:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Dunbar, Oliver R. A., Nelsen, Nicholas H., Mutic, Maya
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computation
Online Access:	https://arxiv.org/abs/2407.00584
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Error Bounds for Learning with Vector-Valued Random Features
by: Lanthaler, Samuel, et al.
Published: (2023)

Operator Learning Using Random Features: A Tool for Scientific Computing
by: Nelsen, Nicholas H., et al.
Published: (2024)

Bilevel optimization for learning hyperparameters: Application to solving PDEs and inverse problems with Gaussian processes
by: Nelsen, Nicholas H., et al.
Published: (2025)

Operator learning meets inverse problems: A probabilistic perspective
by: Nelsen, Nicholas H., et al.
Published: (2025)

Optimizing Emotion Recognition with Wearable Sensor Data: Unveiling Patterns in Body Movements and Heart Rate through Random Forest Hyperparameter Tuning
by: Nur, Zikri Kholifah, et al.
Published: (2024)

Hyperparameter Loss Surfaces Are Simple Near their Optima
by: Lourie, Nicholas, et al.
Published: (2025)

Improved Random Features for Dot Product Kernels
by: Wacker, Jonas, et al.
Published: (2022)

Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features
by: Bombari, Simone, et al.
Published: (2024)

Nesterov Acceleration for Ensemble Kalman Inversion and Variants
by: Vernon, Sydney, et al.
Published: (2025)

Algorithmic Capabilities of Random Transformers
by: Zhong, Ziqian, et al.
Published: (2024)

Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch
by: Ferreira, Fabio, et al.
Published: (2026)

Exploring the Optimized Value of Each Hyperparameter in Various Gradient Descent Algorithms
by: Chen, Abel C. H.
Published: (2022)

Benchmarking Randomized Optimization Algorithms on Binary, Permutation, and Combinatorial Problem Landscapes
by: Odeyemi, Jethro, et al.
Published: (2025)

Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization
by: Qin, Zhen, et al.
Published: (2023)

Feature Importance Guided Random Forest Learning with Simulated Annealing Based Hyperparameter Tuning
by: Balasubramanian, Kowshik, et al.
Published: (2025)

Controllable Feature Whitening for Hyperparameter-Free Bias Mitigation
by: Cho, Yooshin, et al.
Published: (2025)

On Randomized Algorithms in Online Strategic Classification
by: Hutton, Chase, et al.
Published: (2026)

Generalized Random Direction Newton Algorithms for Stochastic Optimization
by: Pachal, Soumen, et al.
Published: (2026)

Toward Routing River Water in Land Surface Models with Recurrent Neural Networks
by: Lima, Mauricio, et al.
Published: (2024)

Learning Algorithm Hyperparameters for Fast Parametric Convex Optimization
by: Sambharya, Rajiv, et al.
Published: (2024)

Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
by: Liu, Brian, et al.
Published: (2024)

Generative Bayesian Hyperparameter Tuning
by: Lopes, Hedibert, et al.
Published: (2025)

Bregman Conditional Random Fields: Sequence Labeling with Parallelizable Inference Algorithms
by: Corro, Caio, et al.
Published: (2025)

An operator learning perspective on parameter-to-observable maps
by: Huang, Daniel Zhengyu, et al.
Published: (2024)

Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selection
by: Cygert, Sebastian, et al.
Published: (2024)

Manifold Random Features
by: Parashar, Ananya, et al.
Published: (2026)

Overtuning in Hyperparameter Optimization
by: Schneider, Lennart, et al.
Published: (2025)

Enhanced Liver Tumor Detection in CT Images Using 3D U-Net and Bat Algorithm for Hyperparameter Optimization
by: Ghorbani, Nastaran, et al.
Published: (2025)

Optimizing Feature Selection with Genetic Algorithms: A Review of Methods and Applications
by: Taha, Zhila Yaseen, et al.
Published: (2024)

A short tour of operator learning theory: Convergence rates, statistical limits, and open questions
by: Brugiapaglia, Simone, et al.
Published: (2026)

Tuning the Tuner: Introducing Hyperparameter Optimization for Auto-Tuning
by: Willemsen, Floris-Jan, et al.
Published: (2025)

Interim Report on Human-Guided Adaptive Hyperparameter Optimization with Multi-Fidelity Sprints
by: Kamfonas, Michael
Published: (2025)

Random Feature Spiking Neural Networks
by: Gollwitzer, Maximilian, et al.
Published: (2025)

The Interplay of Statistics and Noisy Optimization: Learning Linear Predictors with Random Data Weights
by: Clara, Gabriel, et al.
Published: (2025)

Random-Effects Algorithm for Random Objects in Metric Spaces
by: Matabuena, Marcos, et al.
Published: (2026)

Decentralized Kernel Ridge Regression Based on Data-Dependent Random Feature
by: Yang, Ruikai, et al.
Published: (2024)

Robust and Communication-Efficient Federated Domain Adaptation via Random Features
by: Feng, Zhanbo, et al.
Published: (2023)

Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement Learning
by: Bai, Hui, et al.
Published: (2024)

VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization
by: Chatzimparmpas, Angelos, et al.
Published: (2020)

Stein Random Feature Regression
by: Warren, Houston, et al.
Published: (2024)