130 citations · 317 across the 27 of their papers we have counts for
29 papers
Revisiting Self-Training with Regularized Pseudo-Labeling for Tabular Data
Minwook Kim, Juseong Kim, Giltae Song
Recent progress in semi- and self-supervised learning has caused a rift in the long-held belief about the need for an enormous amount of labeled data for machine learning and the i…
Optimal Activation Functions for the Random Features Regression Model
Jianxin Wang, José Bento
The asymptotic mean squared test error and sensitivity of the Random Features Regression model (RFR) have been recently studied. We build on this work and identify in closed-form t…
Distributed Optimization, Averaging via ADMM, and Network Topology
Guilherme França, José Bento
There has been an increasing necessity for scalable optimization methods, especially due to the explosion in the size of datasets and model complexity in modern machine learning ap…
Variational Wasserstein Barycenters for Geometric Clustering
Liang Mi
We propose to compute Wasserstein barycenters (WBs) by solving for Monge maps with variational principle. We discuss the metric properties of WBs and explore their connections, esp…
A Family of Pairwise Multi-Marginal Optimal Transports that Define a Generalized Metric
Liang Mi, Azadeh Sheikholeslami, José Bento
The Optimal transport (OT) problem is rapidly finding its way into machine learning. Favoring its use are its metric properties. Many problems admit solutions with guarantees only…
Exact inference under the perfect phylogeny model
Surjyendu Ray, Bei Jia, Sam Safavi +4
Motivation: Many inference tools use the Perfect Phylogeny Model (PPM) to learn trees from noisy variant allele frequency (VAF) data. Learning in this setting is hard, and existing…