Alexandre Lacoste

88 papers A* 19A 4B 1Journal 55Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CUBE: A Standard for Unifying Agent Benchmarks. CoRR Alexandre Lacoste, Nicolas Gontier, Oleh Shliazhko, Aman Jaiswal, Kusha Sareen, Shailesh Nanisetty, Joan Cabezas, Manuel Del Verme, Omar G. Younis, Simone Baratta, Matteo Avalle, Imene Kerboua, Xing Han Lù, Elron Bandel, Michal Shmueli-Scheuer, Asaf Yehudai, Leshem Choshen, Jonathan Lebensold, Sean Hughes, Massimo Caccia, Alexandre Drouin, Siva Reddy, Tao Yu, Yu Su, Graham Neubig, Dawn Song
2026	J	`jnl`	Privileged Information Distillation for Language Models. CoRR Emiliano Penaloza, Dheeraj Vattikonda, Nicolas Gontier, Alexandre Lacoste, Laurent Charlin, Massimo Caccia
2025	A*	`conf`	Context is Key: A Benchmark for Forecasting with Essential Textual Information. ICML Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin
2025	J	`jnl`	DoomArena: A framework for Testing AI Agents Against Evolving Security Threats. CoRR Léo Boisvert, Mihir Bansal, Chandra Kiran Reddy Evuru, Gabriel Huang, Abhay Puri, Avinandan Bose, Maryam Fazel, Quentin Cappart, Jason Stanley, Alexandre Lacoste, Alexandre Drouin, Krishnamurthy Dvijotham
2025	—	`conf`	EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision. WACV (Workshops) Diego A. Velázquez, Pau Rodríguez López, Sergio Alonso, Josep M. Gonfaus, Jordi Gonzàlez, Gerardo Richarte, Javier Marín, Yoshua Bengio, Alexandre Lacoste
2025	J	`jnl`	EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision. CoRR Diego A. Velázquez, Pau Rodríguez López, Sergio Alonso, Josep M. Gonfaus, Jordi Gonzàlez, Gerardo Richarte, Javier Marín, Yoshua Bengio, Alexandre Lacoste
2025	J	`jnl`	FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agents. CoRR Imene Kerboua, Sahar Omidi Shayegan, Megh Thakkar, Xing Han Lù, Léo Boisvert, Massimo Caccia, Jérémy Espinas, Alexandre Aussem, Véronique Eglin, Alexandre Lacoste
2025	J	`jnl`	How to Train Your LLM Web Agent: A Statistical Diagnosis. CoRR Dheeraj Vattikonda, Santhoshi Ravichandran, Emiliano Penaloza, Hadi Nekoei, Megh Thakkar, Thibault Le Sellier de Chezelles, Nicolas Gontier, Miguel Muñoz-Mármol, Sahar Omidi Shayegan, Stefania Raimondo, Xue Liu, Alexandre Drouin, Laurent Charlin, Alexandre Piché, Alexandre Lacoste, Massimo Caccia
2025	J	`jnl`	Indirect Prompt Injections: Are Firewalls All You Need, or Stronger Benchmarks? CoRR Rishika Bhagwatkar, Kevin Kasa, Abhay Puri, Gabriel Huang, Irina Rish, Graham W. Taylor, Krishnamurthy Dj Dvijotham, Alexandre Lacoste
2025	A*	`conf`	InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. ICLR Gaurav Sahu, Abhay Puri, Juan A. Rodríguez, Amirhossein Abaskohi, Mohammad Chegini, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vázquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam H. Laradji
2025	J	`jnl`	Just-in-time Episodic Feedback Hinter: Leveraging Offline Knowledge to Improve LLM Agents Adaptation. CoRR Hadi Nekoei, Aman Jaiswal, Patrice Béchard, Oleh Shliazhko, Orlando Marquez Ayala, Mathieu Reymond, Massimo Caccia, Alexandre Drouin, Sarath Chandar, Alexandre Lacoste
2025	J	`jnl`	LineRetriever: Planning-Aware Observation Reduction for Web Agents. CoRR Imene Kerboua, Sahar Omidi Shayegan, Megh Thakkar, Xing Han Lù, Massimo Caccia, Véronique Eglin, Alexandre Aussem, Jérémy Espinas, Alexandre Lacoste
2025	J	`jnl`	Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain. CoRR Léo Boisvert, Abhay Puri, Chandra Kiran Reddy Evuru, Nicolas Chapados, Quentin Cappart, Alexandre Lacoste, Krishnamurthy Dj Dvijotham, Alexandre Drouin
2025	J	`jnl`	The BrowserGym Ecosystem for Web Agent Research. Trans. Mach. Learn. Res. Thibault Le Sellier de Chezelles, Maxime Gasse, Alexandre Lacoste, Massimo Caccia, Alexandre Drouin, Léo Boisvert, Megh Thakkar, Tom Marty, Rim Assouel, Sahar Omidi Shayegan, Lawrence Keunho Jang, Xing Han Lù, Ori Yoran, Dehan Kong, Frank F. Xu, Siva Reddy, Graham Neubig, Quentin Cappart, Russ Salakhutdinov, Nicolas Chapados
