Trung Le

发表

Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering pdf

Quan Hung Tran, Quan Tran, Nhan Dam, 2020, COLING.

An optimal sphere and two large margins approach for novelty detection

Trung Le, Wanli Ma, Dat Tran, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Graph-based semi-supervised Support Vector Data Description for novelty detection

Trung Le, Wanli Ma, Dat Tran, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Sparse Adaptive Multi-hyperplane Machine

Trung Le, Dinh Q. Phung, Khanh Nguyen, 2016, PAKDD.

Robust Anomaly Detection in Videos Using Multilevel Representations

Wei Luo, Trung Le, Dinh Q. Phung, 2019, AAAI.

A Novel Parameter Refinement Approach to One Class Support Vector Machine

Trung Le, Wanli Ma, Dat Tran, 2011, ICONIP.

Using EEG artifacts for BCI applications

Trung Le, Wanli Ma, Dat Tran, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Mixture of hyperspheres for novelty detection

Trung Le, Khanh Nguyen, Duy Nguyen, 2016, Vietnam Journal of Computer Science.

A new fuzzy membership computation method for fuzzy support vector machines

Trung Le, Wanli Ma, Dharmendra Sharma, 2010, International Conference on Communications and Electronics 2010.

Fuzzy support vector machines for age and gender classification

Trung Le, Dat Tran, Xu Huang, 2010, INTERSPEECH.

Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images pdf

Trung Le, Dinh Phung, Tamas Abraham, 2020, ArXiv.

Geometric Enclosing Networks

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, IJCAI.

GoGP: Fast Online Regression with Gaussian Processes

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

Code Pointer Network for Binary Function Scope Identification

Trung Le, Dinh Phung, Khanh Nguyen, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Approximation Vector Machines for Large-scale Online Learning

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, J. Mach. Learn. Res..

Robust Support Vector Machine

Trung Le, Wanli Ma, Dat Tran, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection

Tuan Nguyen, Trung Le, Lizhen Qu, 2019, ICLR.

Multiple Distribution Data Description Learning Algorithm for Novelty Detection

Trung Le, Wanli Ma, Dat Tran, 2011, PAKDD.

MGAN: Training Generative Adversarial Nets with Multiple Generators

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2018, ICLR.

Maximal margin learning vector quantisation

Trung Le, Wanli Ma, Dat Tran, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

A Generic Framework for Soft Subspace Pattern Recognition

Trung Le, Wanli Ma, Dharmendra Sharma, 2009 .

Nonparametric Budgeted Stochastic Gradient Descent

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, AISTATS.

Improving Adversarial Robustness by Enforcing Local and Global Compactness

Trung Le, Dinh Q. Phung, Tamas Abraham, 2020, ECCV.

Distributed data augmented support vector machine on Spark

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Budgeted Semi-supervised Support Vector Machine

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, UAI.

Enhancing Performance of SVM-Based Brain-Computer Interface Systems

Trung Le, Dat Tran, Dharmendra Sharma, 2010, Aust. J. Intell. Inf. Process. Syst..

Deep Cost-Sensitive Kernel Machine for Binary Software Vulnerability Detection

Trung Le, John C. Grundy, Khanh Nguyen, 2020, PAKDD.

Scheduling workloads in a network of datacentres to reduce electricity cost and carbon footprint

David Wright, Trung Le, 2015, Sustain. Comput. Informatics Syst..

Deterministic Annealing Multi-Sphere Support Vector Data Description

Trung Le, Wanli Ma, Dat Tran, 2012, ICONIP.

EEG-Based Person Verification Using Multi-Sphere SVDD and UBM

Trung Le, Wanli Ma, Dat Tran, 2013, PAKDD.

Multiple Kernel Learning with Data Augmentation

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, ACML.

Neural Topic Model via Optimal Transport

Trung Le, Dinh Phung, He Zhao, 2020, ICLR.

Least square Support Vector Machine for large-scale dataset

Trung Le, Wanli Ma, Dat Tran, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

CDAO-Store: Ontology-driven Data Integration for

Trung Le, Enrico Pontelli, Tran Cao Son, 2011 .

Large-scale Online Kernel Learning with Random Feature Reparameterization

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, IJCAI.

CDAO-Store: Ontology-driven Data Integration for Phylogenetic Analysis

Trung Le, Enrico Pontelli, Tran Cao Son, 2011, BMC Bioinformatics.

A Theoretical Framework for Multi-sphere Support Vector Data Description

Trung Le, Wanli Ma, Dat Tran, 2010, ICONIP.

Stein Variational Gradient Descent with Variance Reduction

Nhan Dam, Trung Le, Dinh Phung, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

When Can Neural Networks Learn Connected Decision Regions? pdf

Trung Le, Dinh Q. Phung, Trung Le, 2019, ArXiv.

Fuzzy Semi-supervised Large Margin One-Class Support Vector Machine

Trung Le, Mi Dinh, Van Hien Nguyen, 2015 .

Clustering Induced Kernel Learning

Nhan Dam, Trung Le, Tu Dinh Nguyen, 2018, ACML.

Fuzzy Kernel Stochastic Gradient Descent machines

Trung Le, Wanli Ma, Dat Tran, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

A unified model for support vector machine and support vector data description

Trung Le, Wanli Ma, Dat Tran, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Theoretical Perspective of Deep Domain Adaptation pdf

Trung Le, Dinh Q. Phung, Khanh Nguyen, 2018, ArXiv.

A new support vector machine method for medical image classification

Trung Le, Wanli Ma, Dat Tran, 2010, 2010 2nd European Workshop on Visual Information Processing (EUVIP).

