8 citations · 31 across the 13 of their papers we have counts for
5 papers · 1 filter
Double Adaptive Stochastic Gradient Optimization
Kin Gutierrez, Jin Li, Cristian Challu +1
Adaptive moment methods have been remarkably successful in deep learning optimization, particularly in the presence of noisy and/or sparse gradients. We further the advantages of a…
On the Interaction Effects Between Prediction and Clustering
Matt Barnes, Artur Dubrawski
Machine learning systems increasingly depend on pipelines of multiple algorithms to provide high quality and well structured predictions. This paper argues interaction effects betw…
Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
Yichong Xu, Sivaraman Balakrishnan, Aarti Singh +1
In supervised learning, we typically leverage a fully labeled dataset to design methods for function estimation or prediction. In many practical situations, we are able to obtain a…
Noise-Tolerant Interactive Learning from Pairwise Comparisons
Yichong Xu, Hongyang Zhang, Aarti Singh +2
We study the problem of interactively learning a binary classifier using noisy labeling and pairwise comparison oracles, where the comparison oracle answers which one in the given…
Clustering on the Edge: Learning Structure in Graphs
Matt Barnes, Artur Dubrawski
With the recent popularity of graphical clustering methods, there has been an increased focus on the information between samples. We show how learning cluster structure using edge…