Keynotes

Irina Rish is an associate professor in the Computer Science and Operations Research department at the Université de Montréal (UdeM) and a core member of Mila – Quebec AI Institute. She holds MSc and PhD in AI from University of California, Irvine and MSc in Applied Mathematics from Moscow Gubkin Institute. Dr. Rish’s research focus is on machine learning, neural data analysis and neuroscience-inspired AI. Her current research interests include continual lifelong learning, optimization algorithms for deep neural networks, sparse modeling and probabilistic inference, dialog generation, biologically plausible reinforcement learning, and dynamical systems approaches to brain imaging analysis. Before joining UdeM and Mila in 2019, Irina was a research scientist at the IBM T.J. Watson Research Center, where she worked on various projects at the intersection of neuroscience and AI, and led the Neuro-AI challenge. She received multiple IBM awards, including IBM Eminence & Excellence Award and IBM Outstanding Innovation Award in 2018, IBM Outstanding Technical Achievement Award in 2017, and IBM Research Accomplishment Award in 2009.

Zachary Chase Lipton - Tepper School of Business - Carnegie Mellon ...

Zachary Chase Lipton is an assistant professor of Operations Research and Machine Learning at Carnegie Mellon University. His research spans core machine learning methods and their social impact and addresses diverse application areas, including clinical medicine and natural language processing. Current research focuses include robustness under distribution shift, cancer screening, the effective and equitable allocation of organs, and the intersection of causal thinking and the messy high-dimensional data that characterizes modern deep learning applications. He is the founder of the Approximately Correct blog (approximatelycorrect.com) and a co-author of Dive Into Deep Learning, an interactive open-source book drafted entirely through Jupyter notebooks. Find on Twitter (@zacharylipton) or GitHub (@zackchase).

Natalie Schluter is Senior Research Scientist at Google Brain and Associate Professor in NLP and Data Science at the IT University (ITU), in Copenhagen, Denmark.  At ITU she co-developed and now leads the first Data Science programme in Denmark, a BSc.  Before coming to ITU, she held positions as Chief Analyst at MobilePay, Danske Bank, and Postdoctoral Researcher at the University of Copenhagen and Malmö University.  Natalie’s primary research interests are in algorithms and experiment methodology for the development statistical and combinatorial models of natural language understanding and generation, especially under computationally “hard” settings. She holds a PhD in NLP from Dublin City University’s School of Computing.  She holds a further four degrees: an MSc in Mathematics from Trinity College, Dublin, a BSc in Mathematics and MA in Linguistics from the University of Montreal, and a BA in French and Spanish. Natalie is currently serving as Equity Director for the ACL, after serving as ACL 2020 co-Programme Chair.  She is a Canadian, living in Copenhagen for the past 10 years with her two daughters.

Panel

A panel on Ethics, Fairness, and Bias in AI will be moderated by Abhishek Gupta and will feature the keynote speakers as panelists: Natalie Schluter, Zack Chase Lipton, and Irina Rish.

Submit your questions to the panel here!

Abhishek Gupta is the founder of Montreal AI Ethics Institute (https://montrealethics.ai ) and a Machine Learning Engineer at Microsoft where he serves on the CSE Responsible AI Board. His research focuses on applied technical and policy methods to address ethical, safety and inclusivity concerns in using AI in different domains. He has built the largest community driven, public consultation group on AI Ethics in the world. His work on public competence building in AI Ethics has been recognized by governments from North America, Europe, Asia, and Oceania. More information on his work can be found at https://atg-abhishek.github.io. He is a Faculty Associate at the Frankfurt Big Data Lab at the Goethe University, a guest lecturer at the McGill University School of Continuing Studies for the Data Science in Business Decisions course and a Visiting AI Ethics Researcher on the Future of Work for the US State Department representing Canada.

Posters

These correspond to the rooms and poster numbers in Gathertown.

