Hung Bui | DeepAI

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Featured Co-authors

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∙ 11/27/2021

On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources

Domain adaptation (DA) benefits from the rigorous theoretical works that...

0 Trung Phung, et al. ∙

∙ 10/29/2021

Model Fusion of Heterogeneous Neural Networks via Cross-Layer Alignment

Layer-wise model fusion via optimal transport, named OTFusion, applies s...

11 Dang Nguyen, et al. ∙

∙ 06/14/2021

Temporal Predictive Coding For Model-Based Planning In Latent Space

High-dimensional observations are a major challenge in the application o...

0 Tung Nguyen, et al. ∙

∙ 02/16/2021

Improving Bayesian Inference in Deep Neural Networks with Variational Structured Dropout

Approximate inference in deep Bayesian networks exhibits a dilemma of ho...

44 Son Nguyen, et al. ∙

∙ 02/11/2021

BoMb-OT: On Batch of Mini-batches Optimal Transport

Mini-batch optimal transport (m-OT) has been successfully used in practi...

12 Khai Nguyen, et al. ∙

∙ 12/21/2020

Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior

Choosing a proper set of kernel functions is an important problem in lea...

0 Anh Tong, et al. ∙

∙ 10/05/2020

Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein

Relational regularized autoencoder (RAE) is a framework to learn the dis...

3 Khai Nguyen, et al. ∙

∙ 03/16/2020

Vec2Face: Unveil Human Faces from their Blackbox Features in Face Recognition

Unveiling face images of a subject given his/her high-level representati...

0 Chi Nhan Duong, et al. ∙

∙ 02/18/2020

Distributional Sliced-Wasserstein and Applications to Generative Modeling

Sliced-Wasserstein distance (SWD) and its variation, Max Sliced-Wasserst...

4 Khai Nguyen, et al. ∙

∙ 02/09/2020

On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm

We provide a computational complexity analysis for the Sinkhorn algorith...

0 Khiem Pham, et al. ∙

∙ 09/19/2019

On Efficient Multilevel Clustering via Wasserstein Distances

We propose a novel approach to the problem of multilevel clustering, whi...

0 Viet Huynh, et al. ∙

∙ 09/04/2019

Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control

Many real-world sequential decision-making problems can be formulated as...

25 Nir Levine, et al. ∙

∙ 09/21/2017

SpectralFPL: Online Spectral Learning for Single Topic Models

This paper studies how to efficiently learn an optimal latent variable m...

0 Tong Yu, et al. ∙

∙ 02/09/2016

Graphical Model Sketch

Structured high-cardinality data arises in many domains, and poses a maj...

0 Branislav Kveton, et al. ∙

∙ 08/06/2014

Boosted Markov Networks for Activity Recognition

We explore a framework called boosted Markov networks to combine the lea...

0 Truyen Tran, et al. ∙

∙ 08/06/2014

Human Activity Learning and Segmentation using Partially Hidden Discriminative Models

Learning and understanding the typical patterns in the daily activities ...

0 Truyen Tran, et al. ∙

∙ 09/26/2013

Automorphism Groups of Graphical Models and Lifted Variational Inference

Using the theory of group action, we first introduce the concept of the ...

0 Hung Bui, et al. ∙

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