Publications

Preprints/In Preparation

• Adaptive Algorithms for Data Summarization. (with Robert Webber and Ethan Epperly). In preparation.

• Function Spaces Without Kernels: Learning Compact Hilbert Space Representations. (with Su Ann Low, Quentin Rommel, Adam J Thorpe, Ufuk Topcu). [arxiv]

• Learning to Attribute Products to Prices in Retail Shelf Images. (with Spencer Young, Luke Green, Stockton Jenkins, and Porter Jenkins). 

2026

• Dirichlet Active Learning. (with Ryan Murray). Accepted for publication at JMLR. [arxiv]

2025

• MALADY: Multiclass Active Learning with Auction Dynamics on Graphs. (with Gokul Bhusal and Ekaterina Rapinchuk). IEEE Transactions on Artificial Intelligence 2025. [arxiv] [ieee]

2024

• CGAP: A Hybrid Contrastive and Graph-based Active Learning Pipeline to Detect Water and Sediment in Multispectral Images. (with Bohan Chen, Jon Schwenk, and Andrea L. Bertozzi). IEEE JSTARS 2024.

• Active Learning of Dynamics Using Prior Domain Knowledge in the Sampling Process. (with Adam Thorpe and Ufuk Topcu). Conference on Dynamics and Control 2024. [arxiv]

2023

• Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering. (with Yijun Dong, Qi Lei, and Rachel Ward). NeuRIPS 2023 poster. [OpenReview]

• Poisson reweighted Laplacian uncertainty sampling for graph-based active learning. (with Jeff Calder). SIAM Journal on Mathematics of Data Science. [arxiv]

• Model Change Active Learning for Graph-Based Semi-Supervised Learning. (with Andrea L. Bertozzi). Springer Journal of Communications on Applied Mathematics and Computation (CAMC). [arxiv]

• Batch active learning for multispectral and hyperspectral image segmentation using similarity graphs. (with Bohan Chen, Andrea Bertozzi, and Jon Schwenk). Springer Journal of Communications on Applied Mathematics and Computation (CAMC).

• Novel Batch Active Learning Approach and Its Application to Synthetic Aperture Radar Datasets. (with James Chapman, Bohan Chen, Zheng Tan, Jeff Calder, and Andrea L. Bertozzi). Proc. SPIE 12520, Algorithms for Synthetic Aperture Radar Imagery XXX, 12520-13 (2 May 2023).

2022

• Efficient and Reliable Overlay Networks for Decentralized Federated Learning. (co-lead author with Yifan Hua, with collaborators Bao Wang, Chen Qian, and Andrea Bertozzi). SIAM Journal on Applied Mathematics}, Volume 82, Number 4, pp. 1558-1586. [journal][arxiv]

• Graph-based active learning for semi-supervised classification of SAR data. (lead author, with collaborators Jack Mauro, Jason Setiadi, Xoaquin Baca, Zhan Shi, Jeff Calder, Andrea L. Bertozzi). Proc. SPIE 12095, Algorithms for Synthetic Aperture Radar Imagery XXIX, 120950C (31 May 2022). [proceedings][arxiv]

2021

• Posterior Consistency of Semi-Supervised Regression on Graphs. (co-lead author with Hao Li, with collaborators Bamdad Hosseini, Andrew Stuart, and Andrea Bertozzi). Inverse Problems. [journal] [arxiv]

2020

• Efficient Graph-Based Active Learning with Probit Likelihood via Gaussian Approximations. (lead author, with collaborators Hao Li and Andrea Bertozzi). ICML 2020 Workshop on Real-World Experiment Design and Active Learning. [arxiv]

2017

• Pre-processing and Classification of Hyperspectral Imagery via Selective Inpainting. (with Victoria Chayes, Rasika Bhalerao, Jerry Luo, Wei Shu, Andrea Bertozzi, Wenzhi Liao, and Stanley Osher). IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages  6195-6199. [ieee]

Dissertation

• Active Learning and Uncertainty In Graph-Based Semi-Supervised Learning. UCLA Dissertation for Mathematics Ph.D. [view]