arXiv Machine Learning
Jul 23
Lipschitzian SLLNs for random functions
arXiv:2607. 20411v1 Announce Type: cross Abstract: We prove strong laws of large numbers for locally Lipschitz functions in the Lipschitz pseudometric.
Lipschitzian SLLNs for random functions
We prove strong laws of large numbers for locally Lipschitz functions in the Lipschitz pseudometric. Our results hold under either a topological or a model-theoretic condition, with the latter encompassing functions jointly definable in o-minimal structures but extending substantially beyond this class.
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arXiv Machine Learning
Jun 25
Structured Approximations of Measures
arXiv:2310. 09149v3 Announce Type: replace-cross Abstract: We study the approximation of probability measures in the Wasserstein-$p$ distance by structured classes of approximators, motivated by applications in imaging, machine learning, and physical measurement under sensor constraints.
arXiv Machine Learning
Aug 7
On Same-Sample and Independent-Sample Stochastic Extragradient for Monotone Variational Inequalities
arXiv:2608. 06182v1 Announce Type: cross Abstract: We study stochastic extragradient (SEG) methods for solving monotone variational inequality problems (VIPs) over a feasible set.
arXiv AI
Jun 4
Does Order Matter : Connecting The Law of Robustness to Robust Generalization
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arXiv Machine Learning
Jun 15
Recovery thresholds for hidden weighted sparse graphs
arXiv:2606. 14335v1 Announce Type: cross Abstract: Recovering structural information from noisy high-dimensional data is a fundamental task in statistical inference.
arXiv Machine Learning
Jun 5
Sharp First-Order Lower Bounds for Higher-Order Smooth Nonconvex Optimization
arXiv:2606. 05438v1 Announce Type: new Abstract: We study the deterministic first-order oracle complexity of finding \(\epsilon\)-stationary points in smooth nonconvex optimization when the objective satisfies higher-order smoothness assumptions.
arXiv Machine Learning
Jul 9
Finding a stationary point of a stochastic convex problem
arXiv:2607. 06883v1 Announce Type: cross Abstract: We consider the problem of finding stationary points for stochastic convex optimization problems.
arXiv Machine Learning
Aug 10
A proximal subgradient method for nonconvex stochastic optimization under the Kurdyka-{\L}ojasiewicz condition
arXiv:2608. 05460v1 Announce Type: cross Abstract: This work introduces a proximal stochastic subgradient method for minimizing the sum of an expected cost, whose integrand is potentially nonsmooth and nonconvex, and a lower semicontinuous, prox-bounded function.
arXiv Machine Learning
Jul 15
Learning and Testing Convex Functions
arXiv:2511. 11498v2 Announce Type: replace-cross Abstract: We consider the problems of \emph{learning} and \emph{testing} real-valued convex functions over Gaussian space.
arXiv Machine Learning
Jun 24
New Bounds for the Last Iterate of the Stochastic subGradient Method
arXiv:2606. 24879v1 Announce Type: cross Abstract: We study the last iterate of the stochastic subgradient method for one-dimensional convex Lipschitz objectives.
arXiv Machine Learning
Jun 24
Separating Oblivious and Adaptive Models of Variable Selection
arXiv:2602. 16568v2 Announce Type: replace-cross Abstract: Sparse recovery is among the most well-studied problems in learning theory and high-dimensional statistics.
arXiv Machine Learning
Jul 28
Efficient Learning of Truncated Boolean Product Distributions: Influence to the Rescue
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