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stat.ML2025

An Efficient Variant of One-Class SVM with Lifelong Online Learning Guarantees

Joe Suk, Samory Kpotufe

We study outlier (a.k.a., anomaly) detection for single-pass non-stationary streaming data. In the well-studied offline or batch outlier detection problem, traditional methods such…

stat.ML2025

Mixed-Sample SGD: an End-to-end Analysis of Supervised Transfer Learning

Yuyang Deng, Samory Kpotufe

Theoretical works on supervised transfer learning (STL) -- where the learner has access to labeled samples from both source and target distributions -- have for the most part focus…

stat.ML2025

Distributionally-Constrained Adversaries in Online Learning

Moïse Blanchard, Samory Kpotufe

There has been much recent interest in understanding the continuum from adversarial to stochastic settings in online learning, with various frameworks including smoothed settings p…

stat.ML2025

Nonlinear Meta-Learning Can Guarantee Faster Rates

Dimitri Meunier, Zhu Li, Arthur Gretton +1

Many recent theoretical works on \emph{meta-learning} aim to achieve guarantees in leveraging similar representational structures from related tasks towards simplifying a target ta…

stat.ML2025

Adaptive Sample Aggregation In Transfer Learning

Steve Hanneke, Samory Kpotufe

Transfer Learning aims to optimally aggregate samples from a target distribution, with related samples from a so-called source distribution to improve target risk. Multiple procedu…

stat.ML2024

Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products

Gan Yuan, Mingyue Xu, Samory Kpotufe +1

We consider the problem of sufficient dimension reduction (SDR) for multi-index models. The estimators of the central mean subspace in prior works either have slow (non-parametric)…