1 citations · 1 across the 9 of their papers we have counts for
9 papers
Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship
Nang Hung Nguyen, Phi Le Nguyen, Thao Nguyen Truong +2
This paper introduces a new framework for recovering causal graphs from observational data, leveraging the observation that the distribution of an effect, conditioned on its causes…
Rethinking Cross-Modal Fine-Tuning: Optimizing the Interaction Between Feature Alignment and Target Fitting
Trong Khiem Tran, Manh Cuong Dao, Phi Le Nguyen +2
Adapting pre-trained models to unseen feature modalities has become increasingly important due to the growing need for cross-disciplinary knowledge integration. A key challenge her…
ROOT: Rethinking Offline Optimization as Distributional Translation via Probabilistic Bridge
Manh Cuong Dao, The Hung Tran, Phi Le Nguyen +2
This paper studies the black-box optimization task which aims to find the maxima of a black-box function using a static set of its observed input-output pairs. This is often achiev…
Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques
Manh Cuong Dao, Phi Le Nguyen, Thao Nguyen Truong +1
Offline optimization has recently emerged as an increasingly popular approach to mitigate the prohibitively expensive cost of online experimentation. The key idea is to learn a sur…
Boosting Offline Optimizers with Surrogate Sensitivity
Manh Cuong Dao, Phi Le Nguyen, Thao Nguyen Truong +1
Offline optimization is an important task in numerous material engineering domains where online experimentation to collect data is too expensive and needs to be replaced by an in s…
FedBlock: A Blockchain Approach to Federated Learning against Backdoor Attacks
Duong H. Nguyen, Phi L. Nguyen, Truong T. Nguyen +2
Federated Learning (FL) is a machine learning method for training with private data locally stored in distributed machines without gathering them into one place for central learnin…
CT to PET Translation: A Large-scale Dataset and Domain-Knowledge-Guided Diffusion Approach
Dac Thai Nguyen, Trung Thanh Nguyen, Huu Tien Nguyen +5
Positron Emission Tomography (PET) and Computed Tomography (CT) are essential for diagnosing, staging, and monitoring various diseases, particularly cancer. Despite their importanc…
FedCert: Federated Accuracy Certification
Minh Hieu Nguyen, Huu Tien Nguyen, Trung Thanh Nguyen +4
Federated Learning (FL) has emerged as a powerful paradigm for training machine learning models in a decentralized manner, preserving data privacy by keeping local data on clients.…
CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization
Nang Hung Nguyen, Duc Long Nguyen, Trong Bang Nguyen +4
Federated learning enables edge devices to train a global model collaboratively without exposing their data. Despite achieving outstanding advantages in computing efficiency and pr…