Alexandre Lacoste

According to our database, Alexandre Lacoste authored at least 54 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Context is Key: A Benchmark for Forecasting with Essential Textual Information.

Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin

CoRR, 2024

InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation.

Gaurav Sahu, Abhay Puri, Juan A. Rodriguez, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vázquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam Hadj Laradji

CoRR, 2024

WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks.

Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier De Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin

CoRR, 2024

WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?

Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, Léo Boisvert, Megh Thakkar, Quentin Cappart, David Vázquez, Nicolas Chapados, Alexandre Lacoste

CoRR, 2024

Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies.

Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien

CoRR, 2024

WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?

Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vázquez, Nicolas Chapados, Alexandre Lacoste

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Explaining Visual Counterfactual Explainers.

Diego A. Velázquez, Pau Rodríguez, Alexandre Lacoste, Issam H. Laradji, F. Xavier Roca, Jordi Gonzàlez

Trans. Mach. Learn. Res., 2023

Tackling Climate Change with Machine Learning.

David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Sasha Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio

ACM Comput. Surv., 2023

Capture the Flag: Uncovering Data Insights with Large Language Models.

Issam H. Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vázquez, Christopher Pal, Alexandre Drouin

CoRR, 2023

GEO-Bench: Toward Foundation Models for Earth Monitoring.

Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan D. Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels.

Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste

Proceedings of the International Conference on Machine Learning, 2023

Choreographer: Learning and Adapting Skills in Imagination.

Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

From IID to the Independent Mechanisms assumption in continual learning.

Oleksiy Ostapenko, Pau Rodríguez, Alexandre Lacoste, Laurent Charlin

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

A General Purpose Neural Architecture for Geospatial Systems.

Nasim Rahaman, Martin Weiss, Frederik Träuble, Francesco Locatello, Alexandre Lacoste, Yoshua Bengio, Chris Pal, Li Erran Li, Bernhard Schölkopf

CoRR, 2022

Unsupervised Model-based Pre-training for Data-efficient Control from Pixels.

Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste

CoRR, 2022

Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA.

Sébastien Lachapelle, Pau Rodríguez, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Typing assumptions improve identification in causal discovery.

Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark.

Alexandre Lacoste, Evan David Sherwin, Hannah Kerner, Hamed Alemohammad, Björn Lütjens, Jeremy Irvin, David Dao, Alex Chang, Mehmet Gunturkun, Alexandre Drouin, Pau Rodríguez, David Vázquez

CoRR, 2021

Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA.

Sébastien Lachapelle, Pau Rodríguez López, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien

CoRR, 2021

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures.

Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer

CoRR, 2021

Can Active Learning Preemptively Mitigate Fairness Issues?

Frédéric Branchaud-Charron, Parmida Atighehchian, Pau Rodríguez, Grace Abuhamad, Alexandre Lacoste

CoRR, 2021

Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations.

Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data.

Oscar Mañas, Alexandre Lacoste, Xavier Giró-i-Nieto, David Vázquez, Pau Rodríguez

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Estimating Carbon Emissions of Artificial Intelligence [Opinion].

Alexandra Luccioni, Alexandre Lacoste, Victor Schmidt

IEEE Technol. Soc. Mag., 2020

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery.

Issam H. Laradji, Pau Rodríguez, Freddie Kalaitzis, David Vázquez, Ross Young, Ed Davey, Alexandre Lacoste

CoRR, 2020

Bayesian active learning for production, a systematic study and a reusable library.

Parmida Atighehchian, Frédéric Branchaud-Charron, Alexandre Lacoste

CoRR, 2020

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

Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin

CoRR, 2020

Synbols: Probing Learning Algorithms with Synthetic Datasets.

Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning.

Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Differentiable Causal Discovery from Interventional Data.

Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Embedding Propagation: Smoother Manifold for Few-Shot Classification.

Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste

Proceedings of the Computer Vision - ECCV 2020, 2020

Stochastic Neural Network with Kronecker Flow.

Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Quantifying the Carbon Emissions of Machine Learning.

Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, Thomas Dandres

CoRR, 2019

Adaptive Deep Kernel Learning.

Prudencio Tossou, Basile Dura, François Laviolette, Mario Marchand, Alexandre Lacoste

CoRR, 2019

Probability Distillation: A Caveat and Alternatives.

Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron C. Courville

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Hierarchical Importance Weighted Autoencoders.

Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Uncertainty in Multitask Transfer Learning.

Alexandre Lacoste, Boris N. Oreshkin, Wonchang Chung, Thomas Boquet, Negar Rostamzadeh, David Krueger

CoRR, 2018

TADAM: Task dependent adaptive metric for improved few-shot learning.

Boris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Improving Explorability in Variational Inference with Annealed Variational Objectives.

Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Neural Autoregressive Flows.

Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Heuristics for the TSP by Policy Gradient.

Michel Deudon, Pierre Cournut, Alexandre Lacoste, Yossiri Adulyasak, Louis-Martin Rousseau

Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2018

2017

Deep Prior.

Alexandre Lacoste, Thomas Boquet, Negar Rostamzadeh, Boris N. Oreshkin, Wonchang Chung, David Krueger

CoRR, 2017

Bayesian Hypernetworks.

David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville

CoRR, 2017

Accurate Supervised and Semi-Supervised Machine Reading for Long Documents.

Izzeddin Gur, Daniel Hewlett, Alexandre Lacoste, Llion Jones

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Coarse-to-Fine Question Answering for Long Documents.

Eunsol Choi, Daniel Hewlett, Jakob Uszkoreit, Illia Polosukhin, Alexandre Lacoste, Jonathan Berant

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Hierarchical Question Answering for Long Documents.

Eunsol Choi, Daniel Hewlett, Alexandre Lacoste, Illia Polosukhin, Jakob Uszkoreit, Jonathan Berant

CoRR, 2016

PAC-Bayesian Theory Meets Bayesian Inference.

Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia.

Daniel Hewlett, Alexandre Lacoste, Llion Jones, Illia Polosukhin, Andrew Fandrianto, Jay Han, Matthew Kelcey, David Berthelot

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2014

Sequential Model-Based Ensemble Optimization.

Alexandre Lacoste, Hugo Larochelle, Mario Marchand, François Laviolette

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Agnostic Bayesian Learning of Ensembles.

Alexandre Lacoste, Mario Marchand, François Laviolette, Hugo Larochelle

Proceedings of the 31th International Conference on Machine Learning, 2014

2012

Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets.

Alexandre Lacoste, François Laviolette, Mario Marchand

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

2011

A PAC-Bayes Sample-compression Approach to Kernel Methods.

Pascal Germain, Alexandre Lacoste, François Laviolette, Mario Marchand, Sara Shanian

Proceedings of the 28th International Conference on Machine Learning, 2011

2007

A Supervised Classification Algorithm for Note Onset Detection.

Alexandre Lacoste, Douglas Eck

EURASIP J. Adv. Signal Process., 2007

2006

Predicting genre labels for artist using FreeDB.

James Bergstra, Alexandre Lacoste, Douglas Eck

Proceedings of the ISMIR 2006, 2006