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ICML 2019 — accepted papers

ICML 2019 is the 2019 edition of the International Conference on Machine Learning (ICML). OpenAlex lists 154 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

 154papers in the proceedings 1work in our library 5,416citations of these works

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

  1. Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation ↗Xinyang Chen, Sinan Wang, Mingsheng Long et al.242 citations
  2. Analyzing Federated Learning through an Adversarial Lens ↗Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal et al.188 citations
  3. SELFIE: Refurbishing Unclean Samples for Robust Deep Learning ↗Hwanjun Song, Minseok Kim, Jae-Gil Lee175 citations
  4. Invertible Residual Networks ↗Jens Behrmann, Will Grathwohl, Ricky T. Q. Chen et al.161 citations
  5. On learning invariant representations for domain adaptation ↗Han Zhao, Rémi Tachet des Combes, Kun Zhang et al.160 citations
  6. A Deep Reinforcement Learning Perspective on Internet Congestion Control ↗Nathan H. Jay, Noga H. Rotman, Brighten Godfrey et al.152 citations
  7. Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers ↗Hong Liu, Mingsheng Long, Jianmin Wang et al.147 citations
  8. Disentangled Graph Convolutional Networks ↗Jianxin Ma, Peng Cui, Kun Kuang et al.119 citations
  9. COMIC: Multi-view Clustering Without Parameter Selection ↗Xi Peng, Zhenyu Huang, Jiancheng Lv et al.118 citations
  10. MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets ↗Pierre‐Alexandre Mattei, Jes Frellsen107 citations

All accepted papers (154)

The most cited first; 1 with our summary link to their page here, the others to the original.

  1. Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation ↗Xinyang Chen, Sinan Wang, Mingsheng Long et al.242 citations
  2. Analyzing Federated Learning through an Adversarial Lens ↗Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal et al.188 citations
  3. SELFIE: Refurbishing Unclean Samples for Robust Deep Learning ↗Hwanjun Song, Minseok Kim, Jae-Gil Lee175 citations
  4. Invertible Residual Networks ↗Jens Behrmann, Will Grathwohl, Ricky T. Q. Chen et al.161 citations
  5. On learning invariant representations for domain adaptation ↗Han Zhao, Rémi Tachet des Combes, Kun Zhang et al.160 citations
  6. A Deep Reinforcement Learning Perspective on Internet Congestion Control ↗Nathan H. Jay, Noga H. Rotman, Brighten Godfrey et al.152 citations
  7. Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers ↗Hong Liu, Mingsheng Long, Jianmin Wang et al.147 citations
  8. Disentangled Graph Convolutional Networks ↗Jianxin Ma, Peng Cui, Kun Kuang et al.119 citations
  9. COMIC: Multi-view Clustering Without Parameter Selection ↗Xi Peng, Zhenyu Huang, Jiancheng Lv et al.118 citations
  10. MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets ↗Pierre‐Alexandre Mattei, Jes Frellsen107 citations
  11. Doubly robust joint learning for recommendation on data missing not at random ↗Xiaojie Wang, Rui Zhang, Yu Sun et al.88 citations
  12. Optimal Auctions through Deep Learning ↗Paul Dütting, Zhe Feng, Harikrishna Narasimhan et al.83 citations
  13. Graph U-Nets ↗Hongyang Gao, Shuiwang Ji82 citations
  14. Concrete Autoencoders: Differentiable Feature Selection and Reconstruction. ↗Muhammed Fati̇h Balin, Abubakar Abid, James Zou80 citations
  15. What is the Effect of Importance Weighting in Deep Learning ↗Jonathon Byrd, Zachary C. Lipton77 citations
  16. Collaborative Channel Pruning for Deep Networks ↗Hanyu Peng, Jiaxiang Wu, Shifeng Chen et al.76 citations
  17. DL2: Training and Querying Neural Networks with Logic. ↗Marc Fischer, Mislav Balunović, Dana Drachsler-Cohen et al.68 citations
  18. Adversarial Examples Are a Natural Consequence of Test Error in Noise ↗Justin Gilmer, Nic Ford, Nicholas Carlini et al.66 citations
  19. Circuit-GNN: Graph Neural Networks for Distributed Circuit Design ↗Zhang Guo, He Hao, Dina Katabi66 citations
  20. Towards a Deep and Unified Understanding of Deep Neural Models in NLP ↗Chaoyu Guan, Xiting Wang, Quanshi Zhang et al.64 citations
  21. HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving ↗Kshitij Bansal, Sarah M. Loos, Markus N. Rabe et al.63 citations
  22. Efficient Training of BERT by Progressively Stacking ↗Linyuan Gong, Di He, Zhuohan Li et al.62 citations
  23. Shallow-Deep Networks: Understanding and Mitigating Network Overthinking ↗Yiğitcan Kaya, Sanghyun Hong, Tudor Dumitraş55 citations
  24. Unreproducible Research is Reproducible ↗Xavier Bouthillier, César Laurent, Pascal Vincent54 citations
  25. A Framework for Bayesian Optimization in Embedded Subspaces ↗Amin Nayebi, Alexander Munteanu, Matthias Poloczek51 citations

See all 154 papers in ICML 2019 — accepted papers →

 Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

  1. EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksInternational Conference on Machine Learning (ICML)Mingxing Tan, Quoc V. Le2019 · 5,416 citations

 Fields

Computer Science (1)

 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🧑‍🔬Quoc Viet Le1 work here · 5,416 citations

 Top institutions

Institutions on the bylines of its works here, by the number of works.

🏢GoogleMountain View · United States1 work here

works and citations from OpenAlex and our library.

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