activity
20122022
most citedA Survey on Practical Applications of Multi-Armed and Contextual Bandits

107 citations · 287 across the 17 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.CY20202 cited

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing

Prateek Gupta, Tegan Maharaj, Martin Weiss +26

The rapid global spread of COVID-19 has led to an unprecedented demand for effective methods to mitigate the spread of the disease, and various digital contact tracing (DCT) method…

cs.LG2020

Predicting Infectiousness for Proactive Contact Tracing

Yoshua Bengio, Prateek Gupta, Tegan Maharaj +20

The COVID-19 pandemic has spread rapidly worldwide, overwhelming manual contact tracing in many countries and resulting in widespread lockdowns for emergency containment. Large-sca…

cs.LG2020

Double-Linear Thompson Sampling for Context-Attentive Bandits

Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay +2

In this paper, we analyze and extend an online learning framework known as Context-Attentive Bandit, motivated by various practical applications, from medical diagnosis to dialog s…

cs.CR20209 cited

COVI White Paper

Hannah Alsdurf, Edmond Belliveau, Yoshua Bengio +21

The SARS-CoV-2 (Covid-19) pandemic has caused significant strain on public health institutions around the world. Contact tracing is an essential tool to change the course of the Co…

cs.CV2020

Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation

Victor Schmidt, Makesh Narsimhan Sreedhar, Mostafa ElAraby +1

Unpaired Image-to-Image Translation (I2IT) tasks often suffer from lack of data, a problem which self-supervised learning (SSL) has recently been very popular and successful at tac…

cs.AI2020

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning

Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko +8

Continual learning studies agents that learn from streams of tasks without forgetting previous ones while adapting to new ones. Two recent continual-learning scenarios have opened…