February 2025
Preserving Clusters in Prompt Learning for Unsupervised Domain
Adaptation
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,
2025.
February 2025
ACCESS: A Benchmark for Abstract Causal Event Discovery and Reasoning
Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics, 2025.
ACCESS: A Benchmark for Abstract Causal Event Discovery and Reasoning
Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics, 2025.
February 2024
Optimal Transport for Structure Learning Under Missing Data
Proceedings of the 41st International Conference on Machine Learning, 2024.
Optimal Transport for Structure Learning Under Missing Data
Proceedings of the 41st International Conference on Machine Learning, 2024.
February 2024
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport.
Proceedings of the 41st International Conference on Machine Learning, 2024.
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport.
Proceedings of the 41st International Conference on Machine Learning, 2024.
May 2023
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.
Best Student Research Paper Award
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.
Best Student Research Paper Award
January 2023
An Additive Instance-Wise Approach to Multi-class Model Interpretation
Proceedings of the 11th International Conference on Learning Representations, 2023.
An Additive Instance-Wise Approach to Multi-class Model Interpretation
Proceedings of the 11th International Conference on Learning Representations, 2023.
May 2021
How Machines Are Taught
Leaving those mathematical fuzz aside, I am urged to take one step away from the mainstream and rethink how machines learn.
How Machines Are Taught
Leaving those mathematical fuzz aside, I am urged to take one step away from the mainstream and rethink how machines learn.
April 2021
Assumptions of Linear Models
I explain the assumptions underlying Linear Regression, an old-school machine learning model but widely used today.
Assumptions of Linear Models
I explain the assumptions underlying Linear Regression, an old-school machine learning model but widely used today.