---
title: "ICML 2016 — accepted papers — Elamur Research"
description: "ICML 2016 — 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/2016/"
---
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# 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.

[**83** papers in the proceedings](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2016/#works) · [**222** citations of these works](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2016/#works)

## 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 ↗](http://proceedings.mlr.press/v48/gilad-bachrach16.pdf)**Nathan Dowlin, Ran Gilad-Bachrach, Kim Laine et al.*1,228 citations*
2. **[Meta-learning with memory-augmented neural networks ↗](http://proceedings.mlr.press/v48/santoro16.pdf)**Adam Santoro, Sergey Bartunov, Matthew Botvinick et al.*1,121 citations*
3. **[Train faster, generalize better: stability of stochastic gradient descent ↗](http://jmlr.org/proceedings/papers/v48/hardt16.pdf)**Moritz Hardt, Benjamin Recht, Yoram Singer*364 citations*
4. **[33rd International Conference on Machine Learning, ICML 2016 ↗](https://research.aalto.fi/fi/publications/scalable-gradientbased-tuning-of-continuous-regularization-hyperparameters(42380b78-c7fe-476f-9321-24784d0e54ab).html)**Jelena Luketina, Mathias Berglund, Klaus Greff et al.*161 citations*
5. **[A kernelized stein discrepancy for goodness-of-fit tests ↗](http://proceedings.mlr.press/v48/liub16.pdf)**Qiang Liu, Jason D. Lee, Michael I. Jordan*142 citations*
6. **[Towards Automatically-Tuned Neural Networks ↗](http://proceedings.mlr.press/v64/mendoza_towards_2016.pdf)**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 ↗](http://proceedings.mlr.press/v48/yenb16.pdf)**Ian En-Hsu Yen, Xiangru Huang, Kai Zhong et al.*121 citations*
8. **[PHOG: probabilistic model for code ↗](http://proceedings.mlr.press/v48/bielik16.pdf)**Pavol Bielik, Veselin Raychev, Martin Vechev*101 citations*
9. **[Persistent RNNs: stashing recurrent weights on-chip ↗](http://proceedings.mlr.press/v48/diamos16.pdf)**Gregory Diamos, Shubho Sengupta, Bryan Catanzaro et al.*65 citations*
10. **[Learning end-to-end video classification with rank-pooling ↗](http://jmlr.org/proceedings/papers/v48/fernando16.pdf)**Basura Fernando, Stephen Gould*58 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 ↗](http://proceedings.mlr.press/v48/gilad-bachrach16.pdf)**Nathan Dowlin, Ran Gilad-Bachrach, Kim Laine et al.*1,228 citations*
2. **[Meta-learning with memory-augmented neural networks ↗](http://proceedings.mlr.press/v48/santoro16.pdf)**Adam Santoro, Sergey Bartunov, Matthew Botvinick et al.*1,121 citations*
3. **[Train faster, generalize better: stability of stochastic gradient descent ↗](http://jmlr.org/proceedings/papers/v48/hardt16.pdf)**Moritz Hardt, Benjamin Recht, Yoram Singer*364 citations*
4. **[33rd International Conference on Machine Learning, ICML 2016 ↗](https://research.aalto.fi/fi/publications/scalable-gradientbased-tuning-of-continuous-regularization-hyperparameters(42380b78-c7fe-476f-9321-24784d0e54ab).html)**Jelena Luketina, Mathias Berglund, Klaus Greff et al.*161 citations*
5. **[A kernelized stein discrepancy for goodness-of-fit tests ↗](http://proceedings.mlr.press/v48/liub16.pdf)**Qiang Liu, Jason D. Lee, Michael I. Jordan*142 citations*
6. **[Towards Automatically-Tuned Neural Networks ↗](http://proceedings.mlr.press/v64/mendoza_towards_2016.pdf)**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 ↗](http://proceedings.mlr.press/v48/yenb16.pdf)**Ian En-Hsu Yen, Xiangru Huang, Kai Zhong et al.*121 citations*
8. **[PHOG: probabilistic model for code ↗](http://proceedings.mlr.press/v48/bielik16.pdf)**Pavol Bielik, Veselin Raychev, Martin Vechev*101 citations*
9. **[Persistent RNNs: stashing recurrent weights on-chip ↗](http://proceedings.mlr.press/v48/diamos16.pdf)**Gregory Diamos, Shubho Sengupta, Bryan Catanzaro et al.*65 citations*
10. **[Learning end-to-end video classification with rank-pooling ↗](http://jmlr.org/proceedings/papers/v48/fernando16.pdf)**Basura Fernando, Stephen Gould*58 citations*
