81 citations
- Université de MontréalCA11 papers
- McGill UniversityCA7 papers
- Google DeepMind (United Kingdom)GB3 papers
- Brain (Germany)DE2 papers
- Flatiron Health (United States)US2 papers
- Flatiron Institute2 papers
- Google (United States)US2 papers
- Peking UniversityCN2 papers
- Samsung (South Korea)KR2 papers
- Tencent (China)CN2 papers
- Ahlia UniversityBH1 paper
- Brown UniversityUS1 paper
9 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…