147 citations · 251 across the 21 of their papers we have counts for
21 papers
Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches
Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen +1
Randomized smoothing has recently attracted attentions in the field of adversarial robustness to provide provable robustness guarantees on smoothed neural network classifiers. Howe…
Time-to-Pattern: Information-Theoretic Unsupervised Learning for Scalable Time Series Summarization
Alireza Ghods, Trong Nghia Hoang, Diane Cook
Data summarization is the process of generating interpretable and representative subsets from a dataset. Existing time series summarization approaches often search for recurring su…
Personalized Federated Domain Adaptation for Item-to-Item Recommendation
Ziwei Fan, Hao Ding, Anoop Deoras +1
Item-to-Item (I2I) recommendation is an important function in most recommendation systems, which generates replacement or complement suggestions for a particular item based on its…
Federated Learning of Models Pre-Trained on Different Features with Consensus Graphs
Tengfei Ma, Trong Nghia Hoang, Jie Chen
Learning an effective global model on private and decentralized datasets has become an increasingly important challenge of machine learning when applied in practice. Existing distr…
Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms
Linbo Liu, Youngsuk Park, Trong Nghia Hoang +2
This work studies the threats of adversarial attack on multivariate probabilistic forecasting models and viable defense mechanisms. Our studies discover a new attack pattern that n…
Learning Personalized Item-to-Item Recommendation Metric via Implicit Feedback
Trong Nghia Hoang, Anoop Deoras, Tong Zhao +2
This paper studies the item-to-item recommendation problem in recommender systems from a new perspective of metric learning via implicit feedback. We develop and investigate a pers…