Výsledky vyhledávání - "Lee, Byung Hyun"

Report

Doubly Perturbed Task Free Continual Learning

Autor: Lee, Byung Hyun, Oh, Min-hwan, Chun, Se Young

Task Free online continual learning (TF-CL) is a challenging problem where the model incrementally learns tasks without explicit task information. Although training with entire data from the past, present as well as future is considered as the gold s

Externí odkaz: http://arxiv.org/abs/2312.13027

Zobrazit plný text záznamu

Report

Online Continual Learning on Hierarchical Label Expansion

Autor: Lee, Byung Hyun, Jung, Okchul, Choi, Jonghyun, Chun, Se Young

Continual learning (CL) enables models to adapt to new tasks and environments without forgetting previously learned knowledge. While current CL setups have ignored the relationship between labels in the past task and the new task with or without smal

Externí odkaz: http://arxiv.org/abs/2308.14374

Zobrazit plný text záznamu

Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Report

Empirically Accelerating Scaled Gradient Projection Using Deep Neural Network For Inverse Problems In Image Processing

Autor: Lee, Byung Hyun, Chun, Se Young

Recently, deep neural networks (DNNs) have shown advantages in accelerating optimization algorithms. One approach is to unfold finite number of iterations of conventional optimization algorithms and to learn parameters in the algorithms. However, the

Externí odkaz: http://arxiv.org/abs/1902.02449

Zobrazit plný text záznamu