← Authors

Madeleine Udell

23 papers · 2016–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (9) 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (36) 🧭 Keyword Pioneer πŸ† Grand Slam πŸ† Keyword Champion (2) 🧬 Topic Evolution πŸ‘‘ Triple Crown πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (77) πŸ”₯ Unstoppable (7) ❓ The Questioner ⚑ Prolific Year (5) πŸ’Ž Century Club (23)

Conferences

NIPS (10) ICML (5) AAAI (2) AISTATS (2) COLT (1) CVPR (1) ICLR (1) JMLR (1)

Top co-authors

Zachary Frangella (4) Yuxuan Zhao (3) Chengrun Yang (3) Wenzhi Gao (3) Jicong Fan (3) Ya-Chi Chu (2) Yinyu Ye (2) Lijun Ding (2) Will Stephenson (2) Shipu Zhao (2)

Keywords

matrix completion (6) convex optimization (4) low-rank approximation (3) matrix factorization (3) gaussian copula (3) low-rank matrix (2) mixed datum (2) online learning (2) stochastic gradient (2) linear convergence (2) stochastic optimization (2) missing data imputation (2) schatten norm (2) nystrΓΆm approximation (2) nonconvex optimization (2) missing value imputation (2) ridge regression (1) uncertainty quantification (1) model selection (1) hyperparameter optimization (1)

Papers

Gradient Methods with Online Scaling COLT 2025
Understanding Fixed Predictions via Confined Regions ICML 2025
Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent ICML 2025
PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates JMLR 2024
Challenges in Training PINNs: A Loss Landscape Perspective ICML 2024
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models ICML 2024
Online Missing Value Imputation and Change Point Detection with the Gaussian Copula AAAI 2022
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets NIPS 2022
Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data NIPS 2022
How Low Can We Go: Trading Memory for Error in Low-Precision Training ICLR 2022
NysADMM: faster composite convex optimization via low-rank approximation ICML 2022
TenIPS: Inverse Propensity Sampling for Tensor Completion AISTATS 2021
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression NIPS 2021
Approximate Cross-Validation with Low-Rank Data in High Dimensions NIPS 2020
Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning AAAI 2020
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula NIPS 2020
Online High Rank Matrix Completion CVPR 2019
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery NIPS 2019
Causal Inference with Noisy and Missing Covariates via Matrix Factorization NIPS 2018
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives NIPS 2018
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data NIPS 2017
Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage AISTATS 2017
The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM NIPS 2016