Online Batch Selection for Faster Training of Neural Networks

19 November 2015

Papers citing "Online Batch Selection for Faster Training of Neural Networks"

50 / 139 papers shown

Title
Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift Yijun Dong Yuege Xie Rachel A. Ward OOD 12 0 0 04 Oct 2022
To Store or Not? Online Data Selection for Federated Learning with Limited Storage Chen Gong Zhenzhe Zheng Yunfeng Shao Bingshuai Li Fan Wu Guihai Chen 29 15 0 01 Sep 2022
Efficient NLP Model Finetuning via Multistage Data Filtering Ouyang Xu S. Ansari F. Lin Yangfeng Ji 27 2 0 28 Jul 2022
Adaptive Second Order Coresets for Data-efficient Machine Learning Omead Brandon Pooladzandi David Davini Baharan Mirzasoleiman 14 62 0 28 Jul 2022
Prioritized Training on Points that are Learnable, Worth Learning, and Not Yet Learnt Sören Mindermann J. Brauner Muhammed Razzak Mrinank Sharma Andreas Kirsch ... Benedikt Höltgen Aidan N. Gomez Adrien Morisot Sebastian Farquhar Y. Gal 55 148 0 14 Jun 2022
Does Interference Exist When Training a Once-For-All Network? Jordan Shipard Arnold Wiliem Clinton Fookes 19 0 0 20 Apr 2022
Q-TART: Quickly Training for Adversarial Robustness and in-Transferability Madan Ravi Ganesh S. Y. Sekeh Jason J. Corso AAML 21 0 0 14 Apr 2022
FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients Jaemin Shin Yuanchun Li Yunxin Liu Sung-Ju Lee FedML 17 73 0 05 Jan 2022
How Important is Importance Sampling for Deep Budgeted Training? Eric Arazo Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness 20 7 0 27 Oct 2021
Large Batch Experience Replay Thibault Lahire M. Geist Emmanuel Rachelson OffRL 48 13 0 04 Oct 2021
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining Weizhe Hua Yichi Zhang Chuan Guo Zhiru Zhang G. E. Suh OOD 39 15 0 29 Sep 2021
Instance-wise Hard Negative Example Generation for Contrastive Learning in Unpaired Image-to-Image Translation Weilun Wang Wen-gang Zhou Jianmin Bao Dong Chen Houqiang Li SSL 23 81 0 10 Aug 2021
A Tale Of Two Long Tails Daniel D'souza Zach Nussbaum Chirag Agarwal Sara Hooker 29 22 0 27 Jul 2021
When does loss-based prioritization fail? Nie Hu Xinyu Hu Rosanne Liu Sara Hooker J. Yosinski 255 8 0 16 Jul 2021
Prioritized training on points that are learnable, worth learning, and not yet learned (workshop version) Sören Mindermann Muhammed Razzak Winnie Xu Andreas Kirsch Mrinank Sharma Adrien Morisot Aidan N. Gomez Sebastian Farquhar J. Brauner Y. Gal 22 6 0 06 Jul 2021
Curriculum generation using Autoencoder based continuous optimization Dipankar Sarkar Mukur Gupta 17 0 0 16 Jun 2021
Churn Reduction via Distillation Heinrich Jiang Harikrishna Narasimhan Dara Bahri Andrew Cotter Afshin Rostamizadeh 27 15 0 04 Jun 2021
Combining resampling and reweighting for faithful stochastic optimization Jing An Lexing Ying 9 1 0 31 May 2021
AutoSampling: Search for Effective Data Sampling Schedules Ming-hui Sun Hao Dou Baopu Li Lei Cui Junjie Yan Wanli Ouyang 34 6 0 28 May 2021
One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning Chaosheng Dong Xiaojie Jin Weihao Gao Yijia Wang Hongyi Zhang Xiang Wu Jianchao Yang Xiaobing Liu 28 5 0 27 Apr 2021
Stochastic Reweighted Gradient Descent Ayoub El Hanchi D. Stephens 11 8 0 23 Mar 2021
Variance Reduced Training with Stratified Sampling for Forecasting Models Yucheng Lu Youngsuk Park Lifan Chen Bernie Wang Christopher De Sa Dean Phillips Foster AI4TS 38 17 0 02 Mar 2021
Statistical Measures For Defining Curriculum Scoring Function Vinu Sankar Sadasivan A. Dasgupta 14 2 0 27 Feb 2021
Efficient Reinforcement Learning in Resource Allocation Problems Through Permutation Invariant Multi-task Learning D. Cai Shiau Hong Lim L. Wynter 17 3 0 18 Feb 2021
