Benchmarking Deep AUROC Optimization: Loss Functions and Algorithmic Choices

27 March 2022

Papers citing "Benchmarking Deep AUROC Optimization: Loss Functions and Algorithmic Choices"

22 / 22 papers shown

Title
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization Guanghui Wang Minghao Yang Lijun Zhang Tianbao Yang 62 22 0 02 Jul 2021
Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery Zhengyang Wang Meng Liu Youzhi Luo Zhao Xu Yaochen Xie ... Lei Cai Q. Qi Zhuoning Yuan Tianbao Yang Shuiwang Ji 69 101 0 02 Dec 2020
Optimal Algorithms for Convex Nested Stochastic Composite Optimization Zhe Zhang Guanghui Lan 65 30 0 19 Nov 2020
Benchmarking Deep Learning Interpretability in Time Series Predictions Aya Abdelsalam Ismail Mohamed K. Gunady H. C. Bravo Soheil Feizi XAI AI4TS FAtt 47 171 0 26 Oct 2020
A Patient-Centric Dataset of Images and Metadata for Identifying Melanomas Using Clinical Context V. Rotemberg N. Kurtansky B. Betz‐Stablein L. Caffery E. Chousakos ... George Shih A. Stratigos P. Tschandl Jochen Weber H. Soyer 51 408 0 07 Aug 2020
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers Robin M. Schmidt Frank Schneider Philipp Hennig ODL 73 165 0 03 Jul 2020
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao Colin Wei Adrien Gaidon Nikos Arechiga Tengyu Ma 107 1,600 0 18 Jun 2019
Strategies for Pre-training Graph Neural Networks Weihua Hu Bowen Liu Joseph Gomes Marinka Zitnik Percy Liang Vijay S. Pande J. Leskovec SSL AI4CE 110 1,401 0 29 May 2019
On Symmetric Losses for Learning from Corrupted Labels Nontawat Charoenphakdee Jongyeong Lee Masashi Sugiyama NoLa 54 105 0 27 Jan 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison Jeremy Irvin Pranav Rajpurkar M. Ko Yifan Yu Silviana Ciurea-Ilcus ... D. Larson C. Langlotz Bhavik Patel M. Lungren A. Ng 110 2,591 0 21 Jan 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 232 7,638 0 01 Oct 2018
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 670 131,414 0 12 Jun 2017
The Marginal Value of Adaptive Gradient Methods in Machine Learning Ashia Wilson Rebecca Roelofs Mitchell Stern Nathan Srebro Benjamin Recht ODL 56 1,029 0 23 May 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 582 7,441 0 04 Apr 2017
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 328 1,826 0 02 Mar 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 760 36,781 0 25 Aug 2016
Benchmarking Deep Reinforcement Learning for Continuous Control Yan Duan Xi Chen Rein Houthooft John Schulman Pieter Abbeel OffRL 79 1,693 0 22 Apr 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,814 0 10 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.7K 150,006 0 22 Dec 2014
Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions Mengdi Wang Ethan X. Fang Han Liu 93 264 0 14 Nov 2014
One-Pass AUC Optimization Wei Gao Rong Jin Shenghuo Zhu Zhi Zhou 98 185 0 07 May 2013
On the Consistency of AUC Pairwise Optimization Wei Gao Zhi Zhou 117 124 0 03 Aug 2012