---
title: "ICML 2019 — accepted papers — Elamur Research"
description: "ICML 2019 — accepted papers: 1 paper in the Elamur Research library, with our summaries, ranked by citations."
canonical: "https://research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2019/"
---
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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.

[**154** papers in the proceedings](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2019/#works) · [**5,416** citations of these works](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2019/#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 ↗](http://proceedings.mlr.press/v97/chen19i/chen19i.pdf)**Xinyang Chen, Sinan Wang, Mingsheng Long et al.*242 citations*
2. **[Analyzing Federated Learning through an Adversarial Lens ↗](http://proceedings.mlr.press/v97/bhagoji19a/bhagoji19a.pdf)**Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal et al.*188 citations*
3. **[SELFIE: Refurbishing Unclean Samples for Robust Deep Learning ↗](http://proceedings.mlr.press/v97/song19b/song19b.pdf)**Hwanjun Song, Minseok Kim, Jae-Gil Lee*175 citations*
4. **[Invertible Residual Networks ↗](http://proceedings.mlr.press/v97/behrmann19a/behrmann19a.pdf)**Jens Behrmann, Will Grathwohl, Ricky T. Q. Chen et al.*161 citations*
5. **[On learning invariant representations for domain adaptation ↗](http://proceedings.mlr.press/v97/zhao19a/zhao19a.pdf)**Han Zhao, Rémi Tachet des Combes, Kun Zhang et al.*160 citations*
6. **[A Deep Reinforcement Learning Perspective on Internet Congestion Control ↗](http://proceedings.mlr.press/v97/jay19a/jay19a.pdf)**Nathan H. Jay, Noga H. Rotman, Brighten Godfrey et al.*152 citations*
7. **[Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers ↗](http://proceedings.mlr.press/v97/liu19b/liu19b.pdf)**Hong Liu, Mingsheng Long, Jianmin Wang et al.*147 citations*
8. **[Disentangled Graph Convolutional Networks ↗](http://proceedings.mlr.press/v97/ma19a/ma19a.pdf)**Jianxin Ma, Peng Cui, Kun Kuang et al.*119 citations*
9. **[COMIC: Multi-view Clustering Without Parameter Selection ↗](http://proceedings.mlr.press/v97/peng19a/peng19a.pdf)**Xi Peng, Zhenyu Huang, Jiancheng Lv et al.*118 citations*
10. **[MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets ↗](http://proceedings.mlr.press/v97/mattei19a/mattei19a.pdf)**Pierre‐Alexandre Mattei, Jes Frellsen*107 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 ↗](http://proceedings.mlr.press/v97/chen19i/chen19i.pdf)**Xinyang Chen, Sinan Wang, Mingsheng Long et al.*242 citations*
2. **[Analyzing Federated Learning through an Adversarial Lens ↗](http://proceedings.mlr.press/v97/bhagoji19a/bhagoji19a.pdf)**Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal et al.*188 citations*
3. **[SELFIE: Refurbishing Unclean Samples for Robust Deep Learning ↗](http://proceedings.mlr.press/v97/song19b/song19b.pdf)**Hwanjun Song, Minseok Kim, Jae-Gil Lee*175 citations*
4. **[Invertible Residual Networks ↗](http://proceedings.mlr.press/v97/behrmann19a/behrmann19a.pdf)**Jens Behrmann, Will Grathwohl, Ricky T. Q. Chen et al.*161 citations*
5. **[On learning invariant representations for domain adaptation ↗](http://proceedings.mlr.press/v97/zhao19a/zhao19a.pdf)**Han Zhao, Rémi Tachet des Combes, Kun Zhang et al.*160 citations*
6. **[A Deep Reinforcement Learning Perspective on Internet Congestion Control ↗](http://proceedings.mlr.press/v97/jay19a/jay19a.pdf)**Nathan H. Jay, Noga H. Rotman, Brighten Godfrey et al.*152 citations*
7. **[Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers ↗](http://proceedings.mlr.press/v97/liu19b/liu19b.pdf)**Hong Liu, Mingsheng Long, Jianmin Wang et al.*147 citations*
8. **[Disentangled Graph Convolutional Networks ↗](http://proceedings.mlr.press/v97/ma19a/ma19a.pdf)**Jianxin Ma, Peng Cui, Kun Kuang et al.*119 citations*
9. **[COMIC: Multi-view Clustering Without Parameter Selection ↗](http://proceedings.mlr.press/v97/peng19a/peng19a.pdf)**Xi Peng, Zhenyu Huang, Jiancheng Lv et al.*118 citations*
