of the Learning Dynamics under Class Imbalance
por: Francazi, Emanuele, et al.
Publicado: (2022)
por: Francazi, Emanuele, et al.
Publicado: (2022)
Class-Imbalanced Complementary-Label Learning via Weighted Loss
por: Wei, Meng, et al.
Publicado: (2022)
por: Wei, Meng, et al.
Publicado: (2022)
Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance
por: Kaushik, Chiraag, et al.
Publicado: (2024)
por: Kaushik, Chiraag, et al.
Publicado: (2024)
Mitigating Participation Imbalance Bias in Asynchronous Federated Learning
por: Chang, Xiangyu, et al.
Publicado: (2025)
por: Chang, Xiangyu, et al.
Publicado: (2025)
Group & Reweight: A Novel Cost-Sensitive Approach to Mitigating Class Imbalance in Network Traffic Classification
por: Du, Wumei, et al.
Publicado: (2024)
por: Du, Wumei, et al.
Publicado: (2024)
Harmonized Gradient Descent for Class Imbalanced Data Stream Online Learning
por: Zhou, Han, et al.
Publicado: (2025)
por: Zhou, Han, et al.
Publicado: (2025)
Beyond Synthetic Augmentation: Group-Aware Threshold Calibration for Robust Balanced Accuracy in Imbalanced Learning
por: Gittlin, Hunter
Publicado: (2025)
por: Gittlin, Hunter
Publicado: (2025)
Breaking the Prototype Bias Loop: Confidence-Aware Federated Contrastive Learning for Highly Imbalanced Clients
por: Wu, Tian-Shuang, et al.
Publicado: (2026)
por: Wu, Tian-Shuang, et al.
Publicado: (2026)
The Implicit Bias of Logit Regularization
por: Beck, Alon, et al.
Publicado: (2026)
por: Beck, Alon, et al.
Publicado: (2026)
Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection
por: Liu, Huafeng, et al.
Publicado: (2024)
por: Liu, Huafeng, et al.
Publicado: (2024)
DAMEL: Dual-Axis Multi-Expert Learning for Class-Imbalanced Learning
por: Lee, Hyuck, et al.
Publicado: (2026)
por: Lee, Hyuck, et al.
Publicado: (2026)
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
por: Vyas, Nikhil, et al.
Publicado: (2023)
por: Vyas, Nikhil, et al.
Publicado: (2023)
Fair Anomaly Detection For Imbalanced Groups
por: Wu, Ziwei, et al.
Publicado: (2024)
por: Wu, Ziwei, et al.
Publicado: (2024)
Temporal Imbalance of Positive and Negative Supervision in Class-Incremental Learning
por: Ma, Jinge, et al.
Publicado: (2026)
por: Ma, Jinge, et al.
Publicado: (2026)
Framework for Co-distillation Driven Federated Learning to Address Class Imbalance in Healthcare
por: Racha, Suraj, et al.
Publicado: (2024)
por: Racha, Suraj, et al.
Publicado: (2024)
Comparative Evaluation of Machine Learning Approaches for Minority-Class Financial Distress Prediction Under Class Imbalance Constraints
por: Sehgal, Karan, et al.
Publicado: (2026)
por: Sehgal, Karan, et al.
Publicado: (2026)
DCAST: Diverse Class-Aware Self-Training Mitigates Selection Bias for Fairer Learning
por: Tepeli, Yasin I., et al.
Publicado: (2024)
por: Tepeli, Yasin I., et al.
Publicado: (2024)
Optimal Implicit Bias in Linear Regression
por: Varma, Kanumuri Nithin, et al.
Publicado: (2025)
por: Varma, Kanumuri Nithin, et al.
Publicado: (2025)
The Implicit Bias of Adam on Separable Data
por: Zhang, Chenyang, et al.
Publicado: (2024)
por: Zhang, Chenyang, et al.
Publicado: (2024)
Quantum-Informed Contrastive Learning with Dynamic Mixup Augmentation for Class-Imbalanced Expert Systems
por: Jahin, Md Abrar, et al.
Publicado: (2025)
por: Jahin, Md Abrar, et al.
Publicado: (2025)
Ejemplares similares
-
Deep Learning Meets Oversampling: A Learning Framework to Handle Imbalanced Classification
por: Kishanthan, Sukumar, et al.
Publicado: (2025) -
AxelSMOTE: An Agent-Based Oversampling Algorithm for Imbalanced Classification
por: Kishanthan, Sukumar, et al.
Publicado: (2025) -
Large Language Models for Math Education in Low-Resource Languages: A Study in Sinhala and Tamil
por: Kishanthan, Sukumar, et al.
Publicado: (2026) -
Bridging Computational Social Science and Deep Learning: Cultural Dissemination-Inspired Graph Neural Networks
por: Hevapathige, Asela
Publicado: (2025) -
Permutation-Invariant Graph Partitioning:How Graph Neural Networks Capture Structural Interactions?
por: Hevapathige, Asela, et al.
Publicado: (2023)