Publications

2023

Learning with Explanation Constraints
Rattana Pukdee*, Dylan Sam*, J. Zico Kolter, Maria-Florina Balcan, and Pradeep Ravikumar
Under Review & ICLR TrustML Workshop, 2023

Label Propagation with Weak Supervision
Rattana Pukdee*, Dylan Sam*, Maria-Florina Balcan, and Pradeep Ravikumar
International Conference on Learning Representations (ICLR), 2023
[pdf, code]

Losses over Labels: Weakly Supervised Learning via Direct Loss Construction
Dylan Sam and J. Zico Kolter
AAAI Conference on Artificial Intelligence, 2023
[pdf, code]

2022

Improving self-supervised representation learning via sequential adversarial masking
Dylan Sam, Min Bai, Tristan McKinney, and Li Erran Li
NeurIPS 2022 Workshop: Self-Supervised Learning - Theory and Practice, 2022
[pdf]

2021

Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees
Alessio Mazzetto*, Cyrus Cousins*, Dylan Sam, Stephen H Bach, and Eli Upfal
International Conference on Machine Learning (ICML), 2021
[pdf, code]

Semi-Supervised Aggregation of Dependent Weak Supervision Sources with Performance Guarantees
Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, and Stephen H Bach
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
[pdf, code]

Learning from Dependent Weak Supervision Sources
Dylan Sam
Undergraduate Honors Thesis, 2021
[pdf]

Automated Data Accountability for the Mars Science Laboratory
Ryan Alimo, Dylan Sam, Dounia Lakhmiri, Brian Kahovec, and Dariush Divsalar
IEEE Aerospace Conference, 2021
[pdf, code]

2020

Hierarchical Clustering Analysis of Spectral Fingerprints for Cheminformatics
Dylan Sam and Brenda M Rubenstein
NeurIPS Machine Learning for Molecules Workshop, 2020
[pdf]