| 2026 | SODA | Feature Selection and Junta Testing are Statistically Equivalent. | Lorenzo Beretta, Nathaniel Harms, Caleb Koch |
| 2025 | FOCS | Computational-Statistical Tradeoffs from NP-hardness. | Guy Blanc, Caleb Koch, Carmen Strassle, Li-Yang Tan |
| 2024 | COLT | Superconstant Inapproximability of Decision Tree Learning. | Caleb Koch, Carmen Strassle, Li-Yang Tan |
| 2024 | FOCS | Fast Decision Tree Learning Solves Hard Coding-Theoretic Problems. | Caleb Koch, Carmen Strassle, Li-Yang Tan |
| 2024 | FOCS | The Sample Complexity of Smooth Boosting and the Tightness of the Hardcore Theorem. | Guy Blanc, Alexandre Hayderi, Caleb Koch, Li-Yang Tan |
| 2023 | ECOOP | Automata Learning with an Incomplete Teacher. | Mark Moeller, Thomas Wiener, Alaia Solko-Breslin, Caleb Koch, Nate Foster, Alexandra Silva |
| 2023 | FOCS | A strong composition theorem for junta complexity and the boosting of property testers. | Guy Blanc, Caleb Koch, Carmen Strassle, Li-Yang Tan |
| 2023 | FOCS | Properly learning decision trees with queries is NP-hard. | Caleb Koch, Carmen Strassle, Li-Yang Tan |
| 2023 | SODA | Superpolynomial lower bounds for decision tree learning and testing. | Caleb Koch, Carmen Strassle, Li-Yang Tan |
| 2022 | ICML | A query-optimal algorithm for finding counterfactuals. | Guy Blanc, Caleb Koch, Jane Lange, Li-Yang Tan |
| 2022 | STOC | The query complexity of certification. | Guy Blanc, Caleb Koch, Jane Lange, Li-Yang Tan |
| 2017 | MASS | Hyperprofile-Based Computation Offloading for Mobile Edge Networks. | Andrew Crutcher, Caleb Koch, Kyle Coleman, Jon Patman, Flavio Esposito, Prasad Calyam |