My T. Thai

23 papers · 2019–2026 · 9 conferences · across top CS/AI conferences

Achievements

+9 more ↓

🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🌍 Conference Polyglot (8)

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (6) 🏆 Grand Slam 🗃️ Keyword Collector (100) 📈 Trend Setter 💎 Century Club (22) 🔥 Unstoppable (7) ⚡ Prolific Year (8)

Conferences

ICML (5) AAAI (4) AISTATS (4) IJCAI (3) ICLR (2) NIPS (2) ACL (1) ICCV (1) JMLR (1)

Top co-authors

Truc Nguyen (5) Phung Lai (2) Phi Le Nguyen (2) Nguyen Hoang Khoi Do (2) Liang Zhao (2) Minh Vu (2) Dejing Dou (2) Lan N. Nguyen (2) NhatHai Phan (2) Hai Phan (2)

Research topics

Differential Privacy (3) Privacy (1)

Keywords

differential privacy (4) combinatorial optimization (3) federated learning (3) representation learning (2) large language model (2) graph neural network (2) probabilistic graphical model (2) submodular maximization (2) adversarial attack (2) approximation algorithm (2) explainable ai (2) membership inference attack (2) influence maximization (2) neural network (2) model explanation (2) domain adaptation (2) adversarial robustness (2) adversarial learning (1) metric learning (1) transformer architecture (1)

Papers

Discovering a Shared Logical Subspace: Steering LLM Logical Reasoning via Alignment of Natural-Language and Symbolic Views ACL 2026 NeurFlow: Interpreting Neural Networks through Neuron Groups and Functional Interactions ICLR 2025 Metric-Agnostic Continual Learning for Sustainable Group Fairness AAAI 2025 XTSFormer: Cross-Temporal-Scale Transformer for Irregular-Time Event Prediction in Clinical Applications AAAI 2025 ConstStyle: Robust Domain Generalization with Unified Style Transformation ICCV 2025 Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models ICLR 2025 Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models ICML 2025 Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws ICML 2025 EMaP: Explainable AI with Manifold-based Perturbations JMLR 2025 MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization AISTATS 2024 Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data NIPS 2024 Analysis of Privacy Leakage in Federated Large Language Models AISTATS 2024 XRand: Differentially Private Defense against Explanation-Guided Attacks AAAI 2023 Active Membership Inference Attack under Local Differential Privacy in Federated Learning AISTATS 2023 On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network AISTATS 2023 Deep Graph Representation Learning and Optimization for Influence Maximization ICML 2023 Linear Query Approximation Algorithms for Non-monotone Submodular Maximization under Knapsack Constraint IJCAI 2023 Efficient Algorithms for Monotone Non-Submodular Maximization with Partition Matroid Constraint IJCAI 2022 Minimum Robust Multi-Submodular Cover for Fairness AAAI 2021 Scalable Differential Privacy with Certified Robustness in Adversarial Learning ICML 2020 Streaming k-Submodular Maximization under Noise subject to Size Constraint ICML 2020 PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks NIPS 2020 Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness IJCAI 2019