Poster room 1 – Supervised Learning and Deep Learning

2. Deep Active Learning: Unified and Principled Method for Query and Training. Shui, Changjian*; Zhou, Fan; gange, christian; Wang, Boyu. Video. Poster.
9. Towards CNN Representations for Small MS Spectral Data Classification: From Transfer Learning to Cumulative Learning. seddiki, Khawla*; Droit, Arnaud . Video. Poster.
12. Lens design generation with a deep neural network. Côté, Geoffroi*; Lalonde, Jean-Francois; Thibault, Simon. Video. Poster.
14. Tracking and predicting COVID-19 radiological trajectory using deep learning on chest X-rays: initial accuracy testing. Gourdeau, Daniel*; Duchesne, Simon; Archambault, Patrick; Chartrand-Lefebvre, Carl; Dieumegarde, Louis; Forghani, Reza; Gagné, Christian; Hains, Alexandre; Hornstein, David; Le, Huy; Lemieux, Simon; Lévesque, Marie-Hélène; Martin, Diego; Rosenbloom, Lorne; Tang, An; Vecchio, Fabrizio; Potvin, Olivier; Duchesne, Nathalie. Video. Poster.
28. Bayesian active learning for production, a systematic study and a reusable library. Atighehchian, Parmida; Branchaud-Charron, Frederic*; Lacoste, Alexandre. Video. Poster.
31. Structured Convolutional Kernel Networks for Airline Crew Scheduling. Yaakoubi, Yassine*; Lacoste-Julien, Simon; Soumis, Francois. Video. Poster.
36. Toward Metrics for Differentiating Out-of-Distribution Sets. Abbasi, Mahdieh*; Shui, Changjian; Rajabi, Arezoo; Gagné, Christian; Bobba, Rakesh B. Video. Poster.
38. Shaping an input gradient landscape usable for image synthesis while training a deep classifier. Bordes, Florian*; Berthier, Tess; Di Jorio, Lisa; Vincent, Pascal. Video. Poster.
41. Predicting COVID-19 intervention outcome: A Quebec study. Gourdeau, Daniel*; Hains, Alexandre; Dieumegarde, Louis ; Archambault, Patrick; Chartrand-Lefebvre, Carl; Duchesne, Nathalie; Forghani, Reza; Gagné, Christian; Gagnon, Louis; Giguère, Raphaëlle; Hornstein, David; Le, Huy; Lemieux, Simon; Lévesque, Marie-Hélène; Martin, Diego; Nepveu, Simon; Rosenbloom, Lorne; Tang, An; Yiqun Yang, Issac ; Potvin, Olivier; Duchesne, Simon. Video. Poster.
48. Unraveling the neural signatures of dream recall in EEG: a deep learning approach. Kemtur, Anirudha*; Ghosh, Arna; Lajnef, Tarek; dehgan, Artthur; vallat, Raphael; eichenlaub, Jean-Baptiste; Ruby, Perrine; Jerbi, Karim. Video. Poster.
55. Scattering GCN: Overcoming Oversmoothness in Graph Conv. Networks. Min, Yimeng; Wenkel, Frederik*; Wolf, Guy. Video. Poster.
57. Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations. Assran, Mahmoud*; Ballas, Nicolas; Castrejon, Lluis; Rabbat, Mike. Video. Poster.
60. Evaluating Logical Generalization in Graph Neural Networks. Sinha, Koustuv*; Sodhani, Shagun; Pineau, Joelle; Hamilton, Will. Video. Poster.
76. Template-based Unseen Instance Detection. Mercier, Jean-Philippe; Garon, Mathieu*; Giguère, Philippe; Lalonde, Jean-Francois. Video. Poster.
77. Supervised Learning on Phylogenetically Distributed Data. Layne, Elliot I*; Dort, Erika; Hamelin, Richard; Li, Yue; Blanchette, Mathieu. Video. Poster.
88. Zoom Out: Using Thumbnails for Weakly Supervised Land Detection in Whale Population Monitoring. Simpson, Becks*; Gagne, Antoine; Charry Tissier, Emily; Charry, Bertrand. Video. Poster.
92. PatchUp: A Regularization Technique for Convolutional Neural Networks. Faramarzi, Mojtaba; Amini, Mohammad*; Badrinaaraayanan, Akilesh; Verma, Vikas; Chandar, Sarath. Video. Poster.
104. NeurDNet: A Deep Explainable Artificial Intelligent Approach for Neurological Disorders Discrimination. Shahtalebi, Soroosh*; Atashzar, S. Farokh; Patel, Rajni; Jog, Mandar; Mohammadi, Arash. Video. Poster.
105. Guided Attention For Fine-Grained and Hierarchical Classification. Kantor, Charles*; Rauby, Brice; Jehanno, Emmanuel; Boussioux, Léonard; Luccioni, Sasha; Talbot, Hugues. Video. Poster.
110. Exploiting ontological knowledge in deep learning, a case in diary production optimization . Martin, Tomas*; Diallo, Abdoulaye Banire; Valtchev, Petko. Video. Poster.
124. La-MAML: Look-ahead Meta Learning for Continual Learning. Gupta, Gunshi*; Yadav, Karmesh; Paull, Liam. Video. Poster.

