456 citations · 984 across the 34 of their papers we have counts for
7 papers · 1 filter
Benchmarking Multimodal AutoML for Tabular Data with Text Fields
Xingjian Shi, Jonas Mueller, Nick Erickson +2
We consider the use of automated supervised learning systems for data tables that not only contain numeric/categorical columns, but one or more text fields as well. Here we assembl…
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis +4
For supervised learning with tabular data, decision tree ensembles produced via boosting techniques generally dominate real-world applications involving iid training/test sets. How…
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing
Haoyu He, Xingjian Shi, Jonas Mueller +3
We aim to identify how different components in the KD pipeline affect the resulting performance and how much the optimal KD pipeline varies across different datasets/tasks, such as…
Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Junwen Yao, Jonas Mueller, Jane-Ling Wang
Despite their widespread success, the application of deep neural networks to functional data remains scarce today. The infinite dimensionality of functional data means standard lea…
Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
Curtis G. Northcutt, Anish Athalye, Jonas Mueller
We identify label errors in the test sets of 10 of the most commonly-used computer vision, natural language, and audio datasets, and subsequently study the potential for these labe…
Flexible Model Aggregation for Quantile Regression
Rasool Fakoor, Taesup Kim, Jonas Mueller +2
Quantile regression is a fundamental problem in statistical learning motivated by a need to quantify uncertainty in predictions, or to model a diverse population without being over…