Saved in:
| Main Authors: | Matsuoka, Tomoya, Ohsaki, Makoto, Hayashi, Kazuki |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.13869 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Laguerre geometry for optimization of gridshell with specified force distribution
by: Kabaki, Kohei, et al.
Published: (2025)
by: Kabaki, Kohei, et al.
Published: (2025)
Non-parametric structural shape optimization of piecewise developable surfaces using discrete differential geometry
by: Ohsaki, Makoto, et al.
Published: (2024)
by: Ohsaki, Makoto, et al.
Published: (2024)
Robust portfolio optimization for recommender systems considering uncertainty of estimated statistics
by: Yanagi, Tomoya, et al.
Published: (2024)
by: Yanagi, Tomoya, et al.
Published: (2024)
Common pitfalls to avoid while using multiobjective optimization in machine learning
by: Akhter, Junaid, et al.
Published: (2024)
by: Akhter, Junaid, et al.
Published: (2024)
Apprenticeship learning with prior beliefs using inverse optimization
by: Junca, Mauricio, et al.
Published: (2025)
by: Junca, Mauricio, et al.
Published: (2025)
Early predicting of hospital admission using machine learning algorithms: Priority queues approach
by: Antczak, Jakub, et al.
Published: (2026)
by: Antczak, Jakub, et al.
Published: (2026)
PADAM: Parallel averaged Adam reduces the error for stochastic optimization in scientific machine learning
by: Jentzen, Arnulf, et al.
Published: (2025)
by: Jentzen, Arnulf, et al.
Published: (2025)
Data augmentation for machine learning of chemical process flowsheets
by: Balhorn, Lukas Schulze, et al.
Published: (2023)
by: Balhorn, Lukas Schulze, et al.
Published: (2023)
On characterizing optimal learning trajectories in a class of learning problems
by: Befekadu, Getachew K
Published: (2025)
by: Befekadu, Getachew K
Published: (2025)
Distributed optimization: designed for federated learning
by: Guo, Wenyou, et al.
Published: (2025)
by: Guo, Wenyou, et al.
Published: (2025)
Exploring the non-convexity in machine learning using quantum-inspired optimization
by: Kumar, Kandula Eswara Sai, et al.
Published: (2026)
by: Kumar, Kandula Eswara Sai, et al.
Published: (2026)
Revealing design archetypes and flexibility in e-molecule import pathways using Modeling to Generate Alternatives and interpretable machine learning
by: Kchaou, Mahdi, et al.
Published: (2025)
by: Kchaou, Mahdi, et al.
Published: (2025)
Robust support vector machines via conic optimization
by: Cepeda, Valentina, et al.
Published: (2024)
by: Cepeda, Valentina, et al.
Published: (2024)
A survey on secure decentralized optimization and learning
by: Liu, Changxin, et al.
Published: (2024)
by: Liu, Changxin, et al.
Published: (2024)
The impact of machine learning forecasting on strategic decision-making for Bike Sharing Systems
by: Angelelli, Enrico, et al.
Published: (2026)
by: Angelelli, Enrico, et al.
Published: (2026)
Stochastic set-valued optimization and its application to robust learning
by: Giovannelli, Tommaso, et al.
Published: (2026)
by: Giovannelli, Tommaso, et al.
Published: (2026)
Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning
by: Chen, Paula, et al.
Published: (2023)
by: Chen, Paula, et al.
Published: (2023)
Manifold learning and optimization using tangent space proxies
by: Robinett, Ryan A., et al.
Published: (2025)
by: Robinett, Ryan A., et al.
Published: (2025)
A learning-based mathematical programming formulation for the automatic configuration of optimization solvers
by: Iommazzo, Gabriele, et al.
Published: (2024)
by: Iommazzo, Gabriele, et al.
Published: (2024)
An adaptively inexact first-order method for bilevel optimization with application to hyperparameter learning
by: Salehi, Mohammad Sadegh, et al.
Published: (2023)
by: Salehi, Mohammad Sadegh, et al.
Published: (2023)
PolyFormer: learning efficient reformulations for scalable optimization under complex physical constraints
by: Wen, Yilin, et al.
Published: (2026)
by: Wen, Yilin, et al.
Published: (2026)
A learning-based approach to stochastic optimal control under reach-avoid constraint
by: Ni, Tingting, et al.
