Dropout Training as Adaptive Regularization

4 July 2013

Papers citing "Dropout Training as Adaptive Regularization"

50 / 87 papers shown

Title
Analytic theory of dropout regularization Francesco Mori Francesca Mignacco 34 0 0 12 May 2025
Neuroplasticity in Artificial Intelligence -- An Overview and Inspirations on Drop In & Out Learning Yupei Li M. Milling Björn Schuller AI4CE 107 0 0 27 Mar 2025
Random Forest Autoencoders for Guided Representation Learning Adrien Aumon Shuang Ni Myriam Lizotte Guy Wolf Kevin R. Moon Jake S. Rhodes 67 0 0 18 Feb 2025
Beyond Self-Consistency: Loss-Balanced Perturbation-Based Regularization Improves Industrial-Scale Ads Ranking Ilqar Ramazanli Hamid Eghbalzadeh Xiaoyi Liu Yang Wang Jiaxiang Fu Kaushik Rangadurai Sem Park Bo Long Xue Feng 51 0 0 05 Feb 2025
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 91 1 0 25 Nov 2024
Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem Simon Segert 32 0 0 18 Nov 2023
On The Impact of Machine Learning Randomness on Group Fairness Prakhar Ganesh Hong Chang Martin Strobel Reza Shokri FaML 36 30 0 09 Jul 2023
Generalized equivalences between subsampling and ridge regularization Pratik V. Patil Jin-Hong Du 39 5 0 29 May 2023
Dropout Regularization in Extended Generalized Linear Models based on Double Exponential Families Benedikt Lutke Schwienhorst Lucas Kock David J. Nott Nadja Klein 24 1 0 11 May 2023
Evaluating the Robustness of Machine Reading Comprehension Models to Low Resource Entity Renaming Clemencia Siro T. Ajayi 26 2 0 06 Apr 2023
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators Malte J. Rasch C. Mackin Manuel Le Gallo An Chen A. Fasoli ... P. Narayanan H. Tsai G. Burr Abu Sebastian Vijay Narayanan 13 83 0 16 Feb 2023
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability Chengtai Cao Fan Zhou Yurou Dai Jianping Wang Kunpeng Zhang AAML 24 28 0 21 Dec 2022
Data-driven Science and Machine Learning Methods in Laser-Plasma Physics Andreas Döpp C. Eberle S. Howard F. Irshad Jinpu Lin M. Streeter AI4CE 32 63 0 30 Nov 2022
Domain Adaptation under Missingness Shift Helen Zhou Sivaraman Balakrishnan Zachary Chase Lipton 27 8 0 03 Nov 2022
Noise Injection as a Probe of Deep Learning Dynamics Noam Levi I. Bloch M. Freytsis T. Volansky 40 2 0 24 Oct 2022
Data-Efficient Augmentation for Training Neural Networks Tian Yu Liu Baharan Mirzasoleiman 16 7 0 15 Oct 2022
Over-the-Air Split Machine Learning in Wireless MIMO Networks YuZhi Yang Zhaoyang Zhang Yuqing Tian Zhaohui Yang Chongwen Huang C. Zhong Kai‐Kit Wong 26 23 0 07 Oct 2022
Over-the-Air Federated Learning with Privacy Protection via Correlated Additive Perturbations Jialing Liao Zheng Chen Erik G. Larsson 25 12 0 05 Oct 2022
Frequency Dropout: Feature-Level Regularization via Randomized Filtering Mobarakol Islam Ben Glocker OOD 35 6 0 20 Sep 2022
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective Chanwoo Park Sangdoo Yun Sanghyuk Chun AAML 21 32 0 21 Aug 2022
Invariant Structure Learning for Better Generalization and Causal Explainability Yunhao Ge Sercan Ö. Arik Jinsung Yoon Ao Xu Laurent Itti Tomas Pfister OOD CML 34 2 0 13 Jun 2022
A Survey on Dropout Methods and Experimental Verification in Recommendation Yong Li Weizhi Ma C. L. Philip Chen Hao Fei Yiqun Liu Shaoping Ma Yue Yang 33 9 0 05 Apr 2022
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning Soufiane Hayou Bo He Gintare Karolina Dziugaite 37 2 0 22 Oct 2021
Federated Dropout -- A Simple Approach for Enabling Federated Learning on Resource Constrained Devices Dingzhu Wen Ki-Jun Jeon Kaibin Huang FedML 70 90 0 30 Sep 2021