10. **[MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets ↗](http://proceedings.mlr.press/v97/mattei19a/mattei19a.pdf)**Pierre‐Alexandre Mattei, Jes Frellsen*107 citations*
11. **[Doubly robust joint learning for recommendation on data missing not at random ↗](http://proceedings.mlr.press/v97/wang19n/wang19n.pdf)**Xiaojie Wang, Rui Zhang, Yu Sun et al.*88 citations*
12. **[Optimal Auctions through Deep Learning ↗](http://proceedings.mlr.press/v97/duetting19a/duetting19a.pdf)**Paul Dütting, Zhe Feng, Harikrishna Narasimhan et al.*83 citations*
13. **[Graph U-Nets ↗](http://proceedings.mlr.press/v97/gao19a/gao19a.pdf)**Hongyang Gao, Shuiwang Ji*82 citations*
14. **[Concrete Autoencoders: Differentiable Feature Selection and Reconstruction. ↗](http://proceedings.mlr.press/v97/balin19a/balin19a.pdf)**Muhammed Fati̇h Balin, Abubakar Abid, James Zou*80 citations*
15. **[What is the Effect of Importance Weighting in Deep Learning ↗](http://proceedings.mlr.press/v97/byrd19a/byrd19a.pdf)**Jonathon Byrd, Zachary C. Lipton*77 citations*
16. **[Collaborative Channel Pruning for Deep Networks ↗](http://proceedings.mlr.press/v97/peng19c/peng19c.pdf)**Hanyu Peng, Jiaxiang Wu, Shifeng Chen et al.*76 citations*
17. **[DL2: Training and Querying Neural Networks with Logic. ↗](http://proceedings.mlr.press/v97/fischer19a/fischer19a.pdf)**Marc Fischer, Mislav Balunović, Dana Drachsler-Cohen et al.*68 citations*
18. **[Adversarial Examples Are a Natural Consequence of Test Error in Noise ↗](http://proceedings.mlr.press/v97/gilmer19a/gilmer19a.pdf)**Justin Gilmer, Nic Ford, Nicholas Carlini et al.*66 citations*
19. **[Circuit-GNN: Graph Neural Networks for Distributed Circuit Design ↗](http://proceedings.mlr.press/v97/zhang19e/zhang19e.pdf)**Zhang Guo, He Hao, Dina Katabi*66 citations*
20. **[Towards a Deep and Unified Understanding of Deep Neural Models in NLP ↗](http://proceedings.mlr.press/v97/guan19a/guan19a.pdf)**Chaoyu Guan, Xiting Wang, Quanshi Zhang et al.*64 citations*
21. **[HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving ↗](http://proceedings.mlr.press/v97/bansal19a/bansal19a.pdf)**Kshitij Bansal, Sarah M. Loos, Markus N. Rabe et al.*63 citations*
22. **[Efficient Training of BERT by Progressively Stacking ↗](http://proceedings.mlr.press/v97/gong19a/gong19a.pdf)**Linyuan Gong, Di He, Zhuohan Li et al.*62 citations*
23. **[Shallow-Deep Networks: Understanding and Mitigating Network Overthinking ↗](http://proceedings.mlr.press/v97/kaya19a/kaya19a.pdf)**Yiğitcan Kaya, Sanghyun Hong, Tudor Dumitraş*55 citations*
24. **[Unreproducible Research is Reproducible ↗](http://proceedings.mlr.press/v97/bouthillier19a/bouthillier19a.pdf)**Xavier Bouthillier, César Laurent, Pascal Vincent*54 citations*
25. **[A Framework for Bayesian Optimization in Embedded Subspaces ↗](http://proceedings.mlr.press/v97/nayebi19a/nayebi19a.pdf)**Amin Nayebi, Alexander Munteanu, Matthias Poloczek*51 citations*

[See all 154 papers in ICML 2019 — accepted papers →](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2019/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 Networks](https://md.research.elamur.ai/free/en/papers/tan-2019-efficientnet-rethinking-model-scaling-convolutional/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Mingxing Tan, Quoc V. Le*2019 · 5,416 citations*

## Fields

[Computer Science (1)](https://md.research.elamur.ai/free/en/shelves/computer-science/)

## Top authors

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

[🧑‍🔬**Quoc Viet Le**1 work here · 5,416 citations](https://md.research.elamur.ai/free/en/authors/quoc-viet-le/)

## Top institutions

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

[🏢**Google** Mountain View · United States 1 work here](https://md.research.elamur.ai/free/en/companies/google/)

works and citations from OpenAlex and our library.

- [← previous ICML 2009](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2009/)
- [next → ICML 2021](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2021/)
- [↑ back to ICML](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)