8 papers · 1 filter
LLM as Detector: An In-context Learning Approach for Tabular Anomaly Detection
Tu Anh Hoang Nguyen, Dang Nguyen, Thuc Duy Le +2
Anomaly detection in tabular data is challenging because abnormal samples often arise as violations of cross-feature dependencies rather than simple marginal deviations. Existing d…
Diverse Image Priors for Black-box Data-free Knowledge Distillation
Tri-Nhan Vo, Dang Nguyen, Trung Le +2
Knowledge distillation (KD) represents a vital mechanism to transfer expertise from complex teacher networks to efficient student models. However, in decentralized or secure AI eco…
High-dimensional Level Set Estimation with Trust Regions and Double Acquisition Functions
Giang Ngo, Dat Phan Trong, Dang Nguyen +1
Level set estimation (LSE) classifies whether an unknown function's value exceeds a specified threshold for given inputs, a fundamental problem in many real-world applications. In…
Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
Giang Ngo, Dat Phan Trong, Dang Nguyen +2
Bayesian Optimization critically depends on the choice of acquisition function, but no single strategy is universally optimal; the best choice is non-stationary and problem-depende…
Causal-Aware Generative Adversarial Networks with Reinforcement Learning
Tu Anh Hoang Nguyen, Dang Nguyen, Tri-Nhan Vo +2
The utility of tabular data for tasks ranging from model training to large-scale data analysis is often constrained by privacy concerns or regulatory hurdles. While existing data g…
Generating Realistic Tabular Data with Large Language Models
Dang Nguyen, Sunil Gupta, Kien Do +2
While most generative models show achievements in image data generation, few are developed for tabular data generation. Recently, due to success of large language models (LLM) in d…