Title
Investigating performance of neural networks and gradient boosting models approximating microscopic traffic simulations in traffic optimization tasks P. Góra M. Brzeski Marcin Mo.zejko Arkadiusz Klemenko A. Kochanski 19 6 0 02 Dec 2018
Label-Noise Robust Generative Adversarial Networks Takuhiro Kaneko Yoshitaka Ushiku Tatsuya Harada NoLa 24 60 0 27 Nov 2018
Class-Distinct and Class-Mutual Image Generation with GANs Takuhiro Kaneko Yoshitaka Ushiku Tatsuya Harada 14 9 0 27 Nov 2018
Limited Gradient Descent: Learning With Noisy Labels Yi Sun Yan Tian Yiping Xu Jianxiang Li NoLa 35 13 0 20 Nov 2018
Deep Frank-Wolfe For Neural Network Optimization Leonard Berrada Andrew Zisserman M. P. Kumar ODL 21 40 0 19 Nov 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 28 117 0 17 Oct 2018
Detecting Memorization in ReLU Networks Edo Collins Siavash Bigdeli Sabine Süsstrunk 36 4 0 08 Oct 2018
A Practical Approach to Sizing Neural Networks Gerald Friedland A. Metere M. M. Krell 14 7 0 04 Oct 2018
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 47 192 0 02 Oct 2018
Improving the Generalization of Adversarial Training with Domain Adaptation Chuanbiao Song Kun He Liwei Wang J. Hopcroft AAML OOD 28 131 0 01 Oct 2018
Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter Lijun Wu Xu Tan Di He Fei Tian Tao Qin Jianhuang Lai Tie-Yan Liu 18 48 0 01 Sep 2018
Targeted Nonlinear Adversarial Perturbations in Images and Videos R. Rey-de-Castro H. Rabitz AAML 16 10 0 27 Aug 2018
Understanding training and generalization in deep learning by Fourier analysis Zhi-Qin John Xu AI4CE 24 92 0 13 Aug 2018
On the Spectral Bias of Neural Networks Nasim Rahaman A. Baratin Devansh Arpit Felix Dräxler Min Lin Fred Hamprecht Yoshua Bengio Aaron Courville 57 1,395 0 22 Jun 2018
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning Amy Zhang Nicolas Ballas Joelle Pineau CLL OffRL 30 177 0 20 Jun 2018
Insights on representational similarity in neural networks with canonical correlation Ari S. Morcos M. Raghu Samy Bengio DRL 32 432 0 14 Jun 2018
Baselines and a datasheet for the Cerema AWP dataset Ismaïla Seck Khouloud Dahmane Pierre Duthon Gaëlle Loosli 24 11 0 11 Jun 2018
Dimensionality-Driven Learning with Noisy Labels Xingjun Ma Yisen Wang Michael E. Houle Shuo Zhou S. Erfani Shutao Xia S. Wijewickrema James Bailey NoLa 35 425 0 07 Jun 2018
Investigating Label Noise Sensitivity of Convolutional Neural Networks for Fine Grained Audio Signal Labelling Rainer Kelz Gerhard Widmer NoLa 22 4 0 28 May 2018
Topological Data Analysis of Decision Boundaries with Application to Model Selection Karthikeyan N. Ramamurthy Kush R. Varshney Krishnan Mody 17 40 0 25 May 2018
Deep learning generalizes because the parameter-function map is biased towards simple functions Guillermo Valle Pérez Chico Q. Camargo A. Louis MLT AI4CE 18 226 0 22 May 2018
Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction Hongyuan Mei Sheng Zhang Kevin Duh Benjamin Van Durme 16 2 0 21 May 2018
On the Diachronic Stability of Irregularity in Inflectional Morphology Ryan Cotterell Christo Kirov Mans Hulden Jason Eisner 18 7 0 23 Apr 2018
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han Quanming Yao Xingrui Yu Gang Niu Miao Xu Weihua Hu Ivor Tsang Masashi Sugiyama NoLa 58 2,032 0 18 Apr 2018
Joint Optimization Framework for Learning with Noisy Labels Daiki Tanaka Daiki Ikami T. Yamasaki Kiyoharu Aizawa NoLa 39 703 0 30 Mar 2018
On the importance of single directions for generalization Ari S. Morcos David Barrett Neil C. Rabinowitz M. Botvinick 18 329 0 19 Mar 2018
Deep Component Analysis via Alternating Direction Neural Networks Calvin Murdock Ming-Fang Chang Simon Lucey BDL 27 20 0 16 Mar 2018
Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle Rana Ali Amjad Bernhard C. Geiger 35 196 0 27 Feb 2018
A Walk with SGD Chen Xing Devansh Arpit Christos Tsirigotis Yoshua Bengio 27 118 0 24 Feb 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 29 630 0 14 Feb 2018
A trans-disciplinary review of deep learning research for water resources scientists Chaopeng Shen AI4CE 33 682 0 06 Dec 2017
Deep Learning Scaling is Predictable, Empirically Joel Hestness Sharan Narang Newsha Ardalani G. Diamos Heewoo Jun Hassan Kianinejad Md. Mostofa Ali Patwary Yang Yang Yanqi Zhou 63 716 0 01 Dec 2017
Providing theoretical learning guarantees to Deep Learning Networks R. Mello M. D. Ferreira M. Ponti 28 6 0 28 Nov 2017
Three Factors Influencing Minima in SGD Stanislaw Jastrzebski Zachary Kenton Devansh Arpit Nicolas Ballas Asja Fischer Yoshua Bengio Amos Storkey 42 457 0 13 Nov 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 87 9,601 0 25 Oct 2017
High-dimensional dynamics of generalization error in neural networks Madhu S. Advani Andrew M. Saxe AI4CE 90 464 0 10 Oct 2017
Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Rates L. Smith Nicholay Topin AI4CE 25 519 0 23 Aug 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 308 2,892 0 15 Sep 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 308 5,842 0 08 Jul 2016