Jiang, Heinrich

29 publications

NeurIPS 2024 SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models Jianyi Zhang, Da-Cheng Juan, Cyrus Rashtchian, Chun-Sung Ferng, Heinrich Jiang, Yiran Chen

ICLR 2022 Churn Reduction via Distillation Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh

ICLR 2022 Scarf: Self-Supervised Contrastive Learning Using Random Feature Corruption Dara Bahri, Heinrich Jiang, Yi Tay, Donald Metzler

AISTATS 2021 Learning the Truth from Only One Side of the Story Heinrich Jiang, Qijia Jiang, Aldo Pacchiano

AISTATS 2021 Stochastic Bandits with Linear Constraints Aldo Pacchiano, Mohammad Ghavamzadeh, Peter Bartlett, Heinrich Jiang

ICML 2021 Active Covering Heinrich Jiang, Afshin Rostamizadeh

NeurIPSW 2021 An Empirical Study of Pre-Trained Vision Models on Out-of-Distribution Generalization Yaodong Yu, Heinrich Jiang, Dara Bahri, Hossein Mobahi, Seungyeon Kim, Ankit Singh Rawat, Andreas Veit, Yi Ma

ICML 2021 Locally Adaptive Label Smoothing Improves Predictive Churn Dara Bahri, Heinrich Jiang

CVPR 2021 MeanShift++: Extremely Fast Mode-Seeking with Applications to Segmentation and Object Tracking Jennifer Jang, Heinrich Jiang

AAAI 2021 Robustness Guarantees for Mode Estimation with an Application to Bandits Aldo Pacchiano, Heinrich Jiang, Michael I. Jordan

AAAI 2020 A General Approach to Fairness with Optimal Transport Silvia Chiappa, Ray Jiang, Tom Stepleton, Aldo Pacchiano, Heinrich Jiang, John Aslanides

ICML 2020 Deep k-NN for Noisy Labels Dara Bahri, Heinrich Jiang, Maya Gupta

NeurIPS 2020 Faster DBSCAN via Subsampled Similarity Queries Heinrich Jiang, Jennifer Jang, Jakub Lacki

AISTATS 2020 Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang, Ofir Nachum

ICML 2019 DBSCAN++: Towards Fast and Scalable Density Clustering Jennifer Jang, Heinrich Jiang

AAAI 2019 Non-Asymptotic Uniform Rates of Consistency for k-NN Regression Heinrich Jiang

JMLR 2019 Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals Andrew Cotter, Heinrich Jiang, Maya Gupta, Serena Wang, Taman Narayan, Seungil You, Karthik Sridharan

AISTATS 2019 Robustness Guarantees for Density Clustering Heinrich Jiang, Jennifer Jang, Ofir Nachum

ICML 2019 Shape Constraints for Set Functions Andrew Cotter, Maya Gupta, Heinrich Jiang, Erez Louidor, James Muller, Tamann Narayan, Serena Wang, Tao Zhu

ICML 2019 Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints Andrew Cotter, Maya Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Wang, Blake Woodworth, Seungil You

ALT 2019 Two-Player Games for Efficient Non-Convex Constrained Optimization Andrew Cotter, Heinrich Jiang, Karthik Sridharan

UAI 2019 Wasserstein Fair Classification Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa

AAAI 2018 Nonparametric Stochastic Contextual Bandits Melody Y. Guan, Heinrich Jiang

ICML 2018 Quickshift++: Provably Good Initializations for Sample-Based Mean Shift Heinrich Jiang, Jennifer Jang, Samory Kpotufe

NeurIPS 2018 To Trust or Not to Trust a Classifier Heinrich Jiang, Been Kim, Melody Guan, Maya Gupta

ICML 2017 Density Level Set Estimation on Manifolds with DBSCAN Heinrich Jiang

AISTATS 2017 Modal-Set Estimation with an Application to Clustering Heinrich Jiang, Samory Kpotufe

NeurIPS 2017 On the Consistency of Quick Shift Heinrich Jiang

ICML 2017 Uniform Convergence Rates for Kernel Density Estimation Heinrich Jiang