How Does Mixup Help With Robustness and Generalization? Linjun Zhang Zhun Deng Kenji Kawaguchi Amirata Ghorbani James Zou AAML 27 244 0 09 Oct 2020
Explicit Regularisation in Gaussian Noise Injections A. Camuto M. Willetts Umut Simsekli Stephen J. Roberts Chris Holmes 25 55 0 14 Jul 2020
Xiaomingbot: A Multilingual Robot News Reporter Runxin Xu Jun Cao Mingxuan Wang Jiaze Chen Hao Zhou ... Xiang Yin Xijin Zhang Songcheng Jiang Yuxuan Wang Lei Li 23 11 0 12 Jul 2020
Graph Random Neural Network for Semi-Supervised Learning on Graphs Wenzheng Feng Jie Zhang Yuxiao Dong Yu Han Huanbo Luan Qian Xu Qiang Yang Evgeny Kharlamov Jie Tang 26 387 0 22 May 2020
Dropout: Explicit Forms and Capacity Control R. Arora Peter L. Bartlett Poorya Mianjy Nathan Srebro 64 37 0 06 Mar 2020
Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation Chuteng Zhou Prad Kadambi Matthew Mattina P. Whatmough 19 35 0 14 Jan 2020
Empirical Studies on the Properties of Linear Regions in Deep Neural Networks Xiao Zhang Dongrui Wu 21 38 0 04 Jan 2020
Continuous Dropout Xu Shen Xinmei Tian Tongliang Liu Fang Xu Dacheng Tao 17 64 0 28 Nov 2019
Medi-Care AI: Predicting Medications From Billing Codes via Robust Recurrent Neural Networks Deyin Liu Lin Wu Xue Li 37 17 0 14 Nov 2019
Post-synaptic potential regularization has potential Enzo Tartaglione Daniele Perlo Marco Grangetto BDL AAML 27 6 0 19 Jul 2019
Dimensionality compression and expansion in Deep Neural Networks Stefano Recanatesi M. Farrell Madhu S. Advani Timothy Moore Guillaume Lajoie E. Shea-Brown 20 72 0 02 Jun 2019
Orthogonal Deep Neural Networks Kui Jia Shuai Li Yuxin Wen Tongliang Liu Dacheng Tao 34 132 0 15 May 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 25 109 0 09 May 2019
Survey of Dropout Methods for Deep Neural Networks Alex Labach Hojjat Salehinejad S. Valaee 27 149 0 25 Apr 2019
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers Kui Jia Jiehong Lin Mingkui Tan Dacheng Tao 3DV 25 32 0 25 Apr 2019
A Selective Overview of Deep Learning Jianqing Fan Cong Ma Yiqiao Zhong BDL VLM 36 136 0 10 Apr 2019
Effective and Efficient Dropout for Deep Convolutional Neural Networks Shaofeng Cai Jinyang Gao Gang Chen Beng Chin Ooi Wei Wang Meihui Zhang BDL 18 53 0 06 Apr 2019
Cyberthreat Detection from Twitter using Deep Neural Networks Nuno Dionísio Fernando Alves Pedro M. Ferreira A. Bessani 27 76 0 01 Apr 2019
Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model Wenhui Cui Yanling Liu Yuxing Li Meng-Hao Guo Yiming Li Xiuli Li Tianle Wang Xiangzhu Zeng Chuyang Ye 18 174 0 04 Mar 2019
Batch Virtual Adversarial Training for Graph Convolutional Networks Zhijie Deng Yinpeng Dong Jun Zhu GNN 28 62 0 25 Feb 2019
Ising-Dropout: A Regularization Method for Training and Compression of Deep Neural Networks Hojjat Salehinejad S. Valaee 26 30 0 07 Feb 2019
Foothill: A Quasiconvex Regularization for Edge Computing of Deep Neural Networks Mouloud Belbahri Eyyub Sari Sajad Darabi V. Nia MQ 21 1 0 18 Jan 2019
Implicit Regularization of Stochastic Gradient Descent in Natural Language Processing: Observations and Implications Deren Lei Zichen Sun Yijun Xiao William Yang Wang 33 14 0 01 Nov 2018
Applying Deep Learning To Airbnb Search Malay Haldar Mustafa Abdool Prashant Ramanathan Tao Xu Shulin Yang ... Qing Zhang Nick Barrow-Williams B. Turnbull Brendan M. Collins Thomas Legrand DML 23 83 0 22 Oct 2018
An ETF view of Dropout regularization Dor Bank Raja Giryes 8 4 0 14 Oct 2018
Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis M. A. Nabian Hadi Meidani PINN AI4CE 21 57 0 11 Oct 2018