:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Pehle, Christian, Slotine, Jean-Jacques
Formato:	Preprint
Publicado:	2026
Materias:	Optimization and Control Machine Learning
Acceso en línea:	https://arxiv.org/abs/2602.10461
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Contraction Theory for Nonlinear Stability Analysis and Learning-based Control: A Tutorial Overview
por: Tsukamoto, Hiroyasu, et al.
Publicado: (2021)

Riemannian Optimization in Modular Systems
por: Pehle, Christian, et al.
Publicado: (2026)

End-to-End Training of High-Dimensional Optimal Control with Implicit Hamiltonians via Jacobian-Free Backpropagation
por: Gelphman, Eric, et al.
Publicado: (2025)

DPZero: Private Fine-Tuning of Language Models without Backpropagation
por: Zhang, Liang, et al.
Publicado: (2023)

Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
por: Xiao, Quan, et al.
Publicado: (2024)

Contraction Properties of the Global Workspace Primitive
por: Ennis, Michaela, et al.
Publicado: (2023)

Checking the Sufficiently Scattered Condition using a Global Non-Convex Optimization Software
por: Gillis, Nicolas, et al.
Publicado: (2024)

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence
por: Jiao, Yang, et al.
Publicado: (2024)

Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization
por: Kolb, Chris, et al.
Publicado: (2023)

Flattened one-bit stochastic gradient descent: compressed distributed optimization with controlled variance
por: Stollenwerk, Alexander, et al.
Publicado: (2024)

Securing Multi-Agent Systems Against Corruptions via Node Contribution Backpropagation
por: Wu, Chengcan, et al.
Publicado: (2025)

Integrated Forecasting of Marine Renewable Power: An Adaptively Bayesian-Optimized MVMD-LSTM Framework for Wind-Solar-Wave Energy
por: Xie, Baoyi, et al.
Publicado: (2025)

Compact Lifted Relaxations for Low-Rank Optimization
por: Cory-Wright, Ryan, et al.
Publicado: (2026)

A new perspective on low-rank optimization
por: Bertsimas, Dimitris, et al.
Publicado: (2021)

Mixtures Closest to a Given Measure: A Semidefinite Programming Approach
por: Đurašinović, Srećko, et al.
Publicado: (2025)

Stochastic Adaptive Gradient Descent Without Descent
por: Aujol, Jean-François, et al.
Publicado: (2025)

A mathematical framework for time-delay reservoir computing analysis
por: Clabaut, Anh-Tuan, et al.
Publicado: (2026)

Measure-to-measure interpolation using Transformers
por: Geshkovski, Borjan, et al.
Publicado: (2024)

Disjunctive Branch-and-Bound for Certifiably Optimal Low-Rank Matrix Completion
por: Bertsimas, Dimitris, et al.
Publicado: (2023)

Deep Reinforcement Learning for Infinite Horizon Mean Field Problems in Continuous Spaces
por: Angiuli, Andrea, et al.
Publicado: (2023)

On Building Myopic MPC Policies using Supervised Learning
por: Orrico, Christopher A., et al.
Publicado: (2024)

Variable Bregman Majorization-Minimization Algorithm and its Application to Dirichlet Maximum Likelihood Estimation
por: Martin, Ségolène, et al.
Publicado: (2025)

Identifying Systems with Symmetries using Equivariant Autoregressive Reservoir Computers
por: Vides, Fredy, et al.
Publicado: (2023)

An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method
por: Zhang, Jiahao, et al.
Publicado: (2024)

Data Fusion and Machine Learning for Ship Fuel Consumption Modelling -- A Case of Bulk Carrier Vessel
por: Mohamed, Abdella, et al.
Publicado: (2025)

Apprenticeship learning with prior beliefs using inverse optimization
por: Junca, Mauricio, et al.
Publicado: (2025)

On the Convergence of Jacobian-Free Backpropagation for Optimal Control Problems with Implicit Hamiltonians
por: Gelphman, Eric, et al.
Publicado: (2026)

Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization
por: Yang, Jianting, et al.
Publicado: (2024)

Dynamic financial processes identification using sparse regressive reservoir computers
por: Vides, Fredy, et al.
Publicado: (2023)

Data-Driven Stochastic AC-OPF using Gaussian Processes
por: Mitrovic, Mile
Publicado: (2024)

Compression-aware Training of Neural Networks using Frank-Wolfe
por: Zimmer, Max, et al.
Publicado: (2022)

Learning to accelerate distributed ADMM using graph neural networks
por: Doerks, Henri, et al.
Publicado: (2025)

Global Search of Optimal Spacecraft Trajectories using Amortization and Deep Generative Models
por: Beeson, Ryne, et al.
Publicado: (2024)

Variance-Reduced $(\varepsilon,δ)-$Unlearning using Forget Set Gradients
por: Van Waerebeke, Martin, et al.
Publicado: (2026)

Non-Convex Robust Hypothesis Testing using Sinkhorn Uncertainty Sets
por: Wang, Jie, et al.
Publicado: (2024)

Classification under strategic adversary manipulation using pessimistic bilevel optimisation
por: Benfield, David, et al.
Publicado: (2024)

Common pitfalls to avoid while using multiobjective optimization in machine learning
por: Akhter, Junaid, et al.
Publicado: (2024)

Online Traffic Density Estimation using Physics-Informed Neural Networks
por: Wilkman, Dennis, et al.
Publicado: (2025)

Control of Dual-Sourcing Inventory Systems using Recurrent Neural Networks
por: Böttcher, Lucas, et al.
Publicado: (2022)

Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching
por: Chemseddine, Jannis, et al.
Publicado: (2024)