4 papers
Hierarchical Relationship Alignment Metric Learning
Lifeng Gu
Most existing metric learning methods focus on learning a similarity or distance measure relying on similar and dissimilar relations between sample pairs. However, pairs of samples…
Estimating and Improving Fairness with Adversarial Learning
Xiaoxiao Li, Ziteng Cui, Yifan Wu +2
Fairness and accountability are two essential pillars for trustworthy Artificial Intelligence (AI) in healthcare. However, the existing AI model may be biased in its decision marki…
Positive semidefinite support vector regression metric learning
Lifeng Gu
Most existing metric learning methods focus on learning a similarity or distance measure relying on similar and dissimilar relations between sample pairs. However, pairs of samples…
Adversarial Distillation of Bayesian Neural Network Posteriors
Kuan-Chieh Wang, Paul Vicol, James Lucas +3
Bayesian neural networks (BNNs) allow us to reason about uncertainty in a principled way. Stochastic Gradient Langevin Dynamics (SGLD) enables efficient BNN learning by drawing sam…