Publications

ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning
Sean Andrew Chen
Jensen Gao
Siddharth Reddy
Glen Berseth
Anca Dragan
Sergey Levine
Building assistive interfaces for controlling robots through arbitrary, high-dimensional, noisy inputs (e.g., webcam images of eye gaze) can… (see more) be challenging, especially when it involves inferring the user's desired action in the absence of a natural ‘default’ interface. Reinforcement learning from online user feedback on the system's performance presents a natural solution to this problem, and enables the interface to adapt to individual users. However, this approach tends to require a large amount of human-in-the-loop training data, especially when feedback is sparse. We propose a hierarchical solution that learns efficiently from sparse user feedback: we use offline pre-training to acquire a latent embedding space of useful, high-level robot behaviors, which, in turn, enables the system to focus on using online user feedback to learn a mapping from user inputs to desired high-level behaviors. The key insight is that access to a pre-trained policy enables the system to learn more from sparse rewards than a naïve RL algorithm: using the pre-trained policy, the system can make use of successful task executions to relabel, in hindsight, what the user actually meant to do during unsuccessful executions. We evaluate our method primarily through a user study with 12 participants who perform tasks in three simulated robotic manipulation domains using a webcam and their eye gaze: flipping light switches, opening a shelf door to reach objects inside, and rotating a valve. The results show that our method successfully learns to map 128-dimensional gaze features to 7-dimensional joint torques from sparse rewards in under 10 minutes of online training, and seamlessly helps users who employ different gaze strategies, while adapting to distributional shift in webcam inputs, tasks, and environments
2022-02-05
ArXiv (preprint)
doi.org
arxiv.org
TIML: Task-Informed Meta-Learning for Agriculture
Gabriel Tseng
Hannah Kerner
David Rolnick
Labeled datasets for agriculture are extremely spatially imbalanced. When developing algorithms for data-sparse regions, a natural approach … (see more)is to use transfer learning from data-rich regions. While standard transfer learning approaches typically leverage only direct inputs and outputs, geospatial imagery and agricultural data are rich in metadata that can inform transfer learning algorithms, such as the spatial coordinates of data-points or the class of task being learned. We build on previous work exploring the use of meta-learning for agricultural contexts in data-sparse regions and introduce task-informed meta-learning (TIML), an augmentation to model-agnostic meta-learning which takes advantage of task-specific metadata. We apply TIML to crop type classification and yield estimation, and find that TIML significantly improves performance compared to a range of benchmarks in both contexts, across a diversity of model architectures. While we focus on tasks from agriculture, TIML could offer benefits to any meta-learning setup with task-specific metadata, such as classification of geo-tagged images and species distribution modelling.
2022-02-04
ArXiv (preprint)
arxiv.org
arxiv.org
Quantum-Inspired Interpertable AI-Empowered Decision Support System for Detection of Early-Stage Rheumatoid Arthritis in Primary Care Using Scarce Dataset
Samira Abbasgholizadeh-Rahimi
Mojtaba Kolahdoozi
Arka Mitra
Jose L Salmeron
Amir-Mohammad Navali
Alireza Sadeghpour
Amir Mir Mir Mohammadi
2022-02-03
Mathematics (published)
doi.org
Active Learning for Capturing Human Decision Policies in a Data Frugal Context
Loïc Grossetête
Alexandre Marois
Bénédicte Chatelais
Christian Gagné
Daniel Lafond
2022-02-02
Machine Learning, Optimization, and Data Science (published)
doi.org
Sex-specific lesion pattern of functional outcomes after stroke
Anna K. Bonkhoff
Martin Bretzner
Sungmin Hong
Markus D. Schirmer
Alexander L. Cohen
Robert W. Regenhardt
Kathleen Donahue
Marco Nardin
Adrian Dalca
Anne-Katrin Giese
Mark R. Etherton
