| 2022 | ICLR | Scarf: Self-Supervised Contrastive Learning using Random Feature Corruption. | Dara Bahri, Heinrich Jiang, Yi Tay, Donald Metzler |
| 2022 | ICLR | Churn Reduction via Distillation. | Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh |
| 2021 | AAAI | Robustness Guarantees for Mode Estimation with an Application to Bandits. | Aldo Pacchiano, Heinrich Jiang, Michael I. Jordan |
| 2021 | AISTATS | Learning the Truth From Only One Side of the Story. | Heinrich Jiang, Qijia Jiang, Aldo Pacchiano |
| 2021 | AISTATS | Stochastic Bandits with Linear Constraints. | Aldo Pacchiano, Mohammad Ghavamzadeh, Peter L. Bartlett, Heinrich Jiang |
| 2021 | CVPR | MeanShift++: Extremely Fast Mode-Seeking With Applications to Segmentation and Object Tracking. | Jennifer Jang, Heinrich Jiang |
| 2021 | ICML | Locally Adaptive Label Smoothing Improves Predictive Churn. | Dara Bahri, Heinrich Jiang |
| 2021 | ICML | Active Covering. | Heinrich Jiang, Afshin Rostamizadeh |
| 2021 | KDD | Bootstrapping for Batch Active Sampling. | Heinrich Jiang, Maya R. Gupta |
| 2020 | AAAI | A General Approach to Fairness with Optimal Transport. | Silvia Chiappa, Ray Jiang, Tom Stepleton, Aldo Pacchiano, Heinrich Jiang, John Aslanides |
| 2020 | AISTATS | Identifying and Correcting Label Bias in Machine Learning. | Heinrich Jiang, Ofir Nachum |
| 2020 | ICML | Deep k-NN for Noisy Labels. | Dara Bahri, Heinrich Jiang, Maya R. Gupta |
| 2019 | AAAI | Non-Asymptotic Uniform Rates of Consistency for k-NN Regression. | Heinrich Jiang |
| 2019 | AISTATS | Robustness Guarantees for Density Clustering. | Heinrich Jiang, Jennifer Jang, Ofir Nachum |
| 2019 | ALT | Two-Player Games for Efficient Non-Convex Constrained Optimization. | Andrew Cotter, Heinrich Jiang, Karthik Sridharan |
| 2019 | ICML | Shape Constraints for Set Functions. | Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Erez Louidor, James Muller, Taman Narayan, Serena Lutong Wang, Tao Zhu |
| 2019 | ICML | Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. | Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You |
| 2019 | ICML | DBSCAN++: Towards fast and scalable density clustering. | Jennifer Jang, Heinrich Jiang |
| 2019 | UAI | Wasserstein Fair Classification. | Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa |
| 2018 | AAAI | Nonparametric Stochastic Contextual Bandits. | Melody Y. Guan, Heinrich Jiang |
| 2018 | ICML | Quickshift++: Provably Good Initializations for Sample-Based Mean Shift. | Heinrich Jiang, Jennifer Jang, Samory Kpotufe |
| 2017 | AISTATS | Modal-set estimation with an application to clustering. | Heinrich Jiang, Samory Kpotufe |
| 2017 | ICML | Density Level Set Estimation on Manifolds with DBSCAN. | Heinrich Jiang |
| 2017 | ICML | Uniform Convergence Rates for Kernel Density Estimation. | Heinrich Jiang |