Code Action Network for Binary Function Scope Identification

Trung Le, Van Nguyen, John C. Grundy, 2020, PAKDD.

Parameterized Rate-Distortion Stochastic Encoder

Trung Le, Dinh Q. Phung, Dinh Phung, 2020, ICML.

Multiple distribution data description learning method for novelty detection

Trung Le, Wanli Ma, Dat Tran, 2011, The 2011 International Joint Conference on Neural Networks.

Bayesian Multi-Hyperplane Machine for Pattern Recognition

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Scalable Support Vector Clustering Using Budget pdf

Trung Le, Tung Pham, Hang Dang, 2017, ArXiv.

Analogical-based Bayesian Optimization pdf

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, ArXiv.

Three-Player Wasserstein GAN via Amortised Duality

Nhan Dam, Trung Le, Tu Dinh Nguyen, 2019, IJCAI.

One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems

Trung Le, Svetha Venkatesh, Tu Dinh Nguyen, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

Proximity multi-sphere support vector clustering

Trung Le, Wanli Ma, Dat Tran, 2013, Neural Computing and Applications.

Robust Variational Learning for Multiclass Kernel Models with Stein Refinement

Trung Le, Dinh Phung, Tu Nguyen, 2020 .

Multi-Sphere Support Vector Clustering

Trung Le, Wanli Ma, Dat Tran, 2011, ICONIP.

KGAN: How to Break The Minimax Game in GAN pdf

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, ArXiv.

Dual Space Gradient Descent for Online Learning

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, NIPS.

Dual Discriminator Generative Adversarial Nets

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, NIPS.

Transfer2Attack: Text Adversarial Attack with Cross-Domain Interpretability

Trung Le, Dinh Phung, He Zhao, 2020 .

Scalable Support Vector Machine for Semi-supervised Learning pdf

Trung Le, Van Nguyen, Dinh Q. Phung, 2016, ArXiv.

Maximal Margin Approach to Kernel Generalised Learning Vector Quantisation for Brain-Computer Interface

Trung Le, Dat Tran, Dharmendra Sharma, 2012, ICONIP.

Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning

Trung Le, Dinh Q. Phung, Seyit Camtepe, 2021, ArXiv.

Generalised Support Vector Machine for Brain-Computer Interface

Trung Le, Wanli Ma, Dat Tran, 2011, ICONIP.

Learning Generative Adversarial Networks from Multiple Data Sources

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2019, IJCAI.

Neural Sinkhorn Topic Model pdf

Trung Le, Dinh Phung, He Zhao, 2020, ArXiv.

Discriminative Bayesian Nonparametric Clustering

Trung Le, Dinh Q. Phung, Vu Nguyen, 2017, IJCAI.

Kernel-based semi-supervised learning for novelty detection

Trung Le, Van Nguyen, Mi Dinh, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Fuzzy entropy semi-supervised support vector data description

Trung Le, Wanli Ma, Dat Tran, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data

Geoffrey I. Webb, Trung Le, Tu Dinh Nguyen, 2018, KDD.

Fast One-Class Support Vector Machine for Novelty Detection

Trung Le, Svetha Venkatesh, Dinh Q. Phung, 2015, PAKDD.

Offset Curves Loss for Imbalanced Problem in Medical Segmentation pdf

Trung Le, Toan Duc Bui, Marios Savvides, 2020, 2020 25th International Conference on Pattern Recognition (ICPR).

Memetic Algorithm for a University Course Timetabling Problem

Trung Le, Khang Nguyen, Nuong Tran, 2011 .

Fuzzy Multi-Sphere Support Vector Data Description

Trung Le, Wanli Ma, Dat Tran, 2013, PAKDD.

GoGP: scalable geometric-based Gaussian process for online regression

Trung Le, Tu Dinh Nguyen, Khanh Nguyen, 2018, Knowledge and Information Systems.

Supervised Restricted Boltzmann Machines

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, UAI.

Batch Normalized Deep Boltzmann Machines

Wei Luo, Trung Le, Tu Dinh Nguyen, 2018, ACML.

Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness pdf

Trung Le, Dinh Phung, Tamas Abraham, 2020, ArXiv.

Fast Kernel-based method for anomaly detection

Trung Le, Dat Tran, Van Nguyen, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation

Trung Le, Dinh Q. Phung, Michael Papasimeon, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Electrooculography Feature Extraction Techniques for Classification of Eye Movements

Trung Le, Thi Thai Thanh Le, Toan Le, 2018, IFMBE Proceedings.

Fuzzy Multi-sphere Support Vector Data Description

Trung Le, Wanli Ma, Dat Tran, 2012, 2012 IEEE International Conference on Fuzzy Systems.

Multi-Generator Generative Adversarial Nets pdf

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, ArXiv.

Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability pdf

Trung Le, Dinh Phung, He Zhao, 2020, ArXiv.

Text Generation with Deep Variational GAN pdf

Trung Le, Dinh Q. Phung, Michael Papasimeon, 2021, ArXiv.

Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability

Trung Le, Dinh Phung, He Zhao, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

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

Trung Le, Tung Pham, Khai Nguyen, 2021, ArXiv.

LAMDA: Label Matching Deep Domain Adaptation

Trung Le, Dinh Phung, Nhat Ho, 2021, ICML.

Improved and Efficient Text Adversarial Attacks using Target Information pdf

Trung Le, Dinh Phung, He Zhao, 2021, ArXiv.

Large Sample Asymptotic for Nonparametric Mixture Model with Count Data

Trung Le, Svetha Venkatesh, Dinh Phung, 2015 .

Sparkling Vector Machines

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2015 .