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Alexandre Lacoste
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- affiliation: Université Laval
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2020 – today
- 2024
- [c29]Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vázquez, Nicolas Chapados, Alexandre Lacoste:
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks? ICML 2024 - [i38]Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien:
Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies. CoRR abs/2401.04890 (2024) - [i37]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:
WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks? CoRR abs/2403.07718 (2024) - [i36]Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier De Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin:
WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks. CoRR abs/2407.05291 (2024) - [i35]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:
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. CoRR abs/2407.06423 (2024) - [i34]Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin:
Context is Key: A Benchmark for Forecasting with Essential Textual Information. CoRR abs/2410.18959 (2024) - 2023
- [j4]David Rolnick
, Priya L. Donti, Lynn H. Kaack
Tackling Climate Change with Machine Learning. ACM Comput. Surv. 55(2): 42:1-42:96 (2023) - [j3]Diego A. Velázquez, Pau Rodríguez, Alexandre Lacoste, Issam H. Laradji, F. Xavier Roca, Jordi Gonzàlez:
Explaining Visual Counterfactual Explainers. Trans. Mach. Learn. Res. 2023 (2023) - [c28]Oleksiy Ostapenko, Pau Rodríguez, Alexandre Lacoste, Laurent Charlin:
From IID to the Independent Mechanisms assumption in continual learning. AAAI Bridge Program 2023: 25-29 - [c27]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar:
Choreographer: Learning and Adapting Skills in Imagination. ICLR 2023 - [c26]Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste:
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels. ICML 2023: 28598-28617 - [c25]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:
GEO-Bench: Toward Foundation Models for Earth Monitoring. NeurIPS 2023 - [i33]Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan David Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Andrew Irvin, David Dao, Hamed Alemohammad
GEO-Bench: Toward Foundation Models for Earth Monitoring. CoRR abs/2306.03831 (2023) - [i32]Issam H. Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vázquez, Christopher Pal, Alexandre Drouin:
Capture the Flag: Uncovering Data Insights with Large Language Models. CoRR abs/2312.13876 (2023) - 2022
- [c24]Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin:
Typing assumptions improve identification in causal discovery. CLeaR 2022: 162-177 - [c23]Sébastien Lachapelle, Pau Rodríguez, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien:
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA. CLeaR 2022: 428-484 - [i31]Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste:
Unsupervised Model-based Pre-training for Data-efficient Control from Pixels. CoRR abs/2209.12016 (2022) - [i30]Nasim Rahaman, Martin Weiss, Frederik Träuble, Francesco Locatello, Alexandre Lacoste, Yoshua Bengio, Chris Pal, Li Erran Li, Bernhard Schölkopf:
A General Purpose Neural Architecture for Geospatial Systems. CoRR abs/2211.02348 (2022) - [i29]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar:
Choreographer: Learning and Adapting Skills in Imagination. CoRR abs/2211.13350 (2022) - 2021
- [c22]Pau Rodríguez
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. ICCV 2021: 1036-1045 - [c21]Oscar Mañas, Alexandre Lacoste, Xavier Giró-i-Nieto, David Vázquez, Pau Rodríguez
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data. ICCV 2021: 9394-9403 - [i28]Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez:
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. CoRR abs/2103.10226 (2021) - [i27]Oscar Mañas, Alexandre Lacoste, Xavier Giró-i-Nieto, David Vázquez, Pau Rodríguez:
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data. CoRR abs/2103.16607 (2021) - [i26]Frédéric Branchaud-Charron, Parmida Atighehchian, Pau Rodríguez, Grace Abuhamad, Alexandre Lacoste:
Can Active Learning Preemptively Mitigate Fairness Issues? CoRR abs/2104.06879 (2021) - [i25]Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer:
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. CoRR abs/2106.07635 (2021) - [i24]Sébastien Lachapelle, Pau Rodríguez López, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien:
Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA. CoRR abs/2107.10098 (2021) - [i23]Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin:
Typing assumptions improve identification in causal discovery. CoRR abs/2107.10703 (2021) - [i22]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:
Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark. CoRR abs/2112.00570 (2021) - 2020
- [j2]Alexandra Luccioni, Alexandre Lacoste, Victor Schmidt:
Estimating Carbon Emissions of Artificial Intelligence [Opinion]. IEEE Technol. Soc. Mag. 39(2): 48-51 (2020) - [c20]Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville:
Stochastic Neural Network with Kronecker Flow. AISTATS 2020: 4184-4194 - [c19]Pau Rodríguez
Embedding Propagation: Smoother Manifold for Few-Shot Classification. ECCV (26) 2020: 121-138 - [c18]Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin:
Differentiable Causal Discovery from Interventional Data. NeurIPS 2020 - [c17]Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin:
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. NeurIPS 2020 - [c16]Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez:
Synbols: Probing Learning Algorithms with Synthetic Datasets. NeurIPS 2020 - [i21]Pau Rodríguez, Issam H. Laradji, Alexandre Drouin
