📰 ICML 2016 — accepted papers

ICML 2016 is the 2016 edition of the International Conference on Machine Learning (ICML). OpenAlex lists 83 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.

Most cited papers

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

1. CryptoNets: applying neural networks to encrypted data with high throughput and accuracy ↗Nathan Dowlin, Ran Gilad-Bachrach, Kim Laine et al.1,228 citations
2. Meta-learning with memory-augmented neural networks ↗Adam Santoro, Sergey Bartunov, Matthew Botvinick et al.1,121 citations
3. Train faster, generalize better: stability of stochastic gradient descent ↗Moritz Hardt, Benjamin Recht, Yoram Singer364 citations
4. 33rd International Conference on Machine Learning, ICML 2016 ↗Jelena Luketina, Mathias Berglund, Klaus Greff et al.161 citations
5. A kernelized stein discrepancy for goodness-of-fit tests ↗Qiang Liu, Jason D. Lee, Michael I. Jordan142 citations
6. Towards Automatically-Tuned Neural Networks ↗Hector Mendoza, Aaron Klein, Matthias Feurer et al.129 citations
7. PD-sparse: a primal and dual sparse approach to extreme multiclass and multilabel classification ↗Ian En-Hsu Yen, Xiangru Huang, Kai Zhong et al.121 citations
8. PHOG: probabilistic model for code ↗Pavol Bielik, Veselin Raychev, Martin Vechev101 citations
9. Persistent RNNs: stashing recurrent weights on-chip ↗Gregory Diamos, Shubho Sengupta, Bryan Catanzaro et al.65 citations
10. Learning end-to-end video classification with rank-pooling ↗Basura Fernando, Stephen Gould58 citations

All accepted papers (83)

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

1. CryptoNets: applying neural networks to encrypted data with high throughput and accuracy ↗Nathan Dowlin, Ran Gilad-Bachrach, Kim Laine et al.1,228 citations
2. Meta-learning with memory-augmented neural networks ↗Adam Santoro, Sergey Bartunov, Matthew Botvinick et al.1,121 citations
3. Train faster, generalize better: stability of stochastic gradient descent ↗Moritz Hardt, Benjamin Recht, Yoram Singer364 citations
4. 33rd International Conference on Machine Learning, ICML 2016 ↗Jelena Luketina, Mathias Berglund, Klaus Greff et al.161 citations
5. A kernelized stein discrepancy for goodness-of-fit tests ↗Qiang Liu, Jason D. Lee, Michael I. Jordan142 citations
6. Towards Automatically-Tuned Neural Networks ↗Hector Mendoza, Aaron Klein, Matthias Feurer et al.129 citations
7. PD-sparse: a primal and dual sparse approach to extreme multiclass and multilabel classification ↗Ian En-Hsu Yen, Xiangru Huang, Kai Zhong et al.121 citations
8. PHOG: probabilistic model for code ↗Pavol Bielik, Veselin Raychev, Martin Vechev101 citations
9. Persistent RNNs: stashing recurrent weights on-chip ↗Gregory Diamos, Shubho Sengupta, Bryan Catanzaro et al.65 citations
10. Learning end-to-end video classification with rank-pooling ↗Basura Fernando, Stephen Gould58 citations
11. Isotonic hawkes processes ↗Yichen Wang, Bo Xie, Nan Du et al.45 citations
12. Adaptive sampling for SGD by exploiting side information ↗Siddharth Gopal39 citations
13. Efficient multi-instance learning for activity recognition from time series data using an auto-regressive hidden Markov model ↗Xinze Guan, Raviv Raich, Weng‐Keen Wong36 citations
14. Estimating structured vector autoregressive models ↗Igor Melnyk, Arindam Banerjee35 citations
15. Low-rank matrix approximation with stability ↗Dongsheng Li, Chao Chen, Qin Lv et al.35 citations
16. Efficient private empirical risk minimization for high-dimensional learning ↗Shiva Prasad Kasiviswanathan, Hongxia Jin34 citations
17. Robust principal component analysis with side information ↗Kai-Yang Chiang, Cho‐Jui Hsieh, Inderjit S. Dhillon32 citations
18. A distributed variational inference framework for unifying parallel sparse Gaussian process regression models ↗Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low31 citations
19. Conditional bernoulli mixtures for multi-label classification ↗Cheng Li, Bingyu Wang, Virgil Pavlu et al.31 citations
20. Speeding up k-means by approximating Euclidean distances via block vectors ↗Thomas Bottesch, Thomas Bühler, Markus Kächele30 citations
21. A comparative analysis and study of multiview CNN models for joint object categorization and pose estimation ↗Mohamed Elhoseiny, Tarek El-Gaaly, Amr Bakry et al.29 citations
22. Learning Population-Level Diffusions with Generative RNNs ↗Tatsunori Hashimoto, David Kenneth Gifford, Tommi Jaakkola28 citations
23. ForecastICU: a prognostic decision support system for timely prediction of intensive care unit admission ↗Jinsung Yoon, Ahmed M. Alaa, Scott B. Hu et al.27 citations
24. Linking losses for density ratio and class-probability estimation ↗Aditya Krishna Menon, Cheng Soon Ong27 citations
25. The information-theoretic requirements of subspace clustering with missing data ↗Daniel Pimentel-Alarcón, Robert D. Nowak27 citations

See all 83 papers in ICML 2016 — accepted papers →

📄 Papers with our summary in our library (1)

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

1. Unsupervised Deep Embedding for Clustering AnalysisInternational Conference on Machine Learning (ICML)Junyuan Xie, Ross Girshick, Ali Farhadi2016 · 222 citations

📚 Fields

🎭Arts and Humanities (1)🖥️Computer Science (1)

🧑‍🔬 Top authors

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

🏛️ Top institutions

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

🎓University of WashingtonSeattle · United States1 work here🏢MetaMenlo Park · United States1 work here

works and citations from OpenAlex and our library.

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