Multitask Learning via Shared Features: Algorithms and Hardness. - Konstantina Bairaktari; Guy Blanc; Li-Yang Tan; Jonathan R. Ullman; Lydia Zakynthinou (COLT, 2023)

Metalearning with Very Few Samples Per Task. - Maryam Aliakbarpour; Konstantina Bairaktari; Gavin Brown 003; Adam Smith 006; Jonathan R. Ullman (CoRR, 2023)

Fair and Useful Cohort Selection. - Konstantina Bairaktari; Paul Langton; Huy L. Nguyen; Niklas Smedemark-Margulies; Jonathan R. Ullman (Trans. Mach. Learn. Res., 2023)

Metalearning with Very Few Samples Per Task. - Maryam Aliakbarpour; Konstantina Bairaktari; Gavin Brown 003; Adam Smith 006; Nathan Srebro; Jonathan R. Ullman (COLT, 2024)

Privacy in Metalearning and Multitask Learning: Modeling and Separations. - Maryam Aliakbarpour; Konstantina Bairaktari; Adam Smith 006; Marika Swanberg; Jonathan R. Ullman (AISTATS, 2025)

Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage. - Konstantina Bairaktari; Jiayun Wu; Zhiwei Steven Wu (CoRR, 2025)