JMLR · Scour

Universality of Kernel Random Matrices and Kernel Regression in the Quadratic Regime

Talent: A Tabular Analytics and Learning Toolbox

Algorithms for ridge estimation with convergence guarantees

An Augmentation Overlap Theory of Contrastive Learning

On Probabilistic Embeddings in Optimal Dimension Reduction

Fair Text Classification via Transferable Representations

Hierarchical and Stochastic Crystallization Learning: Geometrically Leveraged Nonparametric Regression with Delaunay Triangulation

On the Representation of Pairwise Causal Background Knowledge and Its Applications in Causal Inference

Stochastic Interior-Point Methods for Smooth Conic Optimization with Applications

Online Quantile Regression

Statistical Inference of Random Graphs With a Surrogate Likelihood Function

Graph-accelerated Markov Chain Monte Carlo using Approximate Samples

General Loss Functions Lead to (Approximate) Interpolation in High Dimensions

(De)-regularized Maximum Mean Discrepancy Gradient Flow

Decentralized Bilevel Optimization: A Perspective from Transient Iteration Complexity

Piecewise deterministic sampling with splitting schemes

Physics Informed Kolmogorov-Arnold Neural Networks for Dynamical Analysis via Efficient-KAN and WAV-KAN

Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2

Generalized multi-view model: Adaptive density estimation under low-rank constraints

Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration

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