Latest Research in Machine Learning
38 research papers · 2026 median publication year
Top Research Topics in Machine Learning
- Statistics Theory — 14 papers
- Optimization and Control — 6 papers
- Machine Learning — 4 papers
- Statistical Methods and Inference — 2 papers
- Machine Learning — 2 papers
- Methodology — 2 papers
- Numerical Analysis — 2 papers
- Random Matrices and Applications — 1 papers
- Mathematical Inequalities and Applications — 1 papers
- Computation — 1 papers
Highest-Cited Papers
- Convergence Analysis of a Greedy Algorithm for Conditioning Gaussian Random Variables
- Gradient Descent with Stochastic Subspaces via Persistence of Memory
- Inverse Problems Over Probability Measure Space
- Robust Error Bounds for Vector-Valued Kernel Ridge Regression
- Characterizing Heterogeneous Rates in Finite Mixture Estimation via Partial Optimal Transport
- Extension of Likelihood Ratio Analysis Method to Skorokhod $M_1$ Topology (with Application to Poissonian Smooth Change-Point Model)
- Extension of Likelihood Ratio Analysis Method to Skorokhod $M_1$ Topology (with Application to Poissonian Smooth Change-Point Model)
- Learning to Solve Stochastic Controls with Unknown Drifts and Running Rewards: Theory, Algorithms and Convergence
- On Universality of Non-Separable Approximate Message Passing Algorithms
- Quantile-based Loss Filtering for Outlier-Robust Stochastic Gradient Descent
- Optimal Rates of Convergence for Entropy Regularization in Discounted Markov Decision Processes
- Optimal transport based theory for latent structured models
- Critical-Window Lower Bounds for Gaussian Regression with Bounded-Renewal Linear Splines
- Unified Stein‐Type Characterizations of Bivariate Count Distributions With Applications
- Minimax Lower Bound for Estimating Diffusion-based Local Intrinsic Dimension
- A complete characterization of sequential testability and change detectability in i.i.d. models
- Exact Limits of Random Projections for Preserving Geometry: Distance Recovery, Nearest-Neighbor Rankings, and Covariance Shape in Gaussian Models
- Probability-Maximizing Change Detection: Finite-Window Optimality
- Extending Subsampling to Sequential Stopping
- Scalable Inversion of Contests with Correlated Performances, Including Softmax and Multinomial Probit