Poster room 2 – Computer Vision and Natural Language Processing

1. Developing a core set of mobility domains among individuals with acquired brain injury (ABI): Empowering the creation of core outcome sets using natural language processing (NLP) . Alhasani, Rehab*; Godbout, Mathieu; Durand, Audrey; Ahmed, Sara. Video. Poster.
3. Sequence Modeling with Time-aware Large Kernel Convolutions. Lioutas, Vasileios*; Guo, Yuhong. Video. Poster.
11. Leveraging Subword Embeddings for MultinationalAddress Parsing. Beauchemin, David*; Lamontagne, Luc; Laviolette, François; Yassine, Marouane. Video. Poster.
15. Input Dropout for Spatially Aligned Modalities. de Blois, Sébastien SdeB*; Garon, Mathieu; Gagné, Christian; Lalonde, Jean-Francois. Video. Poster.
22. Self-supervised Robust Object Detectors for Merged Datasets. Abbasi, Mahdieh*; Gagné, Christian; Laurendeau, Denis. Video. Poster.
23. Sust-BERT: Identifying Climate Change in Financial Disclosures using Question Answering. Luccioni, Sasha*; Baylor, Emily. Video. Poster.
37. AN ANALYSIS OF OBJECT REPRESENTATIONS IN DEEP VISUAL TRACKERS. Goroshin, Ross*; Dwibedi, Debidatta; Tompson, Jonathan. Video. Poster.
39. Local Anomaly Detection in Videos using Object-Centric Adversarial Learning. Roy, Pankaj PRR*; Bilodeau, Guillaume-Alexandre; Seoud, Lama. Video. Poster.
44. Automatic Localization of Grasping Point on Trees. Grondin, Vincent*. Video. Poster.
53. High-Wire AI: Automated Robotic Inspection in Low-Data Environments. Peplowski, Alexander*; Lelièvre, Philippe; Bedwani, Jean-Luc; Beaudry, Julien; Bordes, Florian. Video. Poster.
54. Rain rendering for evaluating and improving robustness to bad weather. Tremblay, Maxime*; Halder, Shirsendu S.; de Charette, Raoul; Lalonde, Jean-Francois. Video. Poster.
58. A Question Answering System in Response to the COVID-19 Crisis. Bronzi, Mirko; Pinto, Jeremy; Ghosn, Joumana; Subakan, Cem*; Sharma, Prakhar; Lu, Xing Han; Reddy, Siva. Video. Poster.
62. Big Players: Emotion in Twitter Communities Tweeting about Global Warming. Drown, Dennis J*; Villemaire, Roger; Robert, Serge. Video. Poster.
63. Hurricast: Hurricane Forecasting with Computer Vision and Sequence Modeling. Boussioux, Léonard*; Guenais, Théo J; Zeng, Cynthia; Bertsimas, Dimitris. Video. Poster.
68. Weakly supervised learning for semantic segmentation of microscopy images. Bilodeau, Anthony*; Durand, Audrey; Lavoie-Cardinal, Flavie. Video. Poster.
71. RGB-D-E: Event Camera Calibration for Fast 6-DOF Object Tracking. Dubeau, Etienne*; Garon, Mathieu; Debaque, Benoit; de Charette, Raoul; Lalonde, Jean-Francois. Video. Poster.
89. Low-resource Neural Machine Translation: The case and challenges of Inuktitut. Le, Tan; sadat, fatiha*. Video. Poster.
97. A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well. Garneau, Nicolas*; Godbout, Mathieu; Beauchemin, David; Durand, Audrey; Lamontagne, Luc. Video. Poster.
99. Using Temporal and Geographical Features for Butterfly Classification. Skreta, Marta*; Drapeau Picard, Andre-Philippe; Larrivee, Maxim; Luccioni, Sasha; Rolnick, David. Video. Poster.
101. Towards an Emotionally Driven Natural Language Generation. BELAININE, BILLAL BB; sadat, fatiha*; lounis, hakim; Boukadoum, Mounir. Video. Poster.
106. Learning Long-term Dependencies Using Cognitive Inductive Biases in Self-attention RNNs. Kerg, Giancarlo B*; Kanuparthi, Bhargav; Goyal, Anirudh; Goyette , Kyle; Bengio, Yoshua; Lajoie, Guillaume. Video. Poster.

