Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples

24 April 2017

Papers citing "Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples"

31 / 81 papers shown

Title
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics Swabha Swayamdipta Roy Schwartz Nicholas Lourie Yizhong Wang Hannaneh Hajishirzi Noah A. Smith Yejin Choi 54 429 0 22 Sep 2020
Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering Jingtao Ding Yuhan Quan Quanming Yao Yong Li Depeng Jin 19 97 0 07 Sep 2020
Salvage Reusable Samples from Noisy Data for Robust Learning Zeren Sun Xiansheng Hua Yazhou Yao Xiu-Shen Wei Guosheng Hu Jian Zhang NoLa 29 41 0 06 Aug 2020
Adaptive Task Sampling for Meta-Learning Chenghao Liu Zhihao Wang Doyen Sahoo Yuan Fang Kun Zhang Guosheng Lin 45 54 0 17 Jul 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 24 964 0 16 Jul 2020
Early-Learning Regularization Prevents Memorization of Noisy Labels Sheng Liu Jonathan Niles-Weed N. Razavian C. Fernandez‐Granda NoLa 36 557 0 30 Jun 2020
Learning Bounds for Risk-sensitive Learning Jaeho Lee Sejun Park Jinwoo Shin 25 46 0 15 Jun 2020
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels Jun Shu Qian Zhao Zengben Xu Deyu Meng NoLa 33 29 0 10 Jun 2020
Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation A. Krishnan Mahashweta Das M. Bendre Hao Yang Hari Sundaram 27 64 0 21 May 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 31 10 0 08 Jan 2020
Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning Han-Jia Ye Hong-You Chen De-Chuan Zhan Wei-Lun Chao 39 99 0 06 Jan 2020
Controllable and Progressive Image Extrapolation Yijun Li Lu Jiang Ming-Hsuan Yang 16 19 0 25 Dec 2019
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection Hwanjun Song Minseok Kim Sundong Kim Jae-Gil Lee 27 15 0 19 Nov 2019
Dice Loss for Data-imbalanced NLP Tasks Xiaoya Li Xiaofei Sun Yuxian Meng Junjun Liang Fei Wu Jiwei Li 50 569 0 07 Nov 2019
Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications Nicholas Carlini Ulfar Erlingsson Nicolas Papernot OOD OODD 26 62 0 29 Oct 2019
Learning Data Manipulation for Augmentation and Weighting Zhiting Hu Bowen Tan Ruslan Salakhutdinov Tom Michael Mitchell Eric Xing 29 116 0 28 Oct 2019
Imbalance Problems in Object Detection: A Review Kemal Oksuz Baris Can Cam Sinan Kalkan Emre Akbas ObjD 36 458 0 31 Aug 2019
Submodular Batch Selection for Training Deep Neural Networks K. J. Joseph R. VamshiTeja Krishnakant Singh V. Balasubramanian 15 23 0 20 Jun 2019
Training Data Subset Search with Ensemble Active Learning Kashyap Chitta J. Álvarez Elmar Haussmann C. Farabet 25 13 0 29 May 2019
Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning Xun Wang Xintong Han Weilin Huang Dengke Dong Matthew R. Scott 31 739 0 14 Apr 2019
On The Power of Curriculum Learning in Training Deep Networks Guy Hacohen D. Weinshall ODL 39 441 0 07 Apr 2019
IMAE for Noise-Robust Learning: Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude's Variance Matters Xinshao Wang Yang Hua Elyor Kodirov David Clifton N. Robertson NoLa 24 62 0 28 Mar 2019
Pedestrian Attribute Recognition: A Survey Tianlin Li Shaofei Zheng Rui Yang Aihua Zheng Zhe Chen Jin Tang Bin Luo CVBM 30 127 0 22 Jan 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 23 10 0 18 Dec 2018
An Empirical Study of Example Forgetting during Deep Neural Network Learning Mariya Toneva Alessandro Sordoni Rémi Tachet des Combes Adam Trischler Yoshua Bengio Geoffrey J. Gordon 48 715 0 12 Dec 2018
Theory of Curriculum Learning, with Convex Loss Functions D. Weinshall D. Amir 24 41 0 09 Dec 2018
Unsupervised Hard Example Mining from Videos for Improved Object Detection SouYoung Jin Aruni RoyChowdhury Huaizu Jiang Ashish Singh Aditya Prasad Deep Chakraborty Erik Learned-Miller ObjD 29 63 0 13 Aug 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 69 1,412 0 24 Mar 2018
Large-scale Cloze Test Dataset Created by Teachers Qizhe Xie Guokun Lai Zihang Dai Eduard H. Hovy ELM 30 73 0 09 Nov 2017
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 312 13,377 0 25 Aug 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 93 737 0 19 Mar 2014