11. **[Isotonic hawkes processes ↗](http://proceedings.mlr.press/v48/wangg16.pdf)**Yichen Wang, Bo Xie, Nan Du et al.*45 citations*
12. **[Adaptive sampling for SGD by exploiting side information ↗](http://proceedings.mlr.press/v48/gopal16.pdf)**Siddharth Gopal*39 citations*
13. **[Efficient multi-instance learning for activity recognition from time series data using an auto-regressive hidden Markov model ↗](http://proceedings.mlr.press/v48/guan16.pdf)**Xinze Guan, Raviv Raich, Weng‐Keen Wong*36 citations*
14. **[Estimating structured vector autoregressive models ↗](http://proceedings.mlr.press/v48/melnyk16.pdf)**Igor Melnyk, Arindam Banerjee*35 citations*
15. **[Low-rank matrix approximation with stability ↗](http://proceedings.mlr.press/v48/lib16.pdf)**Dongsheng Li, Chao Chen, Qin Lv et al.*35 citations*
16. **[Efficient private empirical risk minimization for high-dimensional learning ↗](http://proceedings.mlr.press/v48/kasiviswanathan16.pdf)**Shiva Prasad Kasiviswanathan, Hongxia Jin*34 citations*
17. **[Robust principal component analysis with side information ↗](http://proceedings.mlr.press/v48/chiang16.pdf)**Kai-Yang Chiang, Cho‐Jui Hsieh, Inderjit S. Dhillon*32 citations*
18. **[A distributed variational inference framework for unifying parallel sparse Gaussian process regression models ↗](http://proceedings.mlr.press/v48/hoang16.pdf)**Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low*31 citations*
19. **[Conditional bernoulli mixtures for multi-label classification ↗](http://proceedings.mlr.press/v48/lij16.pdf)**Cheng Li, Bingyu Wang, Virgil Pavlu et al.*31 citations*
20. **[Speeding up k-means by approximating Euclidean distances via block vectors ↗](http://jmlr.org/proceedings/papers/v48/bottesch16.pdf)**Thomas Bottesch, Thomas Bühler, Markus Kächele*30 citations*
21. **[A comparative analysis and study of multiview CNN models for joint object categorization and pose estimation ↗](http://proceedings.mlr.press/v48/elhoseiny16.pdf)**Mohamed Elhoseiny, Tarek El-Gaaly, Amr Bakry et al.*29 citations*
22. **[Learning Population-Level Diffusions with Generative RNNs ↗](http://proceedings.mlr.press/v48/hashimoto16.pdf)**Tatsunori Hashimoto, David Kenneth Gifford, Tommi Jaakkola*28 citations*
23. **[ForecastICU: a prognostic decision support system for timely prediction of intensive care unit admission ↗](http://proceedings.mlr.press/v48/yoon16.pdf)**Jinsung Yoon, Ahmed M. Alaa, Scott B. Hu et al.*27 citations*
24. **[Linking losses for density ratio and class-probability estimation ↗](http://proceedings.mlr.press/v48/menon16.pdf)**Aditya Krishna Menon, Cheng Soon Ong*27 citations*
25. **[The information-theoretic requirements of subspace clustering with missing data ↗](http://proceedings.mlr.press/v48/pimentel-alarcon16.pdf)**Daniel Pimentel-Alarcón, Robert D. Nowak*27 citations*

[See all 83 papers in ICML 2016 — accepted papers →](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2016/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 Analysis](https://md.research.elamur.ai/free/en/papers/xie-2016-unsupervised-deep-embedding-clustering-analysis/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Junyuan Xie, Ross Girshick, Ali Farhadi*2016 · 222 citations*

## Fields

[Arts and Humanities (1)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [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.

[🧑‍🔬**Ali Farhadi**1 work here · 222 citations](https://md.research.elamur.ai/free/en/authors/ali-farhadi/) · [🧑‍🔬**Ross Girshick**1 work here · 222 citations](https://md.research.elamur.ai/free/en/authors/ross-girshick/)

## Top institutions

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

[🎓**University of Washington** Seattle · United States 1 work here](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🏢**Meta** Menlo Park · United States 1 work here](https://md.research.elamur.ai/free/en/companies/meta/)

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 2019](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2019/)
- [↑ back to ICML](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)