Poster room 3 – Core Machine Learning

5. Towards a classification of behavioural equivalences in continuous-time Markov processes. Clerc, Florence*; Panangaden, Prakash; Chen, Linan. Video. Poster.
8. Lagrangian-based Dynamics for Game Optimization. Askari Hemmat, Reyhane; Mitra, Amartya*; Lajoie, Guillaume; Mitliagkas, Ioannis. Video. Poster.
10. PAC-Bayesian Binary Activated Deep Neural Networks. Letarte, Gaël*; Germain, Pascal; Guedj, Benjamin; Laviolette, François. Video. Poster.
13. Uncertainty based meta-optimization in few-shot learning. Kwon, Namyeong*; Na, Hwidong; Lacoste-Julien, Simon. Video. Poster.
19. Optimizing ANN Architectures using Mixed Integer Programming. ElAraby, Mostafa*; Wolf, Guy; Carvalho, Margarida. Video. Poster.
26. Associative Alignment for Few-shot Image Classification. Afrasiyabi, Arman*; Lalonde, Jean-Francois; Gagné, Christian. Video. Poster.
27. Metrics for Deterministic Weighted Automata. Utepova, Alika*; Panangaden, Prakash. Video. Poster.
29. How Different Are Lottery Tickets and the Pruned Solution?. Evci, Utku*; Dauphin, Yann; Keskin, Cem; Ioannou, Yani A. Video. Poster.
32. Minimax Theorem for Nonconcave-Nonconvex Games Played with Neural Nets. Gidel, Gauthier*; Czarnecki, Wojciech M; Balduzzi, David; Garnelo, Marta; Bachrach, Yoram. Video. Poster.
45. Differentiable Causal Discovery from Interventional Data. Brouillard, Philippe*; Lachapelle, Sebastien; Lacoste, Alexandre; Lacoste-Julien, Simon; Drouin, Alexandre. Video. Poster.
46. To Each Optimizer a Norm, To Each Norm its Generalization. Babanezhad, Reza*; Vaswani, Sharan; Gallego Posada, Jose D; Mishkin, Aaron; Lacoste-Julien, Simon; Le Roux, Nicolas. Video. Poster.
56. Simulated Hyperparameter Optimization for Statistical Tests in Machine Learning Benchmarks. Bouthillier, Xavier*; Delaunay, Pierre; Bronzi, Mirko; Trofimov, Assya; Nichyporuk, Brennan S; Szeto, Justin; Mohammadi Sepahvand, Nazanin; Raff, Edward; Madan, Kanika; Voleti, Vikram; Ebrahimi Kahou, Samira; Michalski, Vincent; Serdyuk, Dmitriy; Arbel, Tal; Pal, Chris J; Varoquaux, Gael P; Vincent, Pascal. Video. Poster.
59. Average-Case Acceleration Through Spectral Density Estimation. Scieur, Damien*; Pedregosa, Fabian. Video. Poster.
