34 PAPERS ACCEPTED AT THE INTERNATIONAL CONFERENCE ON MACHINE LEARNING (ICML)

Mila, the Quebec AI Institute is pleased to present the work of its researchers at the 37th International Conference on Machine Learning (ICML) being held this week.

For this edition, 34 publications were accepted by the reviewers for their significant contribution in the field of machine learning. In addition, several Mila members contributed to the organization of about ten workshops.

The ICML conference is world-renowned for presenting and publishing cutting-edge research on all aspects of machine learning, and is one of the fastest growing AI conferences in the world.

Accepted papers from Mila researchers cover a range of topics, including the acceleration of Generative Antagonistic Networks, Automatic Natural Language Processing (NLP), and innovations using the Variational Auto-encoder. Here is the complete list:

  1. On the Convergence of Nesterov’s Accelerated Gradient Method in Stochastic Settings
  2. Mahmoud Assran, Michael Rabbat

    https://arxiv.org/abs/2002.12414

  3. All in the (Exponential) Family: Information Geometry and Thermodynamic Variational Inference
  4. Robert Brekelmans, Vaden W Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan

    https://icml.cc/Conferences/2020/ScheduleMultitrack?event=6234

  5. TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
  6. Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy

    https://arxiv.org/abs/2002.04461

  7. Representations for Stable Off-Policy Reinforcement Learning
  8. Dibya Ghosh, Marc Bellemare

    https://proceedings.icml.cc/static/paper_files/icml/2020/5540-Paper.pdf

  9. An end-to-end approach for the verification problem: learning the right distance
  10. Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk

    https://arxiv.org/abs/2002.09469

  11. Universal Equivariant Multilayer Perceptrons
  12. Siamak Ravanbakhsh

    https://arxiv.org/abs/2002.02912

  13. Incidence Networks for Geometric Deep Learning
  14. Marjan Albooyeh, Daniele Bertolini, Siamak Ravanbakhsh

    https://arxiv.org/abs/1905.11460

  15. Latent Variable Modelling with Hyperbolic Normalizing Flows
  16. Joey Bose, Ariella Smofsky, Renjie Liao, Prakash PanangadenWill Hamilton

    https://arxiv.org/abs/2002.06336

  17. Inductive Relation Prediction by Subgraph Reasoning
  18. Komal Teru, Etienne Denis, Will Hamilton

    https://arxiv.org/pdf/1911.06962.pdf

  19. On Variational Learning of Controllable Representations for Text without Supervision
  20. Peng Xu, Jackie Chi Kit Cheung, Yanshuai Cao

    https://arxiv.org/abs/1905.11975

  21. What can I do here? A Theory of Affordances in Reinforcement Learning
  22. Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup

    https://arxiv.org/abs/2006.15085

  23. Constrained Markov Decision Processes via Backward Value Functions
  24. Harsh Satija, Philip Amortila, Joelle Pineau

    https://openreview.net/forum?id=S1lyyANYwr

  25. Invariant Causal Prediction for Block MDPs
  26. Clare Lyle, Amy Zhang, Angelos Filos, Shagun Sodhani, Marta Kwiatkowska, Yarin Gal, Doina PrecupJoelle Pineau

    https://arxiv.org/abs/2003.06016

  27. Online Learned Continual Compression with Adaptive Quantization Modules
  28. Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau

    https://arxiv.org/abs/1911.08019

  29. Interference and Generalization in Temporal Difference Learning
  30. Emmanuel Bengio, Joelle Pineau, Doina Precup

    https://arxiv.org/abs/2003.06350

  31. Few-shot Relation Extraction via Bayesian Meta-learning on Task Graphs
  32. Meng Qu, Tianyu Gao, Louis-Pascal Xhonneux, Jian Tang

    https://arxiv.org/abs/2007.02387

  33. Continuous Graph Neural Networks
  34. Louis-Pascal Xhonneux, Meng Qu, Jian Tang

    https://arxiv.org/abs/1912.00967

  35. Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling
  36. Yao Liu, Pierre-Luc Bacon, Emma Brunskill

    https://arxiv.org/abs/1910.06508

  37. Linear Lower Bounds and Conditioning of Differentiable Games
  38. Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas

    https://arxiv.org/abs/1906.07300

  39. Stochastic Hamiltonian Gradient Methods for Smooth Games
  40. Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal VincentSimon Lacoste-JulienIoannis Mitliagkas

    https://arxiv.org/abs/2007.04202

  41. Countering Language Drift with Seeded Iterated Learning
  42. Yuchen Lu, Soumye Singhal, Florian Strub, Aaron Courville, Olivier Pietquin

    https://arxiv.org/abs/2003.12694

  43. AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
  44. Jae Hyun Lim, Aaron CourvilleChristopher Pal, Chin-Wei Huang

    https://arxiv.org/abs/2006.05164

  45. Revisiting Fundamentals of Experience Replay
  46. William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua BengioHugo Larochelle, Mark Rowland, Will Dabney

