| Adaptive wavelet distillation from neural networks through interpretations W Ha, C Singh, F Lanusse, S Upadhyayula, B Yu Advances in Neural Information Processing Systems 34, 20669-20682, 2021 | 43 | 2021 |
| Fast and flexible estimation of effective migration surfaces J Marcus, W Ha, RF Barber, J Novembre Elife 10, e61927, 2021 | 39 | 2021 |
| Gradient descent with non-convex constraints: local concavity determines convergence RF Barber, W Ha Information and Inference: A Journal of the IMA 7 (4), 755-806, 2018 | 36 | 2018 |
| Estimating the spectrum in computed tomography via Kullback–Leibler divergence constrained optimization W Ha, EY Sidky, RF Barber, TG Schmidt, X Pan Medical physics 46 (1), 81-92, 2019 | 30 | 2019 |
| An equivalence between critical points for rank constraints versus low-rank factorizations W Ha, H Liu, RF Barber SIAM Journal on Optimization 30 (4), 2927-2955, 2020 | 27 | 2020 |
| Robust PCA with compressed data W Ha, R Foygel Barber Advances in Neural Information Processing Systems 28, 2015 | 23 | 2015 |
| Trimmed conformal prediction for high-dimensional models W Chen, Z Wang, W Ha, RF Barber arXiv preprint arXiv:1611.09933, 2016 | 12 | 2016 |
| Statistical guarantees for local graph clustering W Ha, K Fountoulakis, MW Mahoney Journal of Machine Learning Research 22 (148), 1-54, 2021 | 11 | 2021 |
| Transformation importance with applications to cosmology C Singh, W Ha, F Lanusse, V Boehm, J Liu, B Yu arXiv preprint arXiv:2003.01926, 2020 | 11 | 2020 |
| Alternating minimization and alternating descent over nonconvex sets W Ha, RF Barber arXiv preprint arXiv:1709.04451, 2017 | 10 | 2017 |
| An equivalence between stationary points for rank constraints versus low-rank factorizations W Ha, H Liu, RF Barber arXiv preprint arXiv:1812.00404, 2018 | 6 | 2018 |
| Alternating minimization based framework for simultaneous spectral calibration and image reconstruction in spectral ct W Ha, EY Sidky, RF Barber, TG Schmidt, X Pan 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference …, 2018 | 5 | 2018 |
| Interpreting and improving deep-learning models with reality checks C Singh, W Ha, B Yu International Workshop on Extending Explainable AI Beyond Deep Models and …, 2020 | 3 | 2020 |
| Variance-reduced zeroth-order methods for fine-tuning language models T Gautam, Y Park, H Zhou, P Raman, W Ha arXiv preprint arXiv:2404.08080, 2024 | 2 | 2024 |
| Erratum: Estimating the spectrum in computed tomography via Kullback-Leibler divergence constrained optimization. W Ha, EY Sidky, RF Barber, TG Schmidt, X Pan Medical physics 47 (8), 3772, 2020 | 1 | 2020 |
| X-ray spectral calibration from transmission measurements using Gaussian blur model W Ha, EY Sidky, RF Barber Medical Imaging 2017: Physics of Medical Imaging 10132, 894-898, 2017 | 1 | 2017 |
| Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms K Wu, Y Chen, W Ha, B Yu arXiv preprint arXiv:2309.10301, 2023 | | 2023 |
| The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning N Ghosh, S Frei, W Ha, B Yu arXiv preprint arXiv:2308.03215, 2023 | | 2023 |
| Gradient dynamics of single-neuron autoencoders on orthogonal data N Ghosh, S Frei, W Ha, B Yu 14th Annual Workshop on Optimization for Machine Learning (NeurIPS 2022 …, 2022 | | 2022 |
| High-dimensional estimation and optimization with multiple structured signals W Ha University of Chicago, 2018 | | 2018 |
