Copertina

Forecasting Outside the Box: Application-Driven Optimal Pointwise Forecasts for Stochastic Optimization

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Homem-de-Mello, Tito, Valencia, Juan, Lagos, Felipe, Lagos, Guido
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Optimization and Control Machine Learning 90C15
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality
di: Cutler, Joshua, et al.
Pubblicazione: (2022)

Convergence Rate of a Functional Learning Method for Contextual Stochastic Optimization
di: Smith, Noel, et al.
Pubblicazione: (2026)

Robust Clustering on High-Dimensional Data with Stochastic Quantization
di: Kozyriev, Anton, et al.
Pubblicazione: (2024)

An Inexact Halpern Iteration with Application to Distributionally Robust Optimization
di: Liang, Ling, et al.
Pubblicazione: (2024)

A Normal Map-Based Proximal Stochastic Gradient Method: Convergence and Identification Properties
di: Qiu, Junwen, et al.
Pubblicazione: (2023)

Stochastic First-Order Methods with Non-smooth and Non-Euclidean Proximal Terms for Nonconvex High-Dimensional Stochastic Optimization
di: Xie, Yue, et al.
Pubblicazione: (2024)

Optimization without Retraction on the Random Generalized Stiefel Manifold
di: Vary, Simon, et al.
Pubblicazione: (2024)

Globalized Adversarial Regret Optimization: Robust Decisions with Uncalibrated Predictions
di: Kurtz, Jannis, et al.
Pubblicazione: (2026)

Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecasting
di: Garcia, Joaquim Dias, et al.
Pubblicazione: (2021)

A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization
di: Qiu, Junwen, et al.
Pubblicazione: (2023)

Shuffling the Stochastic Mirror Descent via Dual Lipschitz Continuity and Kernel Conditioning
di: Qiu, Junwen, et al.
Pubblicazione: (2026)

An Algebraically Converging Stochastic Gradient Descent Algorithm for Global Optimization
di: Engquist, Björn, et al.
Pubblicazione: (2022)

Stochastic Gradient Descent Revisited
di: Louzi, Azar
Pubblicazione: (2024)

Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence
di: Fatkhullin, Ilyas, et al.
Pubblicazione: (2024)

Boosted Stochastic Frank-Wolfe for Constrained Nonconvex Optimization
di: Nandhan, Navil, et al.
Pubblicazione: (2026)

Fully First-Order Methods for Decentralized Bilevel Optimization
di: Wang, Xiaoyu, et al.
Pubblicazione: (2024)

A Generalized Version of Chung's Lemma and its Applications
di: Jiang, Li, et al.
Pubblicazione: (2024)

MDP modeling for multi-stage stochastic programs
di: Morton, David P., et al.
Pubblicazione: (2025)

MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-Regularized Optimization
di: Li, Luxuan, et al.
Pubblicazione: (2026)

Efficient Data-Driven Optimization with Noisy Data
di: Van Parys, Bart P. G.
Pubblicazione: (2021)

BROS: Bias-Corrected Randomized Subspaces for Memory-Efficient Single-Loop Bilevel Optimization
di: Zhang, Hengrui, et al.
Pubblicazione: (2026)

Multi-timescale Stochastic Programming with Applications in Power Systems
di: Zhang, Yihang, et al.
Pubblicazione: (2025)

Achieving $\tilde{\mathcal{O}}(1/N)$ Optimality Gap in Restless Bandits through Gaussian Approximation
di: Yan, Chen, et al.
Pubblicazione: (2024)

A Framework for Balancing Power Grid Efficiency and Risk with Bi-objective Stochastic Integer Optimization
di: Rossmann, Ramsey, et al.
Pubblicazione: (2024)

Dynamic Systems Coupled with Solutions of Stochastic Nonsmooth Convex Optimization
di: Luo, Jianfeng, et al.
Pubblicazione: (2025)

Optimal Asymptotic Rates for (Stochastic) Gradient Descent under the Local PL-Condition: A Geometric Approach
di: Kassing, Sebastian, et al.
Pubblicazione: (2026)

Alternating Iteratively Reweighted $\ell_1$ and Subspace Newton Algorithms for Nonconvex Sparse Optimization
di: Wang, Hao, et al.
Pubblicazione: (2024)

Penalty-Free SDDP: Feasibility Cuts for Robust Multi-Stage Stochastic Optimization in Energy Planning
di: Freitas, Guilherme, et al.
Pubblicazione: (2025)

Lossy Image Compression with Stochastic Quantization
di: Kozyriev, Anton, et al.
Pubblicazione: (2024)

A Functional Model Method for Nonconvex Nonsmooth Conditional Stochastic Optimization
di: Ruszczyński, Andrzej, et al.
Pubblicazione: (2024)

Extended Triangle Inequalities for Nonconvex Box-Constrained Quadratic Programming
di: Anstreicher, Kurt M., et al.
Pubblicazione: (2025)

A Note on Piecewise Affine Decision Rules for Robust, Stochastic, and Data-Driven Optimization
di: Thomä, Simon, et al.
Pubblicazione: (2024)

Stochastic Optimization under Hidden Convexity
di: Fatkhullin, Ilyas, et al.
Pubblicazione: (2023)

Distributionally Risk-Receptive and Robust Multistage Stochastic Integer Programs and Interdiction Models
di: Kang, Sumin, et al.
Pubblicazione: (2024)

High Probability Guarantees for Random Reshuffling
di: Yu, Hengxu, et al.
Pubblicazione: (2023)

Differential Stochastic Variational Inequalities with Parametric Optimization
di: Chen, Xiaojun, et al.
Pubblicazione: (2025)

On Tackling High-Dimensional Nonconvex Stochastic Optimization via Stochastic First-Order Methods with Non-smooth Proximal Terms and Variance Reduction
di: Xie, Yue, et al.
Pubblicazione: (2025)

Bi-Parameterized Two-Stage Stochastic Min-Max and Min-Min Mixed Integer Programs
di: Kang, Sumin, et al.
Pubblicazione: (2025)

Global Optimality for Constrained Exploration via Penalty Regularization
di: Wolf, Florian, et al.
Pubblicazione: (2026)

Step-Size Stability in Stochastic Optimization: A Theoretical Perspective
di: Schaipp, Fabian, et al.
Pubblicazione: (2026)