Deep curriculum learning optimization
暂无分享,去创建一个
[1] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.
[2] B. Bonev. Feature Selection based on Information Theory , 2010 .
[3] D. Weinshall,et al. Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks , 2018, ICML.
[4] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[5] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[6] Matthijs Douze,et al. Fixing the train-test resolution discrepancy , 2019, NeurIPS.
[7] Lucas Beyer,et al. Big Transfer (BiT): General Visual Representation Learning , 2020, ECCV.
[8] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[9] Rajeev Kumar,et al. Receiver operating characteristic (ROC) curve for medical researchers , 2011, Indian pediatrics.
[10] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Henok Ghebrechristos,et al. Expediting Training Using Information Theory Based Patch Ordering Algorithm , 2018, 2018 International Conference on Computational Science and Computational Intelligence (CSCI).
[12] Oluwasanmi Koyejo,et al. Consistent Binary Classification with Generalized Performance Metrics , 2014, NIPS.
[13] Sotiris B. Kotsiantis,et al. Supervised Machine Learning: A Review of Classification Techniques , 2007, Informatica.
[14] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[15] Yoshua Bengio,et al. Random Search for Hyper-Parameter Optimization , 2012, J. Mach. Learn. Res..
[16] Jason Weston,et al. Curriculum learning , 2009, ICML '09.
[17] Bo Chen,et al. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications , 2017, ArXiv.
[18] Joan Bruna,et al. Intriguing properties of neural networks , 2013, ICLR.
[19] Michael W. Mahoney,et al. Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior , 2017, ArXiv.
[20] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[21] Quoc V. Le,et al. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks , 2019, ICML.
[22] M. N. Sulaiman,et al. A Review On Evaluation Metrics For Data Classification Evaluations , 2015 .
[23] Quoc V. Le,et al. Self-Training With Noisy Student Improves ImageNet Classification , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[25] Andrew F. Rex,et al. Maxwell's Demon, Entropy, Information, Computing , 1990 .
[26] C. V. Jawahar,et al. Cats and dogs , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[27] Jiawei Zhang,et al. Gradient Descent based Optimization Algorithms for Deep Learning Models Training , 2019, ArXiv.
[28] Djemel Ziou,et al. Image Quality Metrics: PSNR vs. SSIM , 2010, 2010 20th International Conference on Pattern Recognition.
[29] Mateu Sbert,et al. Information Theory Tools for Image Processing , 2014, Information Theory Tools for Image Processing.
[30] Kan Chen,et al. Billion-scale semi-supervised learning for image classification , 2019, ArXiv.
[31] Carlo Tomasi,et al. Image Similarity Using Mutual Information of Regions , 2004, ECCV.
[32] Wojciech Czarnecki,et al. On Loss Functions for Deep Neural Networks in Classification , 2017, ArXiv.
[33] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[34] Alex Graves,et al. Automated Curriculum Learning for Neural Networks , 2017, ICML.
[35] Samy Bengio,et al. Understanding deep learning requires rethinking generalization , 2016, ICLR.
[36] Vanya Avramova. Curriculum Learning with Deep Convolutional Neural Networks , 2015 .