Alexandre Lacoste

Affiliations:

Université Laval

According to our database¹, Alexandre Lacoste authored at least 53 papers between 2006 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

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

[BibT_eX]

[DOI]

Valentina Zantedeschi

CoRR, 2024

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

[BibT_eX]

[DOI]

Thibault Le Sellier De Chezelles

CoRR, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

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

[BibT_eX]

[DOI]

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

2023

Explaining Visual Counterfactual Explainers.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Tackling Climate Change with Machine Learning.

[BibT_eX]

[DOI]

ACM Comput. Surv., 2023

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

[BibT_eX]

[DOI]

Issam H. Laradji

Perouz Taslakian

Sai Rajeswar

Valentina Zantedeschi

CoRR, 2023

GEO-Bench: Toward Foundation Models for Earth Monitoring.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Choreographer: Learning and Adapting Skills in Imagination.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

From IID to the Independent Mechanisms assumption in continual learning.

[BibT_eX]

[DOI]

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

A General Purpose Neural Architecture for Geospatial Systems.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

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

Typing assumptions improve identification in causal discovery.

[BibT_eX]

[DOI]

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

2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures.

[BibT_eX]

[DOI]

CoRR, 2021

Can Active Learning Preemptively Mitigate Fairness Issues?

[BibT_eX]

[DOI]

Frédéric Branchaud-Charron

CoRR, 2021

Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

2020

Estimating Carbon Emissions of Artificial Intelligence [Opinion].

[BibT_eX]

[DOI]

Alexandra Luccioni

Alexandre Lacoste

Victor Schmidt

IEEE Technol. Soc. Mag., 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

Parmida Atighehchian

Frédéric Branchaud-Charron

Alexandre Lacoste

CoRR, 2020

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

[BibT_eX]

[DOI]

CoRR, 2020

Synbols: Probing Learning Algorithms with Synthetic Datasets.

[BibT_eX]

[DOI]

Alexandre Lacoste

Pau Rodríguez López

Frederic Branchaud-Charron

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Stochastic Neural Network with Kronecker Flow.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

CoRR, 2019

Adaptive Deep Kernel Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Probability Distillation: A Caveat and Alternatives.

[BibT_eX]

[DOI]

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

Hierarchical Importance Weighted Autoencoders.

[BibT_eX]

[DOI]

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

2018

Uncertainty in Multitask Transfer Learning.

[BibT_eX]

[DOI]

CoRR, 2018

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

Neural Autoregressive Flows.

[BibT_eX]

[DOI]

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

Learning Heuristics for the TSP by Policy Gradient.

[BibT_eX]

[DOI]

Louis-Martin Rousseau

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

2017

Deep Prior.

[BibT_eX]

[DOI]

CoRR, 2017

Bayesian Hypernetworks.

[BibT_eX]

[DOI]

CoRR, 2017

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

[BibT_eX]

[DOI]

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

Coarse-to-Fine Question Answering for Long Documents.

[BibT_eX]

[DOI]

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

2016

Hierarchical Question Answering for Long Documents.

[BibT_eX]

[DOI]

CoRR, 2016

PAC-Bayesian Theory Meets Bayesian Inference.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

2014

Sequential Model-Based Ensemble Optimization.

[BibT_eX]

[DOI]

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

Agnostic Bayesian Learning of Ensembles.

[BibT_eX]

[DOI]

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

2012

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

2007

A Supervised Classification Algorithm for Note Onset Detection.

[BibT_eX]

[DOI]

Alexandre Lacoste

Douglas Eck

EURASIP J. Adv. Signal Process., 2007

2006

Predicting genre labels for artist using FreeDB.

[BibT_eX]

James Bergstra

Alexandre Lacoste

Douglas Eck

Proceedings of the ISMIR 2006, 2006

Alexandre Lacoste

Timeline

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