Search Results for author: Cuong V. Nguyen

Found 14 papers, 4 papers with code

Generalization Bounds for Deep Transfer Learning Using Majority Predictor Accuracy

no code implementations13 Sep 2022 Cuong N. Nguyen, Lam Si Tung Ho, Vu Dinh, Tal Hassner, Cuong V. Nguyen

We analyze new generalization bounds for deep learning models trained by transfer learning from a source to a target task.

Generalization Bounds Transfer Learning

An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator

1 code implementation21 Oct 2021 Cuong V. Nguyen, Tien-Dung Cao, Tram Truong-Huu, Khanh N. Pham, Binh T. Nguyen

In this paper, we perform an empirical study on the impact of several loss functions on the performance of standard GAN models, Deep Convolutional Generative Adversarial Networks (DCGANs).

Transferability and Hardness of Supervised Classification Tasks

no code implementations ICCV 2019 Anh T. Tran, Cuong V. Nguyen, Tal Hassner

As a case study, we transfer a learned face recognition model to CelebA attribute classification tasks, showing state of the art accuracy for tasks estimated to be highly transferable.

Classification Face Recognition +1

Toward Understanding Catastrophic Forgetting in Continual Learning

no code implementations2 Aug 2019 Cuong V. Nguyen, Alessandro Achille, Michael Lam, Tal Hassner, Vijay Mahadevan, Stefano Soatto

As an application, we apply our procedure to study two properties of a task sequence: (1) total complexity and (2) sequential heterogeneity.

Continual Learning

Bayesian Active Learning With Abstention Feedbacks

no code implementations4 Jun 2019 Cuong V. Nguyen, Lam Si Tung Ho, Huan Xu, Vu Dinh, Binh Nguyen

We study pool-based active learning with abstention feedbacks where a labeler can abstain from labeling a queried example with some unknown abstention rate.

Active Learning General Classification

Variational Continual Learning

6 code implementations ICLR 2018 Cuong V. Nguyen, Yingzhen Li, Thang D. Bui, Richard E. Turner

This paper develops variational continual learning (VCL), a simple but general framework for continual learning that fuses online variational inference (VI) and recent advances in Monte Carlo VI for neural networks.

Continual Learning Variational Inference

Bayesian Pool-based Active Learning With Abstention Feedbacks

no code implementations23 May 2017 Cuong V. Nguyen, Lam Si Tung Ho, Huan Xu, Vu Dinh, Binh Nguyen

We study pool-based active learning with abstention feedbacks, where a labeler can abstain from labeling a queried example with some unknown abstention rate.

Active Learning General Classification

Streaming Sparse Gaussian Process Approximations

2 code implementations NeurIPS 2017 Thang D. Bui, Cuong V. Nguyen, Richard E. Turner

Sparse pseudo-point approximations for Gaussian process (GP) models provide a suite of methods that support deployment of GPs in the large data regime and enable analytic intractabilities to be sidestepped.

Accelerated Randomized Mirror Descent Algorithms For Composite Non-strongly Convex Optimization

no code implementations23 May 2016 Le Thi Khanh Hien, Cuong V. Nguyen, Huan Xu, Can-Yi Lu, Jiashi Feng

Avoiding this devise, we propose an accelerated randomized mirror descent method for solving this problem without the strongly convex assumption.

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