Embedding Propagation: Smoother Manifold for Few-Shot Classification. CoRR abs/2003.04151 (2020) - [i20]Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin:
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. CoRR abs/2003.05856 (2020) - [i19]Parmida Atighehchian, Frédéric Branchaud-Charron, Alexandre Lacoste:
Bayesian active learning for production, a systematic study and a reusable library. CoRR abs/2006.09916 (2020) - [i18]Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin:
Differentiable Causal Discovery from Interventional Data. CoRR abs/2007.01754 (2020) - [i17]Alexandre Lacoste, Pau Rodríguez, Frédéric Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez:
Synbols: Probing Learning Algorithms with Synthetic Datasets. CoRR abs/2009.06415 (2020) - [i16]Issam H. Laradji, Pau Rodríguez, Freddie Kalaitzis, David Vázquez, Ross Young, Ed Davey, Alexandre Lacoste:
Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery. CoRR abs/2011.07369 (2020)
2010 – 2019
- 2019
- [c15]Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville:
Hierarchical Importance Weighted Autoencoders. ICML 2019: 2869-2878 - [c14]Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron C. Courville:
Probability Distillation: A Caveat and Alternatives. UAI 2019: 1212-1221 - [i15]Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville:
Hierarchical Importance Weighted Autoencoders. CoRR abs/1905.04866 (2019) - [i14]Prudencio Tossou, Basile Dura, François Laviolette, Mario Marchand, Alexandre Lacoste:
Adaptive Deep Kernel Learning. CoRR abs/1905.12131 (2019) - [i13]Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville:
Stochastic Neural Network with Kronecker Flow. CoRR abs/1906.04282 (2019) - [i12]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 Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli
Tackling Climate Change with Machine Learning. CoRR abs/1906.05433 (2019) - [i11]Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, Thomas Dandres:
Quantifying the Carbon Emissions of Machine Learning. CoRR abs/1910.09700 (2019) - 2018
- [c13]Michel Deudon, Pierre Cournut, Alexandre Lacoste, Yossiri Adulyasak
Learning Heuristics for the TSP by Policy Gradient. CPAIOR 2018: 170-181 - [c12]Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville:
Neural Autoregressive Flows. ICML 2018: 2083-2092 - [c11]Boris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste:
TADAM: Task dependent adaptive metric for improved few-shot learning. NeurIPS 2018: 719-729 - [c10]Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville:
Improving Explorability in Variational Inference with Annealed Variational Objectives. NeurIPS 2018: 9724-9734 - [i10]Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville:
Neural Autoregressive Flows. CoRR abs/1804.00779 (2018) - [i9]Boris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste:
TADAM: Task dependent adaptive metric for improved few-shot learning. CoRR abs/1805.10123 (2018) - [i8]Alexandre Lacoste, Boris N. Oreshkin, Wonchang Chung, Thomas Boquet, Negar Rostamzadeh, David Krueger:
Uncertainty in Multitask Transfer Learning. CoRR abs/1806.07528 (2018) - [i7]Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville:
Improving Explorability in Variational Inference with Annealed Variational Objectives. CoRR abs/1809.01818 (2018) - 2017
- [c9]Eunsol Choi, Daniel Hewlett, Jakob Uszkoreit, Illia Polosukhin, Alexandre Lacoste, Jonathan Berant:
Coarse-to-Fine Question Answering for Long Documents. ACL (1) 2017: 209-220 - [c8]Izzeddin Gur, Daniel Hewlett, Alexandre Lacoste, Llion Jones:
Accurate Supervised and Semi-Supervised Machine Reading for Long Documents. EMNLP 2017: 2011-2020 - [i6]David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville:
Bayesian Hypernetworks. CoRR abs/1710.04759 (2017) - [i5]Alexandre Lacoste, Thomas Boquet, Negar Rostamzadeh, Boris N. Oreshkin, Wonchang Chung, David Krueger:
Deep Prior. CoRR abs/1712.05016 (2017) - 2016
- [c7]Daniel Hewlett, Alexandre Lacoste, Llion Jones, Illia Polosukhin, Andrew Fandrianto, Jay Han, Matthew Kelcey, David Berthelot:
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia. ACL (1) 2016 - [c6]Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien:
PAC-Bayesian Theory Meets Bayesian Inference. NIPS 2016: 1876-1884 - [i4]Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien:
PAC-Bayesian Theory Meets Bayesian Inference. CoRR abs/1605.08636 (2016) - [i3]Daniel Hewlett, Alexandre Lacoste, Llion Jones, Illia Polosukhin, Andrew Fandrianto, Jay Han, Matthew Kelcey, David Berthelot:
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia. CoRR abs/1608.03542 (2016) - [i2]Eunsol Choi, Daniel Hewlett, Alexandre Lacoste, Illia Polosukhin, Jakob Uszkoreit, Jonathan Berant:
Hierarchical Question Answering for Long Documents. CoRR abs/1611.01839 (2016) - 2014
- [c5]Alexandre Lacoste, Mario Marchand, François Laviolette, Hugo Larochelle:
Agnostic Bayesian Learning of Ensembles. ICML 2014: 611-619 - [c4]Alexandre Lacoste, Hugo Larochelle, Mario Marchand, François Laviolette:
Sequential Model-Based Ensemble Optimization. UAI 2014: 440-448 - [i1]Alexandre Lacoste, Hugo Larochelle, François Laviolette, Mario Marchand:
Sequential Model-Based Ensemble Optimization. CoRR abs/1402.0796 (2014) - 2012
- [c3]Alexandre Lacoste, François Laviolette, Mario Marchand:
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets. AISTATS 2012: 665-675 - 2011
- [c2]Pascal Germain, Alexandre Lacoste, François Laviolette, Mario Marchand, Sara Shanian:
A PAC-Bayes Sample-compression Approach to Kernel Methods. ICML 2011: 297-304
2000 – 2009
- 2007
- [j1]Alexandre Lacoste, Douglas Eck:
A Supervised Classification Algorithm for Note Onset Detection. EURASIP J. Adv. Signal Process. 2007 (2007) - 2006
- [c1]James Bergstra, Alexandre Lacoste, Douglas Eck:
Predicting genre labels for artist using FreeDB. ISMIR 2006: 85-88
Coauthor Index
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