75. Principal Neighbourhood Aggregation for Graph Nets. Corso, Gabriele; Cavalleri, Luca; Beani, Dominique*; Lió, Pietro; Veličković, Petar. Video. Poster.
78. Evaluating the impact of lens profiles on depth estimation for wide-angle images. Buquet, Julie*; Zhang, Jinsong; Lalonde, Jean-Francois; Thibault, Simon. Video. Poster.
84. Hyperbolic Normalizing Flows. Bose, Joey*; Smofsky, Ariella; Liao, Renjie; Panangaden, Prakash; Hamilton, Will. Video. Poster.
94. Metric learning: cross-entropy vs. pairwise losses. Boudiaf, Malik*; Rony, Jérôme; Ziko, Imtiaz Masud; Granger, Eric; Pedersoli, Marco; Piantanida, Pablo; Ben Ayed, Ismail. Video. Poster.
95. MPCL: Multi-class N-pair Cosine Similarity for Deep Metric Learning. Shahtalebi, Soroosh*; Mohammadi, Arash. Video. Poster.
96. A Unification of Learning Paradigms for Continual Learning. Normandin, Fabrice; Rodriguez, Pau; Ostapenko, Oleksiy; Vazquez, David; Charlin, Laurent; Rish, Irina; Caccia, Massimo*. Video. Poster.
98. Geometric directional message passing in graph nets. Beani, Dominique*; Passaro, Saro; Létourneau, Vincent; Hamilton, William L; Lió, Pietro. Video. Poster.
107. Out-of-Distribution Generalization via Risk Extrapolation. Krueger, David*; Caballero, Ethan; Jacobsen, Joern-Henrik; Zhang, Amy; Binas, Jonathan; Le Priol, Remi; Courville, Aaron. Video. Poster.
108. NNGeometry: a PyTorch library for flawless handling of large Fisher Information Matrices and Neural Tangent Kernels. George, Thomas*. Video. Poster.
112. Scalable Stochastic Structured Variance-Reduced Gradients for Graph Embedding. Liu, Lewis*; Zhu, Zhaocheng. Video. Poster.
117. Implicit Regularization in Deep Learning: A View from Function Space. Baratin, Aristide*; George, Thomas; Laurent, César; Hjelm, R Devon; Lajoie, Guillaume; Vincent, Pascal; Lacoste-Julien, Simon. Video. Poster.
118. Effective Asynchronous Distributed Deep Neural Network Training for Large-Scale Recommender Systems. Liu, Lewis*; Zhao, Kun; Xu, Shizhen; Li , Yong. Video. Poster.
122. In Search of Robust Measures of Generalization. Dziugaite, Gintare Karolina; Drouin, Alexandre; Neal, Brady; Rajkumar, Nitarshan*; Caballero, Ethan; Wang, Linbo; Mitliagkas, Ioannis; Roy, Daniel M.. Video. Poster.

