Madeleine Udell

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 95

Top Venues

CoRR

NeurIPS

KDD

SIAM J. Math. Data Sci.

Publications

Pratik Rathore, Weimu Lei, Zachary Frangella, Lu Lu, Madeleine Udell
Challenges in Training PINNs: A Loss Landscape Perspective. CoRR (2024)
Mike Van Ness, Madeleine Udell
Interpretable Prediction and Feature Selection for Survival Analysis. CoRR (2024)
Yuxuan Zhao, Madeleine Udell
gcimpute: A Package for Missing Data Imputation. J. Stat. Softw. 108 (4) (2024)
Pratik Rathore, Zachary Frangella, Madeleine Udell
Have ASkotch: Fast Methods for Large-scale, Memory-constrained Kernel Ridge Regression. CoRR (2024)
Ali AhmadiTeshnizi, Wenzhi Gao, Herman Brunborg, Shayan Talaei, Madeleine Udell
OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale. CoRR (2024)
Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models. CoRR (2024)
Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell
The Missing Indicator Method: From Low to High Dimensions. KDD (2023)
Zachary Frangella, Joel A. Tropp, Madeleine Udell
Randomized Nyström Preconditioning. SIAM J. Matrix Anal. Appl. 44 (2) (2023)
Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister
Data-Efficient and Interpretable Tabular Anomaly Detection. KDD (2023)
Sarah J. Zhang, Samuel Florin, Ariel N. Lee, Eamon Niknafs, Andrei Marginean, Annie Wang, Keith Tyser, Zad Chin, Yann Hicke, Nikhil Singh, Madeleine Udell, Yoon Kim, Tonio Buonassisi, Armando Solar-Lezama, Iddo Drori
Exploring the MIT Mathematics and EECS Curriculum Using Large Language Models. CoRR (2023)
Mike Van Ness, Tomas M. Bosschieter, Natasha Din, Andrew Ambrosy, Alexander Sandhu, Madeleine Udell
Interpretable Survival Analysis for Heart Failure Risk Prediction. CoRR (2023)
Mike Van Ness, Tomas M. Bosschieter, Natasha Din, Andrew Ambrosy, Alexander Sandhu, Madeleine Udell
Interpretable Survival Analysis for Heart Failure Risk Prediction. ML4H@NeurIPS (2023)
Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell
OptiMUS: Optimization Modeling Using MIP Solvers and large language models. CoRR (2023)
Jicong Fan, Lijun Ding, Chengrun Yang, Zhao Zhang, Madeleine Udell
Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization for Low-Rank Tensor Completion and Tensor Robust Principal Component Analysis. Trans. Mach. Learn. Res. 2023 (2023)
Iddo Drori, Sarah J. Zhang, Reece Shuttleworth, Sarah Zhang, Keith Tyser, Zad Chin, Pedro Lantigua, Saisamrit Surbehera, Gregory Hunter, Derek Austin, Leonard Tang, Yann Hicke, Sage Simhon, Sathwik Karnik, Darnell Granberry, Madeleine Udell
From Human Days to Machine Seconds: Automatically Answering and Generating Machine Learning Final Exams. KDD (2023)
Wenzhi Gao, Zhaonan Qu, Madeleine Udell, Yinyu Ye
Scalable Approximate Optimal Diagonal Preconditioning. CoRR (2023)
Zachary Frangella, Pratik Rathore, Shipu Zhao, Madeleine Udell
PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates. CoRR (2023)
Lijun Ding, Madeleine Udell
A strict complementarity approach to error bound and sensitivity of solution of conic programs. Optim. Lett. 17 (7) (2023)
Yuxuan Zhao, Eric Landgrebe, Eliot Shekhtman, Madeleine Udell
Online Missing Value Imputation and Change Point Detection with the Gaussian Copula. AAAI (2022)
Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell
How Low Can We Go: Trading Memory for Error in Low-Precision Training. ICLR (2022)
Shipu Zhao, Zachary Frangella, Madeleine Udell
NysADMM: faster composite convex optimization via low-rank approximation. ICML (2022)
Zachary Frangella, Pratik Rathore, Shipu Zhao, Madeleine Udell
SketchySGD: Reliable Stochastic Optimization via Robust Curvature Estimates. CoRR (2022)
Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets. NeurIPS (2022)
Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister
Data-Efficient and Interpretable Tabular Anomaly Detection. CoRR (2022)
Yuxuan Zhao, Alex Townsend, Madeleine Udell
Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data. NeurIPS (2022)
Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell
The Missing Indicator Method: From Low to High Dimensions. CoRR (2022)
Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang
Resource-Constrained Neural Architecture Search on Tabular Datasets. CoRR (2022)
Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister
Towards Group Robustness in the presence of Partial Group Labels. CoRR (2022)
Brian Liu, Miaolan Xie, Haoyue Yang, Madeleine Udell
ControlBurn: Nonlinear Feature Selection with Sparse Tree Ensembles. CoRR (2022)
Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell
How Low Can We Go: Trading Memory for Error in Low-Precision Training. CoRR (2021)
William T. Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression. CoRR (2021)
Chengrun Yang, Lijun Ding, Ziyang Wu, Madeleine Udell
TenIPS: Inverse Propensity Sampling for Tensor Completion. CoRR (2021)
Yiming Sun, Yang Guo, Joel A. Tropp, Madeleine Udell
Tensor Random Projection for Low Memory Dimension Reduction. CoRR (2021)
Brian Liu, Miaolan Xie, Madeleine Udell
ControlBurn: Feature Selection by Sparse Forests. CoRR (2021)
Lijun Ding, Alp Yurtsever, Volkan Cevher, Joel A. Tropp, Madeleine Udell
An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity. SIAM J. Optim. 31 (4) (2021)
Zachary Frangella, Joel A. Tropp, Madeleine Udell
Randomized Nyström Preconditioning. CoRR (2021)
Nikhil Singh, Brandon Kates, Jeff Mentch, Anant Kharkar, Madeleine Udell, Iddo Drori
Privileged Zero-Shot AutoML. CoRR (2021)
Brian Liu, Miaolan Xie, Madeleine Udell
ControlBurn: Feature Selection by Sparse Forests. KDD (2021)
Alp Yurtsever, Joel A. Tropp, Olivier Fercoq, Madeleine Udell, Volkan Cevher
Scalable Semidefinite Programming. SIAM J. Math. Data Sci. 3 (1) (2021)
Jicong Fan, Chengrun Yang, Madeleine Udell
Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering. IEEE Trans. Signal Process. 69 (2021)
Ramchandran Muthukumar, Drew P. Kouri, Madeleine Udell
Randomized Sketching Algorithms for Low-Memory Dynamic Optimization. SIAM J. Optim. 31 (2) (2021)
Lijun Ding, Madeleine Udell
On the Simplicity and Conditioning of Low Rank Semidefinite Programs. SIAM J. Optim. 31 (4) (2021)
William T. Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression. NeurIPS (2021)
Chengrun Yang, Lijun Ding, Ziyang Wu, Madeleine Udell
TenIPS: Inverse Propensity Sampling for Tensor Completion. AISTATS (2021)
Mike Van Ness, Madeleine Udell
CDF Normalization for Controlling the Distribution of Hidden Nodes. ICBINB@NeurIPS (2021)
William T. Stephenson, Madeleine Udell, Tamara Broderick
Approximate Cross-Validation with Low-Rank Data in High Dimensions. CoRR (2020)
Nathan Kallus, Madeleine Udell
Dynamic Assortment Personalization in High Dimensions. Oper. Res. 68 (4) (2020)
Yuxuan Zhao, Madeleine Udell
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula. NeurIPS (2020)
Lijun Ding, Madeleine Udell
On the regularity and conditioning of low rank semidefinite programs. CoRR (2020)
Elizabeth A. Ricci, Madeleine Udell, Ross A. Knepper
An Information-Theoretic Approach to Persistent Environment Monitoring Through Low Rank Model Based Planning and Prediction. CoRR (2020)
Iddo Drori, Anant Kharkar, William R. Sickinger, Brandon Kates, Qiang Ma, Suwen Ge, Eden Dolev, Brenda Dietrich, David P. Williamson, Madeleine Udell
Learning to Solve Combinatorial Optimization Problems on Real-World Graphs in Linear Time. ICMLA (2020)
Lijun Ding, Jicong Fan, Madeleine Udell
kFW: A Frank-Wolfe style algorithm with stronger subproblem oracles. CoRR (2020)
Yiming Sun, Yang Guo, Charlene Luo, Joel A. Tropp, Madeleine Udell
Low-Rank Tucker Approximation of a Tensor from Streaming Data. SIAM J. Math. Data Sci. 2 (4) (2020)
Chengrun Yang, Jicong Fan, Ziyang Wu, Madeleine Udell
AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space. KDD (2020)
Yuxuan Zhao, Madeleine Udell
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula. CoRR (2020)
Jicong Fan, Madeleine Udell
Online high rank matrix completion. CoRR (2020)
William T. Stephenson, Madeleine Udell, Tamara Broderick
Approximate Cross-Validation with Low-Rank Data in High Dimensions. NeurIPS (2020)
Jicong Fan, Chengrun Yang, Madeleine Udell
Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering. CoRR (2020)
Yuxuan Zhao, Madeleine Udell
Missing Value Imputation for Mixed Data via Gaussian Copula. KDD (2020)
Chengrun Yang, Jicong Fan, Ziyang Wu, Madeleine Udell
Efficient AutoML Pipeline Search with Matrix and Tensor Factorization. CoRR (2020)
Yuxuan Zhao, Eric Landgrebe, Eliot Shekhtman, Madeleine Udell
Online Missing Value Imputation and Correlation Change Detection for Mixed-type Data via Gaussian Copