Trung Le

Orcid: 0000-0003-0414-9067

According to our database1, Trung Le authored at least 177 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
AL-SAR: Active Learning for Skeleton-Based Action Recognition.
IEEE Trans. Neural Networks Learn. Syst., November, 2024

Deep Domain Adaptation With Max-Margin Principle for Cross-Project Imbalanced Software Vulnerability Detection.
ACM Trans. Softw. Eng. Methodol., July, 2024

Vision Transformer Inspired Automated Vulnerability Repair.
ACM Trans. Softw. Eng. Methodol., March, 2024

AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities.
Empir. Softw. Eng., February, 2024

Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts.
CoRR, 2024

Preserving Generalization of Language models in Few-shot Continual Relation Extraction.
CoRR, 2024

Connective Viewpoints of Signal-to-Noise Diffusion Models.
CoRR, 2024

MetaAug: Meta-Data Augmentation for Post-Training Quantization.
CoRR, 2024

Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning.
CoRR, 2024

PromptDSI: Prompt-based Rehearsal-free Instance-wise Incremental Learning for Document Retrieval.
CoRR, 2024

Enhancing Domain Adaptation through Prompt Gradient Alignment.
CoRR, 2024

Agnostic Sharpness-Aware Minimization.
CoRR, 2024

Text-Enhanced Data-free Approach for Federated Class-Incremental Learning.
CoRR, 2024

Diversity-Aware Agnostic Ensemble of Sharpness Minimizers.
CoRR, 2024

Removing Undesirable Concepts in Text-to-Image Generative Models with Learnable Prompts.
CoRR, 2024

A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation.
CoRR, 2024

EraseDiff: Erasing Data Influence in Diffusion Models.
CoRR, 2024

DiffAugment: Diffusion based Long-Tailed Visual Relationship Recognition.
CoRR, 2024

Frequency Attention for Knowledge Distillation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Parameter Estimation in DAGs from Incomplete Data via Optimal Transport.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Optimal Transport for Structure Learning Under Missing Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Sharpness-Aware Data Generation for Zero-shot Quantization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Text-Enhanced Data-Free Approach for Federated Class-Incremental Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
VulExplainer: A Transformer-Based Hierarchical Distillation for Explaining Vulnerability Types.
IEEE Trans. Software Eng., October, 2023

The Effect of the Number of Hidden Layers on The Performance of Deep Q-Network for Traveling Salesman Problem.
Knowl. Eng. Data Sci., October, 2023

Polling-Based Memory Interface.
ACM Trans. Design Autom. Electr. Syst., 2023

Generating Adversarial Examples with Task Oriented Multi-Objective Optimization.
Trans. Mach. Learn. Res., 2023

A deep neural network and Bayesian method based framework for all-terminal network reliability estimation considering degradation.
Reliab. Eng. Syst. Saf., 2023

Class-Prototype Conditional Diffusion Model for Continual Learning with Generative Replay.
CoRR, 2023

KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All.
CoRR, 2023

Robust Contrastive Learning With Theory Guarantee.
CoRR, 2023

Unleash Data Generation for Efficient and Effective Data-free Knowledge Distillation.
CoRR, 2023

RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization.
CoRR, 2023

Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities.
CoRR, 2023

Learning Directed Graphical Models with Optimal Transport.
CoRR, 2023

Sharpness & Shift-Aware Self-Supervised Learning.
CoRR, 2023

Hyperbolic Geometry in Computer Vision: A Survey.
CoRR, 2023

Vector Quantized Wasserstein Auto-Encoder.
CoRR, 2023

Flat Seeking Bayesian Neural Networks.
CoRR, 2023

Redundant Array of Independent Memory Devices.
IEEE Comput. Archit. Lett., 2023

Adversarial local distribution regularization for knowledge distillation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Flat Seeking Bayesian Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimal Transport Model Distributional Robustness.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Time-Invariant Representations for Individual Neurons from Population Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Cross-Adversarial Local Distribution Regularization for Semi-supervised Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Vector Quantized Wasserstein Auto-Encoder.
Proceedings of the International Conference on Machine Learning, 2023

An Additive Instance-Wise Approach to Multi-class Model Interpretation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Empirical Evaluation of Autoencoder Models for Anomaly Detection in Packet-based NIDS.
Proceedings of the IEEE Conference on Dependable and Secure Computing, 2023

ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We?
Proceedings of the 30th Asia-Pacific Software Engineering Conference, 2023

Global-Local Regularization Via Distributional Robustness.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Robust Variational Learning for Multiclass Kernel Models With Stein Refinement.
IEEE Trans. Knowl. Data Eng., 2022

Improving kernel online learning with a snapshot memory.
Mach. Learn., 2022

Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance.
CoRR, 2022

Continual Learning with Optimal Transport based Mixture Model.
CoRR, 2022

Improving Multi-task Learning via Seeking Task-based Flat Regions.
CoRR, 2022

Vision Transformer Visualization: What Neurons Tell and How Neurons Behave?
CoRR, 2022

Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations.
CoRR, 2022

An Information-Theoretic and Contrastive Learning-based Approach for Identifying Code Statements Causing Software Vulnerability.
CoRR, 2022

Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle.
CoRR, 2022

STNDT: Modeling Neural Population Activity with a Spatiotemporal Transformer.
CoRR, 2022

Global-Local Regularization Via Distributional Robustness.
CoRR, 2022

A Unified Wasserstein Distributional Robustness Framework for Adversarial Training.
CoRR, 2022

ARNS: A Data-Driven Approach for SoH Estimation of Lithium-Ion Battery Using Nested Sequence Models With Considering Relaxation Effect.
IEEE Access, 2022

Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

VulRepair: a T5-based automated software vulnerability repair.
Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

Stochastic Multiple Target Sampling Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection.
Proceedings of the 44th IEEE/ACM International Conference on Software Engineering: Companion Proceedings, 2022

On Transportation of Mini-batches: A Hierarchical Approach.
Proceedings of the International Conference on Machine Learning, 2022

A Unified Wasserstein Distributional Robustness Framework for Adversarial Training.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Supporting Massive DLRM Inference through Software Defined Memory.
Proceedings of the 42nd IEEE International Conference on Distributed Computing Systems, 2022

Particle-based Adversarial Local Distribution Regularization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
On Label Shift in Domain Adaptation via Wasserstein Distance.
CoRR, 2021

Supporting Massive DLRM Inference Through Software Defined Memory.
CoRR, 2021

SyntheticFur dataset for neural rendering.
CoRR, 2021

Text Generation with Deep Variational GAN.
CoRR, 2021

Improved and Efficient Text Adversarial Attacks using Target Information.
CoRR, 2021

BoMb-OT: On Batch of Mini-batches Optimal Transport.
CoRR, 2021

Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning.
CoRR, 2021

Most: multi-source domain adaptation via optimal transport for student-teacher learning.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Information-theoretic Source Code Vulnerability Highlighting.
Proceedings of the International Joint Conference on Neural Networks, 2021

TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

LAMDA: Label Matching Deep Domain Adaptation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Neural Topic Model via Optimal Transport.
Proceedings of the 9th International Conference on Learning Representations, 2021

STEM: An approach to Multi-source Domain Adaptation with Guarantees.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

POMI: Polling-Based Memory Interface for Hybrid Memory System.
Proceedings of the 39th IEEE International Conference on Computer Design, 2021

Toward the first D-band Point to multipoint wireless system field test.
Proceedings of the Joint European Conference on Networks and Communications & 6G Summit, 2021

Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Towards Understanding Pixel Vulnerability under Adversarial Attacks for Images.
CoRR, 2020

Neural Sinkhorn Topic Model.
CoRR, 2020

Dual-Component Deep Domain Adaptation: A New Approach for Cross Project Software Vulnerability Detection.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Deep Cost-Sensitive Kernel Machine for Binary Software Vulnerability Detection.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Code Action Network for Binary Function Scope Identification.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Code Pointer Network for Binary Function Scope Identification.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Stein Variational Gradient Descent with Variance Reduction.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Offset Curves Loss for Imbalanced Problem in Medical Segmentation.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Parameterized Rate-Distortion Stochastic Encoder.
Proceedings of the 37th International Conference on Machine Learning, 2020

D-band Point to Multi-Point Deployment with G-Band Transport.
Proceedings of the 2020 European Conference on Networks and Communications, 2020

Improving Adversarial Robustness by Enforcing Local and Global Compactness.
Proceedings of the Computer Vision - ECCV 2020, 2020

Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

2019
GoGP: scalable geometric-based Gaussian process for online regression.
Knowl. Inf. Syst., 2019

Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions.
CoRR, 2019

When Can Neural Networks Learn Connected Decision Regions?
CoRR, 2019

Deep Domain Adaptation for Vulnerable Code Function Identification.
Proceedings of the International Joint Conference on Neural Networks, 2019

Learning Generative Adversarial Networks from Multiple Data Sources.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Three-Player Wasserstein GAN via Amortised Duality.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection.
Proceedings of the 7th International Conference on Learning Representations, 2019

Technology for D-band/G-band ultra capacity layer.
Proceedings of the European Conference on Networks and Communications, 2019

Robust Anomaly Detection in Videos Using Multilevel Representations.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Theoretical Perspective of Deep Domain Adaptation.
CoRR, 2018

Jointly Predicting Affective and Mental Health Scores Using Deep Neural Networks of Visual Cues on the Web.
Proceedings of the Web Information Systems Engineering - WISE 2018, 2018

Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Geometric Enclosing Networks.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Bayesian Multi-Hyperplane Machine for Pattern Recognition.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

MGAN: Training Generative Adversarial Nets with Multiple Generators.
Proceedings of the 6th International Conference on Learning Representations, 2018

Transmisson Hub and Terminals for Point to Multipoint W-Band Tweether System.
Proceedings of the 2018 European Conference on Networks and Communications, 2018

Batch Normalized Deep Boltzmann Machines.
Proceedings of The 10th Asian Conference on Machine Learning, 2018

Clustering Induced Kernel Learning.
Proceedings of The 10th Asian Conference on Machine Learning, 2018

2017
Fast support vector clustering.
Vietnam. J. Comput. Sci., 2017

Approximation Vector Machines for Large-scale Online Learning.
J. Mach. Learn. Res., 2017

KGAN: How to Break The Minimax Game in GAN.
CoRR, 2017

Scalable Support Vector Clustering Using Budget.
CoRR, 2017

Analogical-based Bayesian Optimization.
CoRR, 2017

Multi-Generator Generative Adversarial Nets.
CoRR, 2017

Supervised Restricted Boltzmann Machines.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Dual Discriminator Generative Adversarial Nets.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Discriminative Bayesian Nonparametric Clustering.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Large-scale Online Kernel Learning with Random Feature Reparameterization.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

GoGP: Fast Online Regression with Gaussian Processes.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016
Mixture of hyperspheres for novelty detection.
Vietnam. J. Comput. Sci., 2016

Scalable Support Vector Machine for Semi-supervised Learning.
CoRR, 2016

Budgeted Semi-supervised Support Vector Machine .
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Sparse Adaptive Multi-hyperplane Machine.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Dual Space Gradient Descent for Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Fuzzy Kernel Stochastic Gradient Descent machines.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Fast Kernel-based method for anomaly detection.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Distributed data augmented support vector machine on Spark.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Fast Support Vector Clustering.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Nonparametric Budgeted Stochastic Gradient Descent.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Multiple Kernel Learning with Data Augmentation.
Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015
Scheduling workloads in a network of datacentres to reduce electricity cost and carbon footprint.
Sustain. Comput. Informatics Syst., 2015

Fast One-Class Support Vector Machine for Novelty Detection.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Least square Support Vector Machine for large-scale dataset.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Graph-based semi-supervised Support Vector Data Description for novelty detection.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Kernel-based semi-supervised learning for novelty detection.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Using EEG artifacts for BCI applications.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Robust Support Vector Machine.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

2013
Proximity multi-sphere support vector clustering.
Neural Comput. Appl., 2013

EEG-Based Person Verification Using Multi-Sphere SVDD and UBM.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

Fuzzy Multi-Sphere Support Vector Data Description.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

Fuzzy entropy semi-supervised support vector data description.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Maximal margin learning vector quantisation.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012
A unified model for support vector machine and support vector data description.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Deterministic Annealing Multi-Sphere Support Vector Data Description.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

Maximal Margin Approach to Kernel Generalised Learning Vector Quantisation for Brain-Computer Interface.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

Time Domain Parameters for Online Feedback fNIRS-Based Brain-Computer Interface Systems.
Proceedings of the Neural Information Processing - 19th International Conference, 2012

Fuzzy Multi-sphere Support Vector Data Description.
Proceedings of the FUZZ-IEEE 2012, 2012

2011
CDAO-Store: Ontology-driven Data Integration for Phylogenetic Analysis.
BMC Bioinform., 2011

Multiple Distribution Data Description Learning Algorithm for Novelty Detection.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

Multiple distribution data description learning method for novelty detection.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Multi-Sphere Support Vector Clustering.
Proceedings of the Neural Information Processing - 18th International Conference, 2011

A Novel Parameter Refinement Approach to One Class Support Vector Machine.
Proceedings of the Neural Information Processing - 18th International Conference, 2011

Generalised Support Vector Machine for Brain-Computer Interface.
Proceedings of the Neural Information Processing - 18th International Conference, 2011

2010
Enhancing Performance of SVM-Based Brain-Computer Interface Systems.
Aust. J. Intell. Inf. Process. Syst., 2010

Fuzzy support vector machines for age and gender classification.
Proceedings of the 11th Annual Conference of the International Speech Communication Association, 2010

An optimal sphere and two large margins approach for novelty detection.
Proceedings of the International Joint Conference on Neural Networks, 2010

A Theoretical Framework for Multi-sphere Support Vector Data Description.
Proceedings of the Neural Information Processing. Models and Applications, 2010

A new support vector machine method for medical image classification.
Proceedings of the 2nd European Workshop on Visual Information Processing, 2010


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