Poster room 4 – Reinforcement Learning and Others

16. Temporal Difference Couples Poorly with Deep Neural Networks. Bengio, Emmanuel*; Pineau, Joelle; Precup, Doina. Video. Poster.
17. Green Lighting ML: Confidentiality, Integrity, and Availability of Machine Learning Systems in Deployment. Galinkin, Erick*; Gupta, Abhishek. Video. Poster.
20. Probabilistic Risk Awareness Can Reduce the Spread of Covid-19. Bengio, Yoshua; Maharaj, Tegan*; Weiss, Martin; Deleu, Tristan; Gupta, Prateek; Qu, Meng; Rahaman, Nasim; Schmidt, Victor; St-Charles, Pierre-Luc; Rish, Irina; Ortiz, Satya; Carrier, PierreLuc; Muller, Eilif B; Tang, Jian; Bilaniuk, Olexa; Schölkopf, Bernhard; Sharma, Abhinav; Alsdurf, Hannah; Buckeridge, David; Caron, Gaetan; Pal, Chris J; Williams, Andrew. Video. Poster.
25. LinBanditSum: Reframing Extractive Summarization as a Linear Bandit. Godbout, Mathieu*; Lamontagne, Luc; Durand, Audrey. Video. Poster.
30. Unsupervised identification of atypical medication orders: A GANomaly-based approach. Thibault, Maxime*; Snell, Pierre; Durand, Audrey. Video. Poster.
34. Metrics and continuity in reinforcement learning. Le Lan, Charline*; G. Bellemare, Marc; Castro, Pablo Samuel. Video. Poster.
35. An Analysis of the Adaptation Speed of Causal Models. Le Priol, Remi*; Babanezhad, Reza; Bengio, Yoshua; Lacoste-Julien, Simon. Video. Poster.
42. Estimating g-Leakage via Machine Learning. Romanelli, Marco*; Chatzikokolakis, Konstantinos ; Palamidessi, Catuscia; Piantanida, Pablo. Video. Poster.
43. Synbols: Probing Learning Algorithms with Synthetic Datasets. Lacoste, Alexandre*; Rodriguez, Pau; Branchaud-Charron, Frederic; Atighehchian, Parmida; Laradji, Issam Hadj; Caccia, Massimo; Drouin, Alexandre; Craddock, Matt; Vazquez, David. Video. Poster.
50. Extendable and invertible manifold learning with geometry regularized autoencoders. Morin, Sacha*; Duque, Andres F; Wolf, Guy; Moon, Kevin. Video. Poster.
51. Adversarial Example Games. Bose, Joey; Gidel, Gauthier*; Berard, Hugo; Cianflone, Andre; Vincent, Pascal; Lacoste-Julien, Simon; Hamilton, Will. Video. Poster.
52. Enforcing Fairness in Neural Networks via Counterexample-Guided Learning. Farnadi, Golnoosh*; Lacoste-Julien, Simon. Video. Poster.
69. Deep Interpretability for Gene-Wide Association Studies. ); Audrey Lemacon (Montreal Heart Institute); Marie-Pierre Dubé (Montreal Heart Institute); Joelle Pineau (McGill / Facebook). Video. Poster.
70. Anomaly Detection with Autoencoder Augmented GAN. Rafiee, Laya*; Fevens, Thomas. Video. Poster.
79. Neural representation and generation for RNA secondary structures. Yan, Zichao*; Blanchette, Mathieu; Hamilton, Will. Video. Poster.
80. Unsupervised Domain Adversarial Self-Calibration for Electromyographic-based Gesture Recognition. Côté-Allard, Ulysse*; Gagnon-Turcotte, Gabriel; Phinyomark, Angkoon; Glette, Kyrre; Scheme, Erik; Laviolette, François; Gosselin, Benoit. Video. Poster.
81. Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites. Ahsan, Faizy*; Drouin, Alexandre; Laviolette, François; Precup, Doina; Blanchette, Mathieu. Video. Poster.
82. Transfer learning improves genetic risk prediction for under-represented ethnic groups. Lu, Tianyuan; Xu, Yu; Grealey, Jason; Bzdok, Danilo; Greenwood, Celia; Inouye, Michael; Richards, Brent; Durand, Audrey*. Video. Poster.
87. What do we measure when we measure the ethics of AI systems? . Rismani, Shalaleh*; Moon, AJung. Video. Poster.
102. Data Efficient Reinforcement Learning with Self-Predictive Representations. Schwarzer, Max; Anand, Ankesh*; Goel, Rishab; Hjelm, Devon; Courville, Aaron; Bachman, Philip. Video. Poster.
103. Generalized Policy Gradient. Yan, Yutong*; Bacon, Pierre-Luc. Video. Poster.
109. Considering Assumptions of Emergent Communication. Noukhovitch, Michael*. Video. Poster.
111. Fair Kidney Exchange by Enumerating Optimal Solutions. Farnadi, Golnoosh; Babaki, Behrouz; St-Arnaud , William*; Carvalho, Margarida. Video. Poster.
116. RNA 3D Module Identification in Sequences with Structural Context Sampling. Sarrazin Gendron, Roman*; Yao, Hua-Ting; Reinharz, Vladimir; Gonzalez Oliver, Carlos; Ponty, Yann; Waldispuhl, Jerome. Video. Poster.