High-Dimensional Optimization and Probability

Chapter 1 Projection of a Point onto a Convex Set via Charged Balls Method

Chapter 2 Towards Optimal Sampling for Learning Sparse Approximations in High Dimensions

Chapter 3 Recent Theoretical Advances in Non-Convex Optimization

Chapter 4 Higher Order Embeddings for the Composition of the Harmonic Projection and Homotopy Operators

Chapter 5 Codifferentials and Quasidifferentials of the Expectation of Nonsmooth Random Integrands and Two-Stage Stochastic Programming

Chapter 6 On the Expected Extinction Time for the Adjoint Circuit Chains Associated with a Random Walk with Jumps in Random Environments

Chapter 7 A Statistical Learning Theory Approach for the Analysis of the Trade-off Between Sample Size and Precision in Truncated Ordinary Least Squares

Chapter 8 Recent Theoretical Advances in Decentralized Distributed Convex Optimization

Chapter 9 On Training Set Selection in Spatial Deep Learning

Chapter 10 Surrogate-Based Reduced-Dimension Global Optimization in Process Systems Engineering

Chapter 11 A Viscosity Iterative Method with Alternated Inertial Terms for Solving the Split Feasibility Problem

Chapter 12 Efficient Location-Based Tracking for IoT Devices Using Compressive Sensing and Machine Learning Techniques

Chapter 13 Nonsmooth Mathematical Programs with Vanishing Constraints in Banach Spaces