hyperparameter optimization

Revisiting Learning Rate Control AutoML 2025 Scalable Acceleration for Classification-Based Derivative-Free Optimization AAAI 2025 SEARA: An Automated Approach for Obtaining Optimal Retrievers EMNLP 2025 Searching for the Most Human-like Emergent Language EMNLP 2025 Temporal Scaling Law for Large Language Models EMNLP 2025 Towards Precise Scaling Laws for Video Diffusion Transformers CVPR 2025 ULTHO: Ultra-Lightweight yet Efficient Hyperparameter Optimization in Deep Reinforcement Learning ICCV 2025 XAutoLM: Efficient Fine-Tuning of Language Models via Meta-Learning and AutoML EMNLP 2025 A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data NeurIPS 2024 ADOPT: Modified Adam Can Converge with Any β_2 with the Optimal Rate NeurIPS 2024 Aequitas Flow: Streamlining Fair ML Experimentation JMLR 2024 AMLB: an AutoML Benchmark JMLR 2024 An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness NeurIPS 2024 An Algorithmic Framework for the Optimization of Deep Neural Networks Architectures and Hyperparameters JMLR 2024 Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting NeurIPS 2024 A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization ICML 2024 AutoLoRa: An Automated Robust Fine-Tuning Framework ICLR 2024 Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal NeurIPS 2024 Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO IJCAI 2024 Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis ICLR 2024 Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference NeurIPS 2024 Derivatives of Stochastic Gradient Descent in parametric optimization NeurIPS 2024 Efficient Hyperparameter Optimization with Adaptive Fidelity Identification CVPR 2024 FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent ICLR 2024 FlexiBO: A Decoupled Cost-Aware Multi-objective Optimization Approach for Deep Neural Networks (Abstract Reprint) AAAI 2024