Title
Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation D. Lu N. Polomac Iskra Gacheva E. Hattingen Jochen Triesch 18 18 0 17 Jun 2020
PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks Mojtaba Faramarzi Mohammad Amini Akilesh Badrinaaraayanan Vikas Verma A. Chandar AAML 34 31 0 14 Jun 2020
Are we done with ImageNet? Lucas Beyer Olivier J. Hénaff Alexander Kolesnikov Xiaohua Zhai Aaron van den Oord VLM 19 397 0 12 Jun 2020
Probably Approximately Correct Constrained Learning Luiz F. O. Chamon Alejandro Ribeiro 22 38 0 09 Jun 2020
Provable tradeoffs in adversarially robust classification Yan Sun Hamed Hassani David Hong Alexander Robey 23 53 0 09 Jun 2020
The Curious Case of Convex Neural Networks S. Sivaprasad Ankur Singh Naresh Manwani Vineet Gandhi 46 27 0 09 Jun 2020
Learning the gravitational force law and other analytic functions Atish Agarwala Abhimanyu Das Rina Panigrahy Qiuyi Zhang MLT 16 0 0 15 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 41 371 0 30 Apr 2020
Neural Additive Models: Interpretable Machine Learning with Neural Nets Rishabh Agarwal Levi Melnick Nicholas Frosst Xuezhou Zhang Ben Lengerich R. Caruana Geoffrey E. Hinton 46 405 0 29 Apr 2020
How to Teach DNNs to Pay Attention to the Visual Modality in Speech Recognition George Sterpu Christian Saam N. Harte 34 28 0 17 Apr 2020
Dataless Model Selection with the Deep Frame Potential Calvin Murdock Simon Lucey 38 6 0 30 Mar 2020
Analyzing Visual Representations in Embodied Navigation Tasks Erik Wijmans Julian Straub Dhruv Batra Irfan Essa Judy Hoffman Ari S. Morcos 19 2 0 12 Mar 2020
AL2: Progressive Activation Loss for Learning General Representations in Classification Neural Networks Majed El Helou Frederike Dumbgen Sabine Süsstrunk CLL AI4CE 30 2 0 07 Mar 2020
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 319 499 0 05 Mar 2020
Towards Noise-resistant Object Detection with Noisy Annotations Junnan Li Caiming Xiong R. Socher Guosheng Lin ObjD NoLa 62 28 0 03 Mar 2020
Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization S. Chatterjee ODL OOD 11 49 0 25 Feb 2020
Progressive Identification of True Labels for Partial-Label Learning Jiaqi Lv Miao Xu Lei Feng Gang Niu Xin Geng Masashi Sugiyama 19 177 0 19 Feb 2020
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima Zeke Xie Issei Sato Masashi Sugiyama ODL 28 17 0 10 Feb 2020
Importance-Driven Deep Learning System Testing Simos Gerasimou Hasan Ferit Eniser A. Sen Alper Çakan AAML VLM 30 98 0 09 Feb 2020
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study Jinlan Fu Pengfei Liu Qi Zhang Xuanjing Huang AI4CE 33 73 0 12 Jan 2020
Confidence Scores Make Instance-dependent Label-noise Learning Possible Antonin Berthon Bo Han Gang Niu Tongliang Liu Masashi Sugiyama NoLa 37 104 0 11 Jan 2020
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis Davood Karimi Haoran Dou Simon K. Warfield Ali Gholipour NoLa 24 535 0 05 Dec 2019
Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification Zhihui Zhu Xinyang Jiang Feng Zheng Xiao-Wei Guo Feiyue Huang Weishi Zheng Xing Sun 14 71 0 03 Dec 2019
Forecasting significant stock price changes using neural networks F. Kamalov AIFin 11 80 0 21 Nov 2019
Where is the Bottleneck of Adversarial Learning with Unlabeled Data? Jingfeng Zhang Bo Han Gang Niu Tongliang Liu Masashi Sugiyama 30 6 0 20 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 18 104 0 13 Nov 2019