Brandon L. Hancock
Steven J.T. Mocking
Elissa McIntosh
John Richard Attia
Oscar Benavente
S. Bevan
John W. Cole
Amanda Donatti
Christoph Griessenauer … (see 38 more)
Laura Heitsch
Lukas Holmegaard
Katarina Jood
Jordi Jimenez-Conde
Steven Kittner
Robin Lemmens
C. Levi
Caitrin W. McDonough
James Meschia
Chia-Ling Phuah
Arndt Rolfs
Stefan Ropele
Jonathan Rosand
Jaume Roquer
Tatjana Rundek
Ralph L. Sacco
Reinhold Schmidt
Pankaj Sharma
Agnieszka Slowik
Martin Söderholm
Alessandro Sousa
Tara M. Stanne
Daniel Strbian
Turgut Tatlisumak
Vincent Thijs
Achala Vagal
Johan Wasselius
Daniel Woo
Ramin Zand
P. McArdle
Bradford B. Worrall
Christina Jern
Arne G. Lindgren
Jane Maguire
M. Fox
Danilo Bzdok
Ona Wu
Natalia S. Rost
Abstract Stroke represents a considerable burden of disease for both men and women. However, a growing body of literature suggests clinicall… (see more)y relevant sex differences in the underlying causes, presentations and outcomes of acute ischaemic stroke. In a recent study, we reported sex divergences in lesion topographies: specific to women, acute stroke severity was linked to lesions in the left-hemispheric posterior circulation. We here determined whether these sex-specific brain manifestations also affect long-term outcomes. We relied on 822 acute ischaemic patients [age: 64.7 (15.0) years, 39% women] originating from the multi-centre MRI-GENIE study to model unfavourable outcomes (modified Rankin Scale >2) based on acute neuroimaging data in a Bayesian hierarchical framework. Lesions encompassing bilateral subcortical nuclei and left-lateralized regions in proximity to the insula explained outcomes across men and women (area under the curve = 0.81). A pattern of left-hemispheric posterior circulation brain regions, combining left hippocampus, precuneus, fusiform and lingual gyrus, occipital pole and latero-occipital cortex, showed a substantially higher relevance in explaining functional outcomes in women compared to men [mean difference of Bayesian posterior distributions (men – women) = −0.295 (90% highest posterior density interval = −0.556 to −0.068)]. Once validated in prospective studies, our findings may motivate a sex-specific approach to clinical stroke management and hold the promise of enhancing outcomes on a population level.
2022-02-02
Brain Communications (published)
doi.org
Sex-specific lesion pattern of functional outcomes after stroke
Anna K. Bonkhoff
Martin Bretzner
Sungmin Hong
Markus D. Schirmer
Alexander Cohen
Robert W. Regenhardt
Kathleen Donahue
Marco Nardin
Adrian Dalca
Anne-Katrin Giese
Mark R. Etherton
Brandon L. Hancock
Steven J.T. Mocking
Elissa McIntosh
John Attia
Oscar Benavente
Stephen Bevan
John W. Cole
Amanda Donatti
Christoph Griessenauer … (see 39 more)
Laura Heitsch
Lukas Holmegaard
Katarina Jood
Jordi Jimenez-Conde
Steven Kittner
Robin Lemmens
Christopher Levi
Caitrin W. McDonough
James Meschia
Chia-Ling Phuah
Arndt Rolfs
Stefan Ropele
Jonathan Rosand
Jaume Roquer
Tatjana Rundek
Ralph L. Sacco
Reinhold Schmidt
Pankaj Sharma
Agnieszka Slowik
Martin Soederholm
Alessandro Sousa
Tara M. Stanne
Daniel Strbian
Turgut Tatlisumak
Vincent Thijs
Achala Vagal
Johan Wasselius
Daniel Woo
Ramin Zand
Patrick McArdle
Bradford B. Worrall
Christina Jern
Arne G. Lindgren
Jane Maguire
Michael D. Fox
Danilo Bzdok
Ona Wu
Natalia S. Rost
Anna K. Martin Sungmin Markus D. Alexander Robert W. Kathleen L. Marco J. Adrian V. Anne-Katrin Mark R. Brandon L. Steven J. T. Elissa C. John Oscar R. Stephen John W. Amanda Christoph J. Laura Lukas Katarina Jordi Steven J. Robin Christopher R. Caitrin W. James F. Chia-Ling Arndt Stefan Jonathan Jaume Tatjana Ralph L. Reinhold Pankaj Agnieszka Martin Alessandro Tara M. Daniel Turgut Vincent Achala Johan Daniel Ramin Patrick F. Bradford B. Christina Arne G. Jane Michael D. Danilo Ona Natalia S. Bonkhoff
2022-02-02
Brain Communications (published)
doi.org
Estimating causal effects with optimization-based methods: A review and empirical comparison
Martin Cousineau
Vedat Verter
S. Murphy
Joelle Pineau
2022-02-01
ArXiv (preprint)
doi.org
arxiv.org
Evaluation of a prenatal screening decision aid: A mixed methods pilot study.