Published: (2024)
by: Ni, Tingting, et al.
Published: (2024)
Adaptive multi-gradient methods for quasiconvex vector optimization and applications to multi-task learning
by: Minh, Nguyen Anh, et al.
Published: (2024)
by: Minh, Nguyen Anh, et al.
Published: (2024)
Iteratively reweighted kernel machines efficiently learn sparse functions
by: Zhu, Libin, et al.
Published: (2025)
by: Zhu, Libin, et al.
Published: (2025)
A successive approximation method in functional spaces for hierarchical optimal control problems and its application to learning
by: Befekadu, Getachew K.
Published: (2024)
by: Befekadu, Getachew K.
Published: (2024)
Delayed Momentum Aggregation: Communication-efficient Byzantine-robust Federated Learning with Partial Participation
by: Otsuka, Kaoru, et al.
Published: (2025)
by: Otsuka, Kaoru, et al.
Published: (2025)
Optimal service resource management strategy for IoT-based health information system considering value co-creation of users
by: Fang, Ji, et al.
Published: (2022)
by: Fang, Ji, et al.
Published: (2022)
On improving generalization in a class of learning problems with the method of small parameters for weakly-controlled optimal gradient systems
by: Befekadu, Getachew K.
Published: (2024)
by: Befekadu, Getachew K.
Published: (2024)
Enhancing supply chain security with automated machine learning
by: Wang, Haibo, et al.
Published: (2024)
by: Wang, Haibo, et al.
Published: (2024)
Smart energy management: process structure-based hybrid neural networks for optimal scheduling and economic predictive control in integrated systems
by: Wu, Long, et al.
Published: (2024)
by: Wu, Long, et al.
Published: (2024)
Robotic warehousing operations: a learn-then-optimize approach to large-scale neighborhood search
by: Barnhart, Cynthia, et al.
Published: (2024)
by: Barnhart, Cynthia, et al.
Published: (2024)
Graph neural networks for the prediction of molecular structure-property relationships
by: Rittig, Jan G., et al.
Published: (2022)
by: Rittig, Jan G., et al.
Published: (2022)
Generative modeling using evolved quantum Boltzmann machines
by: Wilde, Mark M.
Published: (2025)
by: Wilde, Mark M.
Published: (2025)
Learning to optimize: A tutorial for continuous and mixed-integer optimization
by: Chen, Xiaohan, et al.
Published: (2024)
by: Chen, Xiaohan, et al.
Published: (2024)
A physics-informed Bayesian optimization method for rapid development of electrical machines
by: Asef, Pedram, et al.
Published: (2025)
by: Asef, Pedram, et al.
Published: (2025)
Deep learning-driven scheduling algorithm for a single machine problem minimizing the total tardiness
by: Bouška, Michal, et al.
Published: (2024)
by: Bouška, Michal, et al.
Published: (2024)
MathOptAI.jl: Embed trained machine learning predictors into JuMP models
by: Dowson, Oscar, et al.
Published: (2025)
by: Dowson, Oscar, et al.
Published: (2025)
Continuous-time reinforcement learning for optimal switching over multiple regimes
by: Huang, Yijie, et al.
Published: (2025)
by: Huang, Yijie, et al.
Published: (2025)
A simple uniformly optimal method without line search for convex optimization
by: Li, Tianjiao, et al.
Published: (2023)
by: Li, Tianjiao, et al.
Published: (2023)
Parameter-free Clipped Gradient Descent Meets Polyak
by: Takezawa, Yuki, et al.
Published: (2024)
by: Takezawa, Yuki, et al.
Published: (2024)
Similar Items
-
Laguerre geometry for optimization of gridshell with specified force distribution
by: Kabaki, Kohei, et al.
Published: (2025) -
Non-parametric structural shape optimization of piecewise developable surfaces using discrete differential geometry
by: Ohsaki, Makoto, et al.
Published: (2024) -
Robust portfolio optimization for recommender systems considering uncertainty of estimated statistics
by: Yanagi, Tomoya, et al.
Published: (2024) -
Common pitfalls to avoid while using multiobjective optimization in machine learning
by: Akhter, Junaid, et al.
Published: (2024) -
Apprenticeship learning with prior beliefs using inverse optimization
by: Junca, Mauricio, et al.
Published: (2025)