Robust Training with Ensemble Consensus Jisoo Lee Sae-Young Chung NoLa 22 28 0 22 Oct 2019
A Closer Look at Data Bias in Neural Extractive Summarization Models Ming Zhong Danqing Wang Pengfei Liu Xipeng Qiu Xuanjing Huang 48 42 0 30 Sep 2019
Overparameterized Neural Networks Implement Associative Memory Adityanarayanan Radhakrishnan M. Belkin Caroline Uhler BDL 35 71 0 26 Sep 2019
Symmetric Cross Entropy for Robust Learning with Noisy Labels Yisen Wang Xingjun Ma Zaiyi Chen Yuan Luo Jinfeng Yi James Bailey NoLa 39 878 0 16 Aug 2019
Needles in Haystacks: On Classifying Tiny Objects in Large Images Nick Pawlowski Suvrat Bhooshan Nicolas Ballas F. Ciompi Ben Glocker M. Drozdzal 24 22 0 16 Aug 2019
Visualizing the PHATE of Neural Networks Scott A. Gigante Adam S. Charles Smita Krishnaswamy Gal Mishne 36 37 0 07 Aug 2019
Deep Gamblers: Learning to Abstain with Portfolio Theory Liu Ziyin Zhikang T. Wang Paul Pu Liang Ruslan Salakhutdinov Louis-Philippe Morency Masahito Ueda 23 110 0 29 Jun 2019
Effectiveness of Distillation Attack and Countermeasure on Neural Network Watermarking Ziqi Yang Hung Dang E. Chang AAML 27 34 0 14 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 58 482 0 12 Jun 2019
SGD on Neural Networks Learns Functions of Increasing Complexity Preetum Nakkiran Gal Kaplun Dimitris Kalimeris Tristan Yang Benjamin L. Edelman Fred Zhang Boaz Barak MLT 14 236 0 28 May 2019
Combating Label Noise in Deep Learning Using Abstention S. Thulasidasan Tanmoy Bhattacharya J. Bilmes Gopinath Chennupati J. Mohd-Yusof NoLa 22 177 0 27 May 2019
Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets Guy Hacohen Leshem Choshen D. Weinshall AI4TS OOD 8 56 0 26 May 2019
Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks Yaoyu Zhang Zhi-Qin John Xu Tao Luo Zheng Ma MLT AI4CE 33 38 0 24 May 2019
Curriculum Loss: Robust Learning and Generalization against Label Corruption Yueming Lyu Ivor W. Tsang NoLa 66 172 0 24 May 2019
Wasserstein Adversarial Regularization (WAR) on label noise Kilian Fatras B. Bushan Sylvain Lobry Rémi Flamary D. Tuia Nicolas Courty 19 24 0 08 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 A. Clifton N. Robertson NoLa 24 62 0 28 Mar 2019
Robust Inference via Generative Classifiers for Handling Noisy Labels Kimin Lee Sukmin Yun Kibok Lee Honglak Lee Bo-wen Li Jinwoo Shin NoLa 33 134 0 31 Jan 2019
Error Feedback Fixes SignSGD and other Gradient Compression Schemes Sai Praneeth Karimireddy Quentin Rebjock Sebastian U. Stich Martin Jaggi 21 493 0 28 Jan 2019
Stiffness: A New Perspective on Generalization in Neural Networks Stanislav Fort Pawel Krzysztof Nowak Stanislaw Jastrzebski S. Narayanan 21 94 0 28 Jan 2019
Robust Learning at Noisy Labeled Medical Images: Applied to Skin Lesion Classification Cheng Xue Qi Dou Xueying Shi Hao Chen Pheng Ann Heng NoLa 21 104 0 23 Jan 2019
Overfitting Mechanism and Avoidance in Deep Neural Networks Shaeke Salman Xiuwen Liu 9 139 0 19 Jan 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Tao Luo Yan Xiao Zheng Ma 14 503 0 19 Jan 2019
Generalization in Deep Networks: The Role of Distance from Initialization Vaishnavh Nagarajan J. Zico Kolter ODL 4 95 0 07 Jan 2019
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 46 715 0 12 Dec 2018