361 citations
- Carnegie Mellon UniversityUS12 papers
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5 papers · 1 filter
A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization
Mathieu Dagréou, Thomas Moreau, Samuel Vaiter +1
Bilevel optimization problems, which are problems where two optimization problems are nested, have more and more applications in machine learning. In many practical cases, the uppe…
Missing Data Imputation using Optimal Transport
Boris Muzellec, Julie Josse, Claire Boyer +1
Missing data is a crucial issue when applying machine learning algorithms to real-world datasets. Starting from the simple assumption that two batches extracted randomly from the s…
PiPs: a Kernel-based Optimization Scheme for Analyzing Non-Stationary 1D Signals
Jieren Xu, Yitong Li, Haizhao Yang +2
This paper proposes a novel kernel-based optimization scheme to handle tasks in the analysis, e.g., signal spectral estimation and single-channel source separation of 1D non-statio…
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data
Makoto Yamada, Jiliang Tang, Jose Lugo-Martinez +10
Machine learning methods are used to discover complex nonlinear relationships in biological and medical data. However, sophisticated learning models are computationally unfeasible…
Explaining the Success of AdaBoost and Random Forests as Interpolating Classifiers
Abraham J. Wyner, Matthew Olson, Justin Bleich +1
There is a large literature explaining why AdaBoost is a successful classifier. The literature on AdaBoost focuses on classifier margins and boosting's interpretation as the optimi…