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"

26 / 26 papers shown

Title
Privacy-Preserving Model and Preprocessing Verification for Machine Learning Wenbiao Li Anisa Halimi Xiaoqian Jiang Jaideep Vaidya Erman Ayday AAML 77 0 0 14 Jan 2025
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels Erjian Guo Zicheng Wang Zhen Zhao Luping Zhou NoLa 116 0 0 12 Jan 2025
Multi-Label Bayesian Active Learning with Inter-Label Relationships Yuanyuan Qi Jueqing Lu Xiaohao Yang Joanne Enticott Lan Du 119 0 0 26 Nov 2024
Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels Curtis G. Northcutt Tailin Wu Isaac L. Chuang NoLa 34 157 0 04 May 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 257 4,612 0 10 Nov 2016
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys Pratik Chaudhari A. Choromańska Stefano Soatto Yann LeCun Carlo Baldassi C. Borgs J. Chayes Levent Sagun R. Zecchina ODL 82 769 0 06 Nov 2016
Toward Implicit Sample Noise Modeling: Deviation-driven Matrix Factorization Guang-He Lee Shao-Wen Yang Shou-de Lin 18 2 0 28 Oct 2016
Mollifying Networks Çağlar Gülçehre Marcin Moczulski Francesco Visin Yoshua Bengio 38 46 0 17 Aug 2016
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 77 2,000 0 14 Jun 2016
Robust Probabilistic Modeling with Bayesian Data Reweighting Yixin Wang A. Kucukelbir David M. Blei OOD NoLa 32 12 0 13 Jun 2016
Training Region-based Object Detectors with Online Hard Example Mining Abhinav Shrivastava Abhinav Gupta Ross B. Girshick ObjD 119 2,411 0 12 Apr 2016
A Variational Analysis of Stochastic Gradient Algorithms Stephan Mandt Matthew D. Hoffman David M. Blei 36 157 0 08 Feb 2016
Active Sampler: Light-weight Accelerator for Complex Data Analytics at Scale Jinyang Gao H. V. Jagadish Beng Chin Ooi 37 18 0 12 Dec 2015
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.3K 192,638 0 10 Dec 2015
Variance Reduction in SGD by Distributed Importance Sampling Guillaume Alain Alex Lamb Chinnadhurai Sankar Aaron Courville Yoshua Bengio FedML 44 198 0 20 Nov 2015
Online Batch Selection for Faster Training of Neural Networks I. Loshchilov Frank Hutter ODL 62 299 0 19 Nov 2015
What Objective Does Self-paced Learning Indeed Optimize? Deyu Meng Qian Zhao Lu Jiang 53 77 0 19 Nov 2015
Stochastic Gradient Made Stable: A Manifold Propagation Approach for Large-Scale Optimization Yadong Mu Wei Liu Wei Fan 45 33 0 28 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 198 19,448 0 09 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 736 149,474 0 22 Dec 2014
Variational Tempering Stephan Mandt James McInerney Farhan Abrol Rajesh Ranganath David M. Blei BDL 46 55 0 07 Nov 2014
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 541 13,395 0 25 Aug 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 138 738 0 19 Mar 2014
No More Pesky Learning Rates Tom Schaul Sixin Zhang Yann LeCun 77 477 0 06 Jun 2012
Bayesian Active Learning for Classification and Preference Learning N. Houlsby Ferenc Huszár Zoubin Ghahramani M. Lengyel 61 901 0 24 Dec 2011
Natural Language Processing (almost) from Scratch R. Collobert Jason Weston Léon Bottou Michael Karlen Koray Kavukcuoglu Pavel P. Kuksa 121 7,711 0 02 Mar 2011