109 citations · 252 across the 16 of their papers we have counts for
8 papers · 1 filter
Structured Evaluation of Synthetic Tabular Data
Scott Cheng-Hsin Yang, Baxter Eaves, Michael Schmidt +2
Tabular data is common yet typically incomplete, small in volume, and access-restricted due to privacy concerns. Synthetic data generation offers potential solutions. Many metrics…
Explainable AI for medical imaging: Explaining pneumothorax diagnoses with Bayesian Teaching
Tomas Folke, Scott Cheng-Hsin Yang, Sean Anderson +1
Limited expert time is a key bottleneck in medical imaging. Due to advances in image classification, AI can now serve as decision-support for medical experts, with the potential fo…
Interpretable deep Gaussian processes with moments
Chi-Ken Lu, Scott Cheng-Hsin Yang, Xiaoran Hao +1
Deep Gaussian Processes (DGPs) combine the expressiveness of Deep Neural Networks (DNNs) with quantified uncertainty of Gaussian Processes (GPs). Expressive power and intractable i…
Discrepancy-Based Algorithms for Non-Stationary Rested Bandits
Corinna Cortes, Giulia DeSalvo, Vitaly Kuznetsov +2
We study the multi-armed bandit problem where the rewards are realizations of general non-stationary stochastic processes, a setting that generalizes many existing lines of work an…
Optimal Cooperative Inference
Scott Cheng-Hsin Yang, Yue Yu, Arash Givchi +3
Cooperative transmission of data fosters rapid accumulation of knowledge by efficiently combining experiences across learners. Although well studied in human learning and increasin…
Online Learning with Automata-based Expert Sequences
Mehryar Mohri, Scott Yang
We consider a general framework of online learning with expert advice where regret is defined with respect to sequences of experts accepted by a weighted automaton. Our framework c…
Online Learning with Abstention
Corinna Cortes, Giulia DeSalvo, Claudio Gentile +2
We present an extensive study of the key problem of online learning where algorithms are allowed to abstain from making predictions. In the adversarial setting, we show how existin…
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Corinna Cortes, Xavi Gonzalvo, Vitaly Kuznetsov +2
We present new algorithms for adaptively learning artificial neural networks. Our algorithms (AdaNet) adaptively learn both the structure of the network and its weights. They are b…