English

A note on using performance and data profilesfor training algorithms

Optimization and Control 2021-05-31 v1 Performance
Authors: Margherita Porcelli , Philippe L. Toint
View on arXiv ↗ PDF ↗

Abstract

It is shown how to use the performance and data profile benchmarking tools to improve algorithms' performance. An illustration for the BFO derivative-free optimizer suggests that the obtained gains are potentially significant.

Keywords

optimization

Cite

@article{arxiv.1711.09407,
  title  = {A note on using performance and data profilesfor training algorithms},
  author = {Margherita Porcelli and Philippe L. Toint},
  journal= {arXiv preprint arXiv:1711.09407},
  year   = {2021}
}

Comments

8 pages, 4 tables, 4 figures

Related papers

View all related →
Mathematical Software · Computer Science
Benchmarking Optimization Software with Performance Profiles
Elizabeth D. Dolan, Jorge J. Moré
2007-05-23
Optimization and Control · Mathematics
Exploiting problem structure in derivative free optimization
Margherita Porcelli, Philippe L. Toint
2021-01-13
Machine Learning · Statistics
The Potential Benefits of Filtering Versus Hyper-Parameter Optimization
Michael R. Smith, Tony Martinez, Christophe Giraud-Carrier
2014-03-14
Neural and Evolutionary Computing · Computer Science
Using Affine Combinations of BBOB Problems for Performance Assessment
Diederick Vermetten, Furong Ye, Carola Doerr
2023-03-09
Optimization and Control · Mathematics
Nested Performance Profiles for Benchmarking Software
Rasoul Hekmati, Hanieh Mirhajianmoghadam
2020-01-31
Programming Languages · Computer Science
Profile Guided Optimization without Profiles: A Machine Learning Approach
Nadav Rotem, Chris Cummins
2022-01-05
Machine Learning · Computer Science
Using More Data to Speed-up Training Time
Shai Shalev-Shwartz, Ohad Shamir, Eran Tromer
2011-06-16
Machine Learning · Computer Science
Practical tradeoffs between memory, compute, and performance in learned optimizers
Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan +1
2022-07-19
Machine Learning · Computer Science
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing
Jesus A. De Loera, Jamie Haddock, Anna Ma, Deanna Needell
2019-07-30
Optimization and Control · Mathematics
Best practices for comparing optimization algorithms
Vahid Beiranvand, Warren Hare, Yves Lucet
2017-09-26
Machine Learning · Statistics
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
Bernd Bischl, Martin Binder, Michel Lang, Tobias Pielok +8
2021-11-29
Machine Learning · Computer Science
Bayesian Optimization for Iterative Learning
Vu Nguyen, Sebastian Schulze, Michael A Osborne
2021-01-19
Machine Learning · Statistics
Benchmarking Simulation-Based Inference
Jan-Matthis Lueckmann, Jan Boelts, David S. Greenberg, Pedro J. Gonçalves +1
2021-04-12
Machine Learning · Computer Science
How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers
Yuanhao Xiong, Xuanqing Liu, Li-Cheng Lan, Yang You +2
2020-10-21
Machine Learning · Computer Science
Bayesian Optimization for Selecting Efficient Machine Learning Models
Lidan Wang, Franck Dernoncourt, Trung Bui
2020-08-04
Performance · Computer Science
From Profiling to Optimization: Unveiling the Profile Guided Optimization
Bingxin Liu, Yinghui Huang, Jianhua Gao, Jianjun Shi +3
2025-07-23
Machine Learning · Statistics
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria +4
2020-04-21
Machine Learning · Computer Science
No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models
Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini +1
2023-11-15
Machine Learning · Computer Science
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice
Li Yang, Abdallah Shami
2022-10-06
Other Computer Science · Computer Science
Parameter-Free Deterministic Global Search with Central Force Optimization
Richard A. Formato
2010-05-31
Machine Learning · Computer Science
A Field Guide to Federated Optimization
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi +49
2021-07-16
Software Engineering · Computer Science
How to "DODGE" Complex Software Analytics?
Amritanshu Agrawal, Wei Fu, Di Chen, Xipeng Shen +1
2019-12-03
Machine Learning · Computer Science
Hyperparameter Optimisation with Early Termination of Poor Performers
Dobromir Marinov, Daniel Karapetyan
2019-08-08
Distributed, Parallel, and Cluster Computing · Computer Science
dPRO: A Generic Profiling and Optimization System for Expediting Distributed DNN Training
Hanpeng Hu, Chenyu Jiang, Yuchen Zhong, Yanghua Peng +4
2022-05-19
Optimization and Control · Mathematics
Two-timescale Derivative Free Optimization for Performative Prediction with Markovian Data
Haitong Liu, Qiang Li, Hoi-To Wai
2024-05-24