2024	J	`jnl`	Context is Key: A Benchmark for Forecasting with Essential Textual Information. CoRR Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin
2024	J	`jnl`	GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks. CoRR Muhammad Sohail Danish, Muhammad Akhtar Munir, Syed Roshaan Ali Shah, Kartik Kuckreja, Fahad Shahbaz Khan, Paolo Fraccaro, Alexandre Lacoste, Salman H. Khan
2024	J	`jnl`	InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. CoRR Gaurav Sahu, Abhay Puri, Juan A. Rodríguez, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vázquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam Hadj Laradji
2024	J	`jnl`	Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies. CoRR Sébastien Lachapelle, Pau Rodríguez López, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2024	J	`jnl`	The BrowserGym Ecosystem for Web Agent Research. CoRR Thibault Le Sellier de Chezelles, Maxime Gasse, Alexandre Drouin, Massimo Caccia, Léo Boisvert, Megh Thakkar, Tom Marty, Rim Assouel, Sahar Omidi Shayegan, Lawrence Keunho Jang, Xing Han Lù, Ori Yoran, Dehan Kong, Frank F. Xu, Siva Reddy, Quentin Cappart, Graham Neubig, Ruslan Salakhutdinov, Nicolas Chapados, Alexandre Lacoste
2024	A*	`conf`	WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks. NeurIPS Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier de Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin
2024	J	`jnl`	WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks. CoRR Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier de Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin
2024	J	`jnl`	WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks? CoRR 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
2024	A*	`conf`	WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks? ICML Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vázquez, Nicolas Chapados, Alexandre Lacoste
2023	J	`jnl`	Capture the Flag: Uncovering Data Insights with Large Language Models. CoRR Issam H. Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vázquez, Christopher Pal, Alexandre Drouin
2023	A*	`conf`	Choreographer: Learning and Adapting Skills in Imagination. ICLR Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar
2023	J	`jnl`	Explaining Visual Counterfactual Explainers. Trans. Mach. Learn. Res. Diego A. Velázquez, Pau Rodríguez, Alexandre Lacoste, Issam H. Laradji, F. Xavier Roca, Jordi Gonzàlez
2023	—	`conf`	From IID to the Independent Mechanisms assumption in continual learning. AAAI Bridge Program Oleksiy Ostapenko, Pau Rodríguez, Alexandre Lacoste, Laurent Charlin
2023	A*	`conf`	GEO-Bench: Toward Foundation Models for Earth Monitoring. NeurIPS 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 J. Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu
2023	J	`jnl`	GEO-Bench: Toward Foundation Models for Earth Monitoring. CoRR Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan David Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Andrew Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava J. Newman, Yoshua Bengio, Stefano Ermon, Xiao Xiang Zhu
2023	A*	`conf`	Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels. ICML Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste
2023	J	`jnl`	Tackling Climate Change with Machine Learning. ACM Comput. Surv. 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
2022	J	`jnl`	A General Purpose Neural Architecture for Geospatial Systems. CoRR Nasim Rahaman, Martin Weiss, Frederik Träuble, Francesco Locatello, Alexandre Lacoste, Yoshua Bengio, Chris Pal, Li Erran Li, Bernhard Schölkopf
2022	J	`jnl`	Choreographer: Learning and Adapting Skills in Imagination. CoRR Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar
2022	—	`conf`	Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA. CLeaR Sébastien Lachapelle, Pau Rodríguez, Yash Sharma, Katie Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2022	—	`conf`	Typing assumptions improve identification in causal discovery. CLeaR Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin
2022	J	`jnl`	Unsupervised Model-based Pre-training for Data-efficient Control from Pixels. CoRR Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste
2021	A*	`conf`	Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. ICCV Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez
2021	J	`jnl`	Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. CoRR Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam H. Laradji, Laurent Charlin, David Vázquez
2021	J	`jnl`	Can Active Learning Preemptively Mitigate Fairness Issues? CoRR Frédéric Branchaud-Charron, Parmida Atighehchian, Pau Rodríguez, Grace Abuhamad, Alexandre Lacoste
2021	J	`jnl`	Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA. CoRR Sébastien Lachapelle, Pau Rodríguez López, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
2021	A*	`conf`	Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data. ICCV Oscar Mañas, Alexandre Lacoste, Xavier Giró-i-Nieto, David Vázquez, Pau Rodríguez
2021	J	`jnl`	Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data. CoRR Oscar Mañas, Alexandre Lacoste, Xavier Giró-i-Nieto, David Vázquez, Pau Rodríguez
2021	J	`jnl`	Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark. CoRR 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
2021	J	`jnl`	Typing assumptions improve identification in causal discovery. CoRR Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin
2021	J	`jnl`	Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. CoRR Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer
2020	J	`jnl`	Bayesian active learning for production, a systematic study and a reusable library. CoRR Parmida Atighehchian, Frédéric Branchaud-Charron, Alexandre Lacoste
2020	J	`jnl`	Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery. CoRR Issam H. Laradji, Pau Rodríguez, Freddie Kalaitzis, David Vázquez, Ross Young, Ed Davey, Alexandre Lacoste
2020	A*	`conf`	Differentiable Causal Discovery from Interventional Data. NeurIPS Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
2020	J	`jnl`	Differentiable Causal Discovery from Interventional Data. CoRR Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
2020	—	`conf`	Embedding Propagation: Smoother Manifold for Few-Shot Classification. ECCV (26) Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste
2020	J	`jnl`	Embedding Propagation: Smoother Manifold for Few-Shot Classification. CoRR Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste
2020	J	`jnl`	Estimating Carbon Emissions of Artificial Intelligence [Opinion]. IEEE Technol. Soc. Mag. Alexandra Luccioni, Alexandre Lacoste, Victor Schmidt
2020	A*	`conf`	Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. NeurIPS Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
2020	J	`jnl`	Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. CoRR Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
2020	A	`conf`	Stochastic Neural Network with Kronecker Flow. AISTATS Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville
2020	A*	`conf`	Synbols: Probing Learning Algorithms with Synthetic Datasets. NeurIPS Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez
2020	J	`jnl`	Synbols: Probing Learning Algorithms with Synthetic Datasets. CoRR Alexandre Lacoste, Pau Rodríguez, Frédéric Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez
2019	J	`jnl`	Adaptive Deep Kernel Learning. CoRR Prudencio Tossou, Basile Dura, François Laviolette, Mario Marchand, Alexandre Lacoste
2019	A*	`conf`	Hierarchical Importance Weighted Autoencoders. ICML Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville
2019	J	`jnl`	Hierarchical Importance Weighted Autoencoders. CoRR Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville
2019	A	`conf`	Probability Distillation: A Caveat and Alternatives. UAI Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron C. Courville
2019	J	`jnl`	Quantifying the Carbon Emissions of Machine Learning. CoRR Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, Thomas Dandres
2019	J	`jnl`	Stochastic Neural Network with Kronecker Flow. CoRR Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville
2019	J	`jnl`	Tackling Climate Change with Machine Learning. CoRR 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, Konrad P. Körding, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio
2018	A*	`conf`	Improving Explorability in Variational Inference with Annealed Variational Objectives. NeurIPS Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville
2018	J	`jnl`	Improving Explorability in Variational Inference with Annealed Variational Objectives. CoRR Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville
2018	B	`conf`	Learning Heuristics for the TSP by Policy Gradient. CPAIOR Michel Deudon, Pierre Cournut, Alexandre Lacoste, Yossiri Adulyasak, Louis-Martin Rousseau
2018	A*	`conf`	Neural Autoregressive Flows. ICML Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville
2018	J	`jnl`	Neural Autoregressive Flows. CoRR Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville
2018	A*	`conf`	TADAM: Task dependent adaptive metric for improved few-shot learning. NeurIPS Boris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste
2018	J	`jnl`	TADAM: Task dependent adaptive metric for improved few-shot learning. CoRR Boris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste
2018	J	`jnl`	Uncertainty in Multitask Transfer Learning. CoRR Alexandre Lacoste, Boris N. Oreshkin, Wonchang Chung, Thomas Boquet, Negar Rostamzadeh, David Krueger
2017	A*	`conf`	Accurate Supervised and Semi-Supervised Machine Reading for Long Documents. EMNLP Izzeddin Gur, Daniel Hewlett, Alexandre Lacoste, Llion Jones
2017	J	`jnl`	Bayesian Hypernetworks. CoRR David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville
2017	—	`conf`	Coarse-to-Fine Question Answering for Long Documents. ACL (1) Eunsol Choi, Daniel Hewlett, Jakob Uszkoreit, Illia Polosukhin, Alexandre Lacoste, Jonathan Berant
2017	J	`jnl`	Deep Prior. CoRR Alexandre Lacoste, Thomas Boquet, Negar Rostamzadeh, Boris N. Oreshkin, Wonchang Chung, David Krueger
2016	J	`jnl`	Hierarchical Question Answering for Long Documents. CoRR Eunsol Choi, Daniel Hewlett, Alexandre Lacoste, Illia Polosukhin, Jakob Uszkoreit, Jonathan Berant
2016	—	`conf`	PAC-Bayesian Theory Meets Bayesian Inference. NIPS Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien
2016	J	`jnl`	PAC-Bayesian Theory Meets Bayesian Inference. CoRR Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien
2016	—	`conf`	WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia. ACL (1) Daniel Hewlett, Alexandre Lacoste, Llion Jones, Illia Polosukhin, Andrew Fandrianto, Jay Han, Matthew Kelcey, David Berthelot
2016	J	`jnl`	WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia. CoRR Daniel Hewlett, Alexandre Lacoste, Llion Jones, Illia Polosukhin, Andrew Fandrianto, Jay Han, Matthew Kelcey, David Berthelot
2014	A*	`conf`	Agnostic Bayesian Learning of Ensembles. ICML Alexandre Lacoste, Mario Marchand, François Laviolette, Hugo Larochelle
2014	A	`conf`	Sequential Model-Based Ensemble Optimization. UAI Alexandre Lacoste, Hugo Larochelle, Mario Marchand, François Laviolette
2014	J	`jnl`	Sequential Model-Based Ensemble Optimization. CoRR Alexandre Lacoste, Hugo Larochelle, François Laviolette, Mario Marchand
2012	A	`conf`	Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets. AISTATS Alexandre Lacoste, François Laviolette, Mario Marchand
2011	A*	`conf`	A PAC-Bayes Sample-compression Approach to Kernel Methods. ICML Pascal Germain, Alexandre Lacoste, François Laviolette, Mario Marchand, Sara Shanian
2007	J	`jnl`	A Supervised Classification Algorithm for Note Onset Detection. EURASIP J. Adv. Signal Process. Alexandre Lacoste, Douglas Eck
2006	—	`conf`	Predicting genre labels for artist using FreeDB. ISMIR James Bergstra, Alexandre Lacoste, Douglas Eck