    https://acsweb.ucsd.edu/~wfedus/pdf/replay.pdf

  47. Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
  48. Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio

    https://arxiv.org/abs/2006.16981

  49. Learning to Navigate in Synthetically Accessible Chemical Space Using Reinforcement Learning
  50. Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Haoran Wei, Yashaswi Pathak, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio

    https://arxiv.org/abs/2004.12485

  51. Small-GAN: Speeding up GAN Training using Core-Sets
  52. Samrath Sinha, Han Zhang, Anirudh Goyal, Yoshua BengioHugo Larochelle, Augustus Odena

    https://arxiv.org/abs/1910.13540

  53. Perceptual Generative Autoencoders
  54. Zijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua BengioLiam Paull

    https://arxiv.org/abs/1906.10335

  55. Decoupled Greedy Learning of CNNs
  56. Eugene Blilovsky, Michael Eickenbert, Edouard Oyallon

    https://proceedings.icml.cc/static/paper_files/icml/2020/2966-Paper.pdf

  57. Revisiting Training Strategies and Generalization Performance in Deep Metric Learning
  58. Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen

    https://arxiv.org/abs/2002.08473

  59. Learning Structured Latent Factors from Dependent Data: A Generative Model Framework from Information-Theoretic Perspective
  60. Ruixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro

    https://proceedings.icml.cc/static/paper_files/icml/2020/1111-Paper.pdf

  61. On Relativistic f-Divergences
  62. Alexia Jolicoeur-Martineau

    https://proceedings.icml.cc/static/paper_files/icml/2020/2391-Paper.pdf

  63. A Unified Theory of Decentralized SGD with Changing Topology and Local Updates
  64. Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich

    https://proceedings.icml.cc/static/paper_files/icml/2020/4675-Paper.pdf

  65. A Graph to Graphs Framework for Retrosynthesis Prediction
  66. Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang

    https://arxiv.org/abs/2003.12725

  67. Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation
  68. Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei

    https://proceedings.icml.cc/static/paper_files/icml/2020/5006-Paper.pdf

WORKSHOPS

  1. Women in Machine Learning Un-Workshop
  2. Tatjana Chavdarova · Caroline V Weis · Amy Zhang · Fariba Yousefi · Mandana Samiei · Larissa Schiavo

    https://icml.cc/Conferences/2020/Schedule?showEvent=7300

  3. Graph Representation Learning and Beyond (GRL+)
  4. Petar Veličković · Michael M. Bronstein · Andreea Deac · Will Hamilton · Jessica Hamrick · Milad Hashemi · Stefanie Jegelka · Jure Leskovec · Renjie Liao · Federico Monti · Yizhou Sun · Kevin Swersky · Rex (Zhitao) Ying · Marinka Žitnik

    https://icml.cc/Conferences/2020/Schedule?showEvent=5715

  5. Self-supervision in Audio and Speech
  6. Mirco Ravanelli · Dmitriy Serdyuk · R Devon Hjelm · Bhuvana Ramabhadran · Titouan Parcollet

    https://icml.cc/Conferences/2020/Schedule?showEvent=5732

  7. MLRetrospectives : A Venue for Self-Reflection in ML Research
  8. Jessica Forde · Jesse Dodge · Mayoore Jaiswal · Rosanne Liu · Ryan Lowe · Rosanne Liu · Joelle Pineau · Yoshua Bengio

    https://icml.cc/Conferences/2020/Schedule?showEvent=5739

  9. Workshop on Continual Learning
  10. Haytham Fayek · Arslan Chaudhry · David Lopez-Paz · Eugene Belilovsky · Jonathan Schwarz · Marc Pickett · Rahaf Aljundi · Sayna Ebrahimi · Razvan Pascanu · Puneet Dokania

    https://icml.cc/Conferences/2020/Schedule?showEvent=5743

  11. 4th Lifelong Learning Workshop
  12. Shagun Sodhani · Sarath Chandar · Balaraman Ravindran · Doina Precup

    https://icml.cc/Conferences/2020/Schedule?showEvent=5735

  13. INNF+: Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models
  14. Chin-Wei Huang · David Krueger · Rianne Van den Berg · George Papamakarios · Chris Cremer · Tian Qi Chen · Danilo J. Rezende

    https://icml.cc/Conferences/2020/Schedule?showEvent=5742

  15. Machine Learning for Global Health
  16. Danielle Belgrave · Danielle Belgrave · Stephanie Hyland · Charles Onu · Nicholas Furnham · Ernest Mwebaze · Neil Lawrence

    https://icml.cc/Conferences/2020/Schedule?showEvent=5728

  17. Bridge Between Perception and Reasoning: Graph Neural Networks & Beyond
  18. Jian Tang · Le Song · Jure Leskovec · Renjie Liao · Yujia Li · Sanja Fidler · Richard Zemel · Ruslan Salakhutdinov

    https://icml.cc/Conferences/2020/Schedule?showEvent=5744

Photo from: Perceptual Generative Autoencoders https://arxiv.org/abs/1906.10335