← Authors

Trong Nghia Hoang

23 papers · 2013–2026 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (12) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (38) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (15) 🌍 Conference Polyglot (7) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (80) πŸš€ Conference Pioneer πŸ’Ž Century Club (21) πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter ⚑ Prolific Year (8)

Conferences

AAAI (6) ICML (5) IJCAI (4) UAI (4) NIPS (2) ICCV (1) ICLR (1)

Top co-authors

Minh Hoang (4) Quang Minh Hoang (3) Aryan Deshwal (3) Bryan Kian Hsiang Low (3) Phi Le Nguyen (3) Kian Hsiang Low (3) Jimeng Sun (2) Jana Doppa (2) Cao Xiao (2) Azza Fadhel (2)

Keywords

federated learning (6) gaussian process (4) transfer learning (3) domain adaptation (3) variational inference (2) representation learning (2) distributed learning (2) sparse gaussian process (2) knowledge distillation (2) prompt tuning (2) pre-trained model (2) bayesian optimization (2) offline optimization (2) surrogate model (2) computer vision (1) continual learning (1) probabilistic modeling (1) multimodal learning (1) online learning (1) active learning (1)

Papers

ForeSWE: Forecasting Snow-Water Equivalent with an Uncertainty-Aware Attention Model AAAI 2026
Nanoporous Materials Discovery via Search Bias-Guided Surrogate Modeling AAAI 2026
Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data ICCV 2025
Few-Shot Learning via Repurposing Ensemble of Black-Box Models AAAI 2024
Collaborative Learning across Heterogeneous Systems with Pre-Trained Models AAAI 2024
Boosting Offline Optimizers with Surrogate Sensitivity ICML 2024
Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data NIPS 2024
Offline Model-Based Optimization via Policy-Guided Gradient Search AAAI 2024
Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques NIPS 2024
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching ICML 2024
Revisiting Kernel Attention with Correlated Gaussian Process Representation UAI 2024
Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms ICLR 2023
Federated learning of models pre-trained on different features with consensus graphs UAI 2023
Personalized federated domain adaptation for item-to-item recommendation UAI 2023
Bayesian federated estimation of causal effects from observational data UAI 2022
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems AAAI 2019
DDL: Deep Dictionary Learning for Predictive Phenotyping IJCAI 2019
RDPD: Rich Data Helps Poor Data via Imitation IJCAI 2019
A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models ICML 2016
A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data ICML 2015
Nonmyopic Ξ΅-Bayes-Optimal Active Learning of Gaussian Processes ICML 2014
Interactive POMDP Lite: Towards Practical Planning to Predict and Exploit Intentions for Interacting with Self-Interested Agents IJCAI 2013
A General Framework for Interacting Bayes-Optimally with Self-Interested Agents Using Arbitrary Parametric Model and Model Prior IJCAI 2013