Locally Adaptive Label Smoothing for Predictive Churn Dara Bahri Heinrich Jiang NoLa 35 8 0 09 Feb 2021
FairBatch: Batch Selection for Model Fairness Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh VLM 6 128 0 03 Dec 2020
Unsupervised Difficulty Estimation with Action Scores Octavio Arriaga Matias Valdenegro-Toro FAtt 10 1 0 23 Nov 2020
Optimal Client Sampling for Federated Learning Wenlin Chen Samuel Horváth Peter Richtárik FedML 30 190 0 26 Oct 2020
A Survey on Curriculum Learning Xin Wang Yudong Chen Wenwu Zhu SyDa 32 22 0 25 Oct 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics Swabha Swayamdipta Roy Schwartz Nicholas Lourie Yizhong Wang Hannaneh Hajishirzi Noah A. Smith Yejin Choi 32 429 0 22 Sep 2020
Margin-Based Regularization and Selective Sampling in Deep Neural Networks Berry Weinstein Shai Fine Y. Hel-Or MQ 14 2 0 13 Sep 2020
Which Strategies Matter for Noisy Label Classification? Insight into Loss and Uncertainty Wonyoung Shin Jung-Woo Ha Shengzhe Li Yongwoo Cho Hoyean Song Sunyoung Kwon NoLa 6 9 0 14 Aug 2020
Monocular Real-Time Volumetric Performance Capture Ruilong Li Yuliang Xiu Shunsuke Saito Zeng Huang Kyle Olszewski Hao Li 3DH 121 93 0 28 Jul 2020
Distractor-Aware Neuron Intrinsic Learning for Generic 2D Medical Image Classifications Lijun Gong Kai Ma Yefeng Zheng 6 14 0 20 Jul 2020
Adaptive Task Sampling for Meta-Learning Chenghao Liu Zhihao Wang Doyen Sahoo Yuan Fang Anton van den Hengel S. Hoi 20 54 0 17 Jul 2020
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay Scott Fujimoto D. Meger Doina Precup 13 56 0 12 Jul 2020
STADB: A Self-Thresholding Attention Guided ADB Network for Person Re-identification Bo Jiang Sheng Wang Tianlin Li A. Zheng OOD 31 1 0 07 Jul 2020
DynNet: Physics-based neural architecture design for linear and nonlinear structural response modeling and prediction S. S. Eshkevari Martin Takávc S. Pakzad Majid Jahani AI4CE 8 14 0 03 Jul 2020
Multi-Precision Policy Enforced Training (MuPPET): A precision-switching strategy for quantised fixed-point training of CNNs A. Rajagopal D. A. Vink Stylianos I. Venieris C. Bouganis MQ 16 14 0 16 Jun 2020
Rethinking preventing class-collapsing in metric learning with margin-based losses Elad Levi Tete Xiao Xiaolong Wang Trevor Darrell 14 13 0 09 Jun 2020
Graph Learning with Loss-Guided Training Eliav Buchnik E. Cohen 16 1 0 31 May 2020
Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation A. Krishnan Mahashweta Das M. Bendre Hao Yang Hari Sundaram 16 64 0 21 May 2020
Stochastic batch size for adaptive regularization in deep network optimization Kensuke Nakamura Stefano Soatto Byung-Woo Hong ODL 19 6 0 14 Apr 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 46 1,928 0 11 Apr 2020
No Regret Sample Selection with Noisy Labels H. Song N. Mitsuo S. Uchida D. Suehiro NoLa 27 5 0 06 Mar 2020
Using Wavelets to Analyze Similarities in Image-Classification Datasets Roozbeh Yousefzadeh 21 0 0 24 Feb 2020
Distributionally Robust Deep Learning using Hardness Weighted Sampling Lucas Fidon Michael Aertsen Thomas Deprest Doaa Emam Frédéric Guffens ... Andrew Melbourne Sébastien Ourselin Jan Deprest Georg Langs Tom Kamiel Magda Vercauteren OOD 22 10 0 08 Jan 2020
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection Hwanjun Song Minseok Kim Sundong Kim Jae-Gil Lee 19 15 0 19 Nov 2019
Selective sampling for accelerating training of deep neural networks Berry Weinstein Shai Fine Y. Hel-Or 11 3 0 16 Nov 2019
Accelerating Deep Learning by Focusing on the Biggest Losers Angela H. Jiang Daniel L.-K. Wong Giulio Zhou D. Andersen J. Dean ... Gauri Joshi M. Kaminsky M. Kozuch Zachary Chase Lipton Padmanabhan Pillai 11 118 0 02 Oct 2019