Imagen de Portada

ViRN: Variational Inference and Distribution Trilateration for Long-Tailed Continual Representation Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Dai, Hao, Tang, Chong, Chauhan, Jagmohan
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective
por: Dai, Hao, et al.
Publicado: (2025)

Parallax: Runtime Parallelization for Operator Fallbacks in Heterogeneous Edge Systems
por: Tang, Chong, et al.
Publicado: (2025)

Representation Norm Amplification for Out-of-Distribution Detection in Long-Tail Learning
por: Shin, Dong Geun, et al.
Publicado: (2024)

Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition
por: Zhou, Zi-Hao, et al.
Publicado: (2024)

Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
por: Hu, Chengming, et al.
Publicado: (2023)

CORAL: Disentangling Latent Representations in Long-Tailed Diffusion
por: Rodriguez, Esther, et al.
Publicado: (2025)

DELTA: Decoupling Long-Tailed Online Continual Learning
por: Raghavan, Siddeshwar, et al.
Publicado: (2024)

On The Relationship Between Continual Learning and Long-Tailed Recognition
por: Molahasani, Mahdiyar, et al.
Publicado: (2023)

Heterogeneous Learning Rate Scheduling for Neural Architecture Search on Long-Tailed Datasets
por: Tang, Chenxia
Publicado: (2024)

Decouple then Converge: Handling Unknown Unlabeled Distributions in Long-Tailed Semi-Supervised Learning
por: Gan, Kai, et al.
Publicado: (2024)

Stick-Breaking Mixture Normalizing Flows with Component-Wise Tail Adaptation for Variational Inference
por: Han, Seungsu, et al.
Publicado: (2025)

Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference
por: Nguyen, Dai Hai, et al.
Publicado: (2023)

Quality at the Tail of Machine Learning Inference
por: Yang, Zhengxin, et al.
Publicado: (2022)

Long-Tailed Out-of-Distribution Detection with Refined Separate Class Learning
por: Feng, Shuai, et al.
Publicado: (2025)

Nonstationary Reinforcement Learning with Linear Function Approximation
por: Zhou, Huozhi, et al.
Publicado: (2020)

Continual Learning of Numerous Tasks from Long-tail Distributions
por: Kang, Liwei, et al.
Publicado: (2024)

Variational Learning of Disentangled Representations
por: Slavutsky, Yuli, et al.
Publicado: (2025)

TAET: Two-Stage Adversarial Equalization Training on Long-Tailed Distributions
por: YuHang, Wang, et al.
Publicado: (2025)

Mitigating Long-Tailed Anomaly Score Distributions with Importance-Weighted Loss
por: Lee, Jungi, et al.
Publicado: (2026)

Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption
por: Chen, Yankai, et al.
Publicado: (2026)

Deconfounding Imitation Learning with Variational Inference
por: Vuorio, Risto, et al.
Publicado: (2022)

Learning with Importance Weighted Variational Inference
por: Daudel, Kamélia, et al.
Publicado: (2024)

Tail Distribution of Regret in Optimistic Reinforcement Learning
por: Khodadadian, Sajad, et al.
Publicado: (2025)

Time-Varying Graph Learning for Data with Heavy-Tailed Distribution
por: Javaheri, Amirhossein, et al.
Publicado: (2024)

REMIND: Rethinking Medical High-Modality Learning under Missingness--A Long-Tailed Distribution Perspective
por: Wu, Chenwei, et al.
Publicado: (2026)

Long-Tailed Recognition via Information-Preservable Two-Stage Learning
por: Lin, Fudong, et al.
Publicado: (2025)

Unsupervised Contrastive Learning Using Out-Of-Distribution Data for Long-Tailed Dataset
por: Hoang, Cuong Manh, et al.
Publicado: (2025)

Distribution-Aware Robust Learning from Long-Tailed Data with Noisy Labels
por: Baik, Jae Soon, et al.
Publicado: (2024)

Personalized Federated Learning on Heterogeneous and Long-Tailed Data via Expert Collaborative Learning
por: Lv, Fengling, et al.
Publicado: (2024)

High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
por: Gorbunov, Eduard, et al.
Publicado: (2023)

Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions
por: Xie, Tianyu, et al.
Publicado: (2024)

Variational Rectification Inference for Learning with Noisy Labels
por: Sun, Haoliang, et al.
Publicado: (2026)

Long-Tail Learning with Rebalanced Contrastive Loss
por: De Alvis, Charika, et al.
Publicado: (2023)

Generalizing Trilateration: Approximate Maximum Likelihood Estimator for Initial Orbit Determination in Low-Earth Orbit
por: Ferreira, Ricardo, et al.
Publicado: (2024)

Local Timescale Gates for Timescale-Robust Continual Spiking Neural Networks
por: Tiwari, Ansh, et al.
Publicado: (2025)

Stop Suppressing the Tail: Causal Inference for Extreme Events
por: Uehara, Eichi
Publicado: (2026)

PVBF: A Framework for Mitigating Parameter Variation Imbalance in Online Continual Learning
por: Tao, Zelin, et al.
Publicado: (2025)

Variational Bayes for Federated Continual Learning
por: Yao, Dezhong, et al.
Publicado: (2024)

TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge
por: Kwon, Young D., et al.
Publicado: (2023)

Efficient Mixture Learning in Black-Box Variational Inference
por: Hotti, Alexandra, et al.
Publicado: (2024)