6 papers · 1 filter
Representing short-term movement to reveal animal identity and learning progress
Ping Zhang, Quang-Huy Nguyen, Yingtie Lei +5
How learning progresses over time and varies across individuals is a longstanding question in cognitive and behavioral science. However, a major challenge is identifying observable…
Ontic state recovery through prediction
Ping Zhang, Quang-Huy Nguyen, Yingtie Lei +1
We encounter a system through its responses, yet its state concerns how the system is. Predicting further responses promises knowledge beyond what is immediately observed. What tha…
Conformalized Neural Networks for Federated Uncertainty Quantification under Dual Heterogeneity
Quang-Huy Nguyen, Jiaqi Wang, Wei-Shinn Ku
Federated learning (FL) faces challenges in uncertainty quantification (UQ). Without reliable UQ, FL systems risk deploying overconfident models at under-resourced agents, leading…
Improving Pareto Set Learning for Expensive Multi-objective Optimization via Stein Variational Hypernetworks
Minh-Duc Nguyen, Phuong Mai Dinh, Quang-Huy Nguyen +2
Expensive multi-objective optimization problems (EMOPs) are common in real-world scenarios where evaluating objective functions is costly and involves extensive computations or phy…
Detecting Out-of-Distribution Objects through Class-Conditioned Inpainting
Quang-Huy Nguyen, Jin Peng Zhou, Zhenzhen Liu +4
Recent object detectors have achieved impressive accuracy in identifying objects seen during training. However, real-world deployment often introduces novel and unexpected objects,…
Controllable Expensive Multi-objective Learning with Warm-starting Bayesian Optimization
Quang-Huy Nguyen, Long P. Hoang, Hoang V. Viet +1
Pareto Set Learning (PSL) is a promising approach for approximating the entire Pareto front in multi-objective optimization (MOO) problems. However, existing derivative-free PSL me…