A strong composition theorem for junta complexity and the boosting of property testers. - Guy Blanc; Caleb Koch 001; Carmen Strassle; Li-Yang Tan (FOCS, 2023)

Properly learning decision trees with queries is NP-hard. - Caleb Koch 001; Carmen Strassle; Li-Yang Tan (FOCS, 2023)

Certification with an NP Oracle. - Guy Blanc; Caleb Koch 001; Jane Lange; Carmen Strassle; Li-Yang Tan (ITCS, 2023)

Superpolynomial lower bounds for decision tree learning and testing. - Caleb Koch 001; Carmen Strassle; Li-Yang Tan (SODA, 2023)

A Strong Direct Sum Theorem for Distributional Query Complexity. - Guy Blanc; Caleb Koch 001; Carmen Strassle; Li-Yang Tan (CCC, 2024)

Superconstant Inapproximability of Decision Tree Learning. - Caleb Koch 001; Carmen Strassle; Li-Yang Tan (COLT, 2024)

Fast Decision Tree Learning Solves Hard Coding-Theoretic Problems. - Caleb Koch 001; Carmen Strassle; Li-Yang Tan (FOCS, 2024)

A Distributional-Lifting Theorem for PAC Learning. - Guy Blanc; Jane Lange; Carmen Strassle; Li-Yang Tan (COLT, 2025)

Computational-Statistical Tradeoffs from NP-hardness. - Guy Blanc; Caleb Koch 001; Carmen Strassle; Li-Yang Tan (CoRR, 2025)