Do Better ImageNet Models Transfer Better?

23 May 2018

Papers citing "Do Better ImageNet Models Transfer Better?"

50 / 639 papers shown

Title
MixPath: A Unified Approach for One-shot Neural Architecture Search Xiangxiang Chu Shun Lu Xudong Li Bo-Wen Zhang 11 21 0 16 Jan 2020
ScaIL: Classifier Weights Scaling for Class Incremental Learning Eden Belouadah Adrian Daniel Popescu CLL 9 78 0 16 Jan 2020
Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation Fajie Yuan Xiangnan He Alexandros Karatzoglou Liguang Zhang 11 0 0 13 Jan 2020
Deeper Insights into Weight Sharing in Neural Architecture Search Yuge Zhang Zejun Lin Junyan Jiang Quanlu Zhang Yujing Wang Hui Xue Chen Zhang Yaming Yang 18 48 0 06 Jan 2020
Inter- and Intra-domain Knowledge Transfer for Related Tasks in Deep Character Recognition Nishai Kooverjee Steven D. James Terence L van Zyl 13 4 0 02 Jan 2020
Recognizing Instagram Filtered Images with Feature De-stylization Zhe Wu Zuxuan Wu Bharat Singh L. Davis 8 20 0 30 Dec 2019
Big Transfer (BiT): General Visual Representation Learning Alexander Kolesnikov Lucas Beyer Xiaohua Zhai J. Puigcerver Jessica Yung Sylvain Gelly N. Houlsby MQ 12 1,183 0 24 Dec 2019
Multimodal Prediction based on Graph Representations Í. C. Dourado S. Tabbone Ricardo da S. Torres 11 0 0 21 Dec 2019
Measuring Dataset Granularity Yin Cui Zeqi Gu D. Mahajan L. V. D. van der Maaten Serge J. Belongie Ser-Nam Lim 16 13 0 21 Dec 2019
A Broader Study of Cross-Domain Few-Shot Learning Yunhui Guo Noel Codella Leonid Karlinsky James V. Codella John R. Smith Kate Saenko Tajana Simunic Rogerio Feris 23 45 0 16 Dec 2019
Targeted transfer learning to improve performance in small medical physics datasets M. Romero Y. Interian T. Solberg Gilmer Valdes OOD 17 47 0 14 Dec 2019
Robust Deep Graph Based Learning for Binary Classification Minxiang Ye V. Stanković L. Stanković Gene Cheung OOD 15 10 0 06 Dec 2019
Self-Supervised Learning of Video-Induced Visual Invariances Michael Tschannen Josip Djolonga Marvin Ritter Aravindh Mahendran Xiaohua Zhai N. Houlsby Sylvain Gelly Mario Lucic SSL 8 61 0 05 Dec 2019
Value-laden Disciplinary Shifts in Machine Learning Ravit Dotan S. Milli AILaw 17 47 0 03 Dec 2019
Transfer Learning in Visual and Relational Reasoning T. S. Jayram Vincent Marois Tomasz Kornuta V. Albouy Emre Sevgen A. Ozcan NAI OOD LRM 9 2 0 27 Nov 2019
"You might also like this model": Data Driven Approach for Recommending Deep Learning Models for Unknown Image Datasets Ameya Prabhu Riddhiman Dasgupta A. Sankaran Srikanth G. Tamilselvam Senthil Mani 8 0 0 26 Nov 2019
Optimizing Data Usage via Differentiable Rewards Xinyi Wang Hieu H. Pham Paul Michel Antonios Anastasopoulos J. Carbonell Graham Neubig 16 58 0 22 Nov 2019
Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels Lu Jiang Di Huang Mason Liu Weilong Yang NoLa 6 3 0 21 Nov 2019
AdaFilter: Adaptive Filter Fine-tuning for Deep Transfer Learning Yunhui Guo Yandong Li Liqiang Wang Tajana Simunic 19 41 0 21 Nov 2019
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks Katherine L. Hermann Ting Chen Simon Kornblith CVBM 11 21 0 20 Nov 2019
In-domain representation learning for remote sensing Maxim Neumann André Susano Pinto Xiaohua Zhai N. Houlsby SSL 13 62 0 15 Nov 2019
Self-training with Noisy Student improves ImageNet classification Qizhe Xie Minh-Thang Luong Eduard H. Hovy Quoc V. Le NoLa 13 2,357 0 11 Nov 2019
On Architectures for Including Visual Information in Neural Language Models for Image Description Marc Tanti Albert Gatt K. Camilleri VLM 22 2 0 09 Nov 2019
Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings Paul Bergmann Michael Fauser David Sattlegger C. Steger 17 650 0 06 Nov 2019
Evaluating Lottery Tickets Under Distributional Shifts Shrey Desai Hongyuan Zhan Ahmed Aly UQCV OOD 11 41 0 28 Oct 2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 59 19,391 0 23 Oct 2019
Extraction of Complex DNN Models: Real Threat or Boogeyman? B. Atli S. Szyller Mika Juuti Samuel Marchal Nadarajah Asokan MLAU MIACV 17 45 0 11 Oct 2019
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction Method Artur Jordão M. Lie V. H. C. Melo William Robson Schwartz 6 3 0 05 Oct 2019
An empirical study of pretrained representations for few-shot classification Tiago Ramalho Laura Vana-Gur P. Filzmoser VLM 9 6 0 03 Oct 2019
A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark Xiaohua Zhai J. Puigcerver A. Kolesnikov P. Ruyssen C. Riquelme ... Michael Tschannen Marcin Michalski Olivier Bousquet Sylvain Gelly N. Houlsby SSL 14 425 0 01 Oct 2019
Deep learning tools for the measurement of animal behavior in neuroscience Mackenzie W. Mathis Alexander Mathis 3DV VLM 17 311 0 30 Sep 2019
Towards Understanding the Transferability of Deep Representations Hong Liu Mingsheng Long Jianmin Wang Michael I. Jordan 14 25 0 26 Sep 2019
Deep Model Transferability from Attribution Maps Jie Song Yixin Chen Xinchao Wang Chengchao Shen Mingli Song 6 54 0 26 Sep 2019
Pretraining boosts out-of-domain robustness for pose estimation Alexander Mathis Thomas Biasi Steffen Schneider Mert Yüksekgönül Byron Rogers Matthias Bethge Mackenzie W. Mathis OOD 14 122 0 24 Sep 2019
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML Aniruddh Raghu M. Raghu Samy Bengio Oriol Vinyals 172 639 0 19 Sep 2019
Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs J. Kubilius Martin Schrimpf Kohitij Kar Ha Hong N. Majaj ... Kailyn Schmidt Aran Nayebi Daniel M. Bear Daniel L. K. Yamins J. DiCarlo 22 256 0 13 Sep 2019
Pretrained AI Models: Performativity, Mobility, and Change L. Varshney N. Keskar R. Socher 13 20 0 07 Sep 2019
Saccader: Improving Accuracy of Hard Attention Models for Vision Gamaleldin F. Elsayed Simon Kornblith Quoc V. Le VLM 25 70 0 20 Aug 2019
SCARLET-NAS: Bridging the Gap between Stability and Scalability in Weight-sharing Neural Architecture Search Xiangxiang Chu Bo-Wen Zhang Qingyuan Li Ruijun Xu Xudong Li 16 24 0 16 Aug 2019
How Does Learning Rate Decay Help Modern Neural Networks? Kaichao You Mingsheng Long Jianmin Wang Michael I. Jordan 12 4 0 05 Aug 2019
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions Matthew Faw Rajat Sen Karthikeyan Shanmugam C. Caramanis Sanjay Shakkottai 20 3 0 23 Jul 2019
MixConv: Mixed Depthwise Convolutional Kernels Mingxing Tan Quoc V. Le 19 374 0 22 Jul 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 16 1,416 0 16 Jul 2019
Introduction to Camera Pose Estimation with Deep Learning Yoli Shavit Ron Ferens 12 67 0 08 Jul 2019
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search Xiangxiang Chu Bo-Wen Zhang Ruijun Xu 11 331 0 03 Jul 2019
Fixing the train-test resolution discrepancy Hugo Touvron Andrea Vedaldi Matthijs Douze Hervé Jégou 10 420 0 14 Jun 2019
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers Ari S. Morcos Haonan Yu Michela Paganini Yuandong Tian 6 228 0 06 Jun 2019
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP Haonan Yu Sergey Edunov Yuandong Tian Ari S. Morcos 14 148 0 06 Jun 2019
When Does Label Smoothing Help? Rafael Müller Simon Kornblith Geoffrey E. Hinton UQCV 10 1,906 0 06 Jun 2019
DAWN: Dynamic Adversarial Watermarking of Neural Networks S. Szyller B. Atli Samuel Marchal Nadarajah Asokan MLAU AAML 11 176 0 03 Jun 2019