Titilayo Tatiana Agbadje
Samira Abbasgholizadeh-Rahimi
Mélissa Côté
Andrée-Anne Tremblay
Mariama Penda Diallo
Hélène Elidor
Alex Poulin Herron
Codjo Djignefa Djade
France Légaré
2022-02-01
Patient Education and Counseling (published)
doi.org
How Do Open Source Software Contributors Perceive and Address Usability?: Valued Factors, Practices, and Challenges
Wenting Wang
Jinghui Cheng
Jin Guo
Given the recent changes in the open source software (OSS) landscape, we examined OSS contributors’ current valued factors, practices, and… (see more) challenges concerning usability. Our survey provides insights for OSS practitioners and tool designers to promote a user-centric mindset and improve usability practice in OSS communities.
2022-02-01
IEEE Software (published)
doi.org
arxiv.org
Inferring global-scale temporal latent topics from news reports to predict public health interventions for COVID-19
Zhi Wen
Guido Powell
Imane Chafi
David Buckeridge
Y. K. Li
Yue Li
2022-02-01
Patterns (published)
doi.org
Exploring social inequalities in healthcare trajectories following diagnosis of diabetes: a state sequence analysis of linked survey and administrative data
Rachel McKay
Laurence Letarte
Alain Gillian Lucie David Manon Catherine Anaïs Benoit A Vanasse Bartlett Blais Buckeridge Choinière Hudon
Alain Gillian Lucie David Manon Catherine Anaïs Benoit Alexandre Amélie Pasquale Valérie Marie-Pascale Mike Anne-Marie Marc Josiane Mireille Stéphanie Pierre Annie Isabelle Danielle Denis Jaime André Geneviève Jean-François Roxanne Marc-Antoine Pier Sonia Vanasse
Alain Vanasse
Gillian Bartlett
Lucie Blais
David Buckeridge
Manon Choinière
Catherine Hudon
Anaïs Lacasse
Benoit Lamarche
Alexandre Lebel
Amélie Quesnel-Vallée
Pasquale Roberge
Valérie Émond
Marie-Pascale Pomey
Mike Benigeri
Anne-Marie Cloutier
Marc Dorais … (see 16 more)
Josiane Courteau
Mireille Courteau
Stéphanie Plante
Pierre Cambon
Annie Giguère
Isabelle Leroux
Danielle St-Laurent
Denis Roy
Jaime Borja
André Néron
Geneviève Landry
Jean-François Ethier
Roxanne Dault
Marc-Antoine Côté-Marcil
Pier Tremblay
Sonia Quirion
2022-01-31
BMC Health Services Research (published)
doi.org
Exploring social inequalities in healthcare trajectories following diagnosis of diabetes: a state sequence analysis of linked survey and administrative data
Rachel Marie Mckay
Laurence Letarte
Alain Gillian Lucie David Manon Catherine Anaïs Benoit A Vanasse Bartlett Blais Buckeridge Choinière Hudon
Alain Vanasse
Gillian M. Bartlett
Lucie Blais
David Buckeridge
Manon. Choinière
Catherine. Hudon
Anaïs Lacasse
Benoit Lamarche
Alexandre Lebel
Amélie Quesnel-Vallée
Pasquale Roberge
Valérie Émond
Marie-Pascale Pomey
Mike Benigeri
Anne-Marie Cloutier
Marc Dorais
Josiane Courteau … (see 15 more)
Mireille Courteau
Stéphanie Plante
Pierre Cambon
Annie Giguère
Isabelle Nogueira Leroux
Danielle St-Laurent
Denis Roy
Jaime Borja
A. Néron
Geneviève Landry
J. Éthier
Roxanne Dault
Marc-Antoine Côté-Marcil
Pier Tremblay
Sonia Quirion
2022-01-31
BMC Health Services Research (published)
doi.org