167 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université de MontréalCA31 papers
- McGill UniversityCA16 papers
- Mila - Quebec Artificial Intelligence InstituteCA11 papers
- Concordia UniversityCA5 papers
- Flatiron Health (United States)US5 papers
- Flatiron Institute5 papers
- Google DeepMind (United Kingdom)GB5 papers
- Meta (Israel)IL5 papers
- Canadian Institute for Advanced ResearchCA4 papers
- Polytechnique MontréalCA4 papers
- University of TorontoCA4 papers
- Google (United States)US3 papers
11 papers · 1 filter
Equivariant Networks for Pixelized Spheres
Mehran Shakerinava, Siamak Ravanbakhsh
Pixelizations of Platonic solids such as the cube and icosahedron have been widely used to represent spherical data, from climate records to Cosmic Microwave Background maps. Plato…
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning
Eugene Belilovsky, Louis Leconte, Lucas Caccia +2
A commonly cited inefficiency of neural network training using back-propagation is the update locking problem: each layer must wait for the signal to propagate through the full net…
Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction
Zhexue Chen, Hong Huang, Bang Liu +2
Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from sentences, where each triplet includes an entity, its associated sentiment, and the opinion span explaining…
Randomized Exploration for Reinforcement Learning with General Value Function Approximation
Haque Ishfaq, Qiwen Cui, Viet Nguyen +5
We propose a model-free reinforcement learning algorithm inspired by the popular randomized least squares value iteration (RLSVI) algorithm as well as the optimism principle. Unlik…
Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval
Zijing Ou, Qinliang Su, Jianxing Yu +5
With the need of fast retrieval speed and small memory footprint, document hashing has been playing a crucial role in large-scale information retrieval. To generate high-quality ha…
Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting
Yi Cheng, Siyao Li, Bang Liu +4
This paper explores the task of Difficulty-Controllable Question Generation (DCQG), which aims at generating questions with required difficulty levels. Previous research on this ta…
Structured Convolutional Kernel Networks for Airline Crew Scheduling
Yassine Yaakoubi, François Soumis, Simon Lacoste-Julien
Motivated by the needs from an airline crew scheduling application, we introduce structured convolutional kernel networks (Struct-CKN), which combine CKNs from Mairal et al. (2014)…
Deep Discourse Analysis for Generating Personalized Feedback in Intelligent Tutor Systems
Matt Grenander, Robert Belfer, Ekaterina Kochmar +3
We explore creating automated, personalized feedback in an intelligent tutoring system (ITS). Our goal is to pinpoint correct and incorrect concepts in student answers in order to…
Continuous Coordination As a Realistic Scenario for Lifelong Learning
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville +1
Current deep reinforcement learning (RL) algorithms are still highly task-specific and lack the ability to generalize to new environments. Lifelong learning (LLL), however, aims at…
Variance Penalized On-Policy and Off-Policy Actor-Critic
Arushi Jain, Gandharv Patil, Ayush Jain +2
Reinforcement learning algorithms are typically geared towards optimizing the expected return of an agent. However, in many practical applications, low variance in the return is de…
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
Louis Thiry, Michael Arbel, Eugene Belilovsky +1
A recent line of work showed that various forms of convolutional kernel methods can be competitive with standard supervised deep convolutional networks on datasets like CIFAR-10, o…