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20232026
most citedEnhancing Domain Adaptation through Prompt Gradient Alignment

2 citations · 10 across the 25 of their papers we have counts for

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6 papers · 1 filter

cs.LG2023★ 1 cited

Class-Prototype Conditional Diffusion Model with Gradient Projection for Continual Learning

Khanh Doan, Quyen Tran, Tung Lam Tran +3

Mitigating catastrophic forgetting is a key hurdle in continual learning. Deep Generative Replay (GR) provides techniques focused on generating samples from prior tasks to enhance…

cs.LG2023★ 1 cited

KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All

Quyen Tran, Hoang Phan, Lam Tran +4

Drawing inspiration from prompt tuning techniques applied to Large Language Models, recent methods based on pre-trained ViT networks have achieved remarkable results in the field o…

cs.LG2023

Generalization Bounds for Robust Contrastive Learning: From Theory to Practice

Ngoc N. Tran, Lam Tran, Hoang Phan +5

Contrastive Learning first extracts features from unlabeled data, followed by linear probing with labeled data. Adversarial Contrastive Learning (ACL) integrates Adversarial Traini…

eess.IV2023

Cross-adversarial local distribution regularization for semi-supervised medical image segmentation

Thanh Nguyen-Duc, Trung Le, Roland Bammer +3

Medical semi-supervised segmentation is a technique where a model is trained to segment objects of interest in medical images with limited annotated data. Existing semi-supervised…

cs.CV2023

NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation

Minh-Tuan Tran, Trung Le, Xuan-May Le +3

Data-Free Knowledge Distillation (DFKD) has made significant recent strides by transferring knowledge from a teacher neural network to a student neural network without accessing th…

cs.LG2023

Sharpness-Aware Teleportation on Riemannian Manifolds

Tuan Truong, Hoang-Phi Nguyen, Haocheng Luo +4

Recent studies highlight the effectiveness of flat minima in enhancing generalization, with sharpness-aware minimization (SAM) achieving state-of-the-art performance. Additionally,…