Improved Training Speed, Accuracy, and Data Utilization Through Loss Function Optimization

27 May 2019

Papers citing "Improved Training Speed, Accuracy, and Data Utilization Through Loss Function Optimization"

35 / 35 papers shown

Title
GANetic Loss for Generative Adversarial Networks with a Focus on Medical Applications S. Akhmedova Nils Körber GAN MedIm 37 0 0 07 Jun 2024
Next Generation Loss Function for Image Classification S. Akhmedova Nils Körber VLM 32 2 0 19 Apr 2024
Evolving Loss Functions for Specific Image Augmentation Techniques Brandon Morgan Dean Frederick Hougen 35 0 0 09 Apr 2024
Fast and Efficient Local Search for Genetic Programming Based Loss Function Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang 46 2 0 01 Mar 2024
Predicting O-GlcNAcylation Sites in Mammalian Proteins with Transformers and RNNs Trained with a New Loss Function Pedro Seber 27 2 0 27 Feb 2024
Neural Loss Function Evolution for Large-Scale Image Classifier Convolutional Neural Networks Brandon Morgan Dean Frederick Hougen 14 2 0 30 Jan 2024
Meta-tuning Loss Functions and Data Augmentation for Few-shot Object Detection B. Demirel Orhun Bugra Baran R. G. Cinbis 39 10 0 24 Apr 2023
Online Loss Function Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang 35 5 0 30 Jan 2023
Efficient Activation Function Optimization through Surrogate Modeling G. Bingham Risto Miikkulainen 16 2 0 13 Jan 2023
Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities Brian Bartoldson B. Kailkhura Davis W. Blalock 31 47 0 13 Oct 2022
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning Christian Raymond Qi Chen Bing Xue Mengjie Zhang FedML 29 11 0 19 Sep 2022
Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning Momin Abbas Quan-Wu Xiao Lisha Chen Pin-Yu Chen Tianyi Chen 21 78 0 08 Jun 2022
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions Zhaoqi Leng Mingxing Tan Chenxi Liu E. D. Cubuk Xiaojie Shi Shuyang Cheng Drago Anguelov 18 134 0 26 Apr 2022
Generating meta-learning tasks to evolve parametric loss for classification learning Zhaoyang Hai Xiabi Liu Yuchen Ren N. Q. Soomro 30 0 0 20 Nov 2021
GCCN: Global Context Convolutional Network Ali Hamdi Flora D. Salim D. Kim 12 1 0 22 Oct 2021
Signature-Graph Networks Ali Hamdi Flora D. Salim D. Kim Xiaojun Chang 21 1 0 22 Oct 2021
Problem Learning: Towards the Free Will of Machines Yongfeng Zhang FaML 21 2 0 01 Sep 2021
Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks Jun Shu Deyu Meng Zongben Xu 26 6 0 06 Jul 2021
Evolving parametrized Loss for Image Classification Learning on Small Datasets Zhaoyang Hai Xiabi Liu 16 0 0 15 Mar 2021
Population-Based Evolution Optimizes a Meta-Learning Objective Kevin Frans Olaf Witkowski 25 5 0 11 Mar 2021
Searching for Robustness: Loss Learning for Noisy Classification Tasks Boyan Gao Henry Gouk Timothy M. Hospedales OOD NoLa 33 18 0 27 Feb 2021
Evolving GAN Formulations for Higher Quality Image Synthesis Santiago Gonzalez Mohak Kant Risto Miikkulainen GAN 23 4 0 17 Feb 2021
Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search Peidong Liu Gengwei Zhang Bochao Wang Hang Xu Xiaodan Liang Yong-jia Jiang Zhenguo Li 13 28 0 09 Feb 2021
Effective Regularization Through Loss-Function Metalearning Santiago Gonzalez Risto Miikkulainen 26 5 0 02 Oct 2020
Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons, Recommendations and Challenges Aritz D. Martinez Javier Del Ser Esther Villar-Rodriguez E. Osaba Javier Poyatos Siham Tabik Daniel Molina Francisco Herrera 35 26 0 09 Aug 2020
flexgrid2vec: Learning Efficient Visual Representations Vectors Ali Hamdi D. Kim Flora D. Salim SSL GNN 30 7 0 30 Jul 2020
Discovering Parametric Activation Functions G. Bingham Risto Miikkulainen ODL 12 70 0 05 Jun 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 55 1,935 0 11 Apr 2020
Meta-learning curiosity algorithms Ferran Alet Martin Schneider Tomas Lozano-Perez L. Kaelbling 25 63 0 11 Mar 2020
Evolutionary Optimization of Deep Learning Activation Functions G. Bingham William Macke Risto Miikkulainen ODL 19 50 0 17 Feb 2020
Regularized Evolutionary Population-Based Training J. Liang Santiago Gonzalez H. Shahrzad Risto Miikkulainen 14 9 0 11 Feb 2020
FastGAE: Scalable Graph Autoencoders with Stochastic Subgraph Decoding Guillaume Salha-Galvan Romain Hennequin Jean-Baptiste Remy Manuel Moussallam Michalis Vazirgiannis GNN BDL 23 6 0 05 Feb 2020
Optimizing Loss Functions Through Multivariate Taylor Polynomial Parameterization Santiago Gonzalez Risto Miikkulainen 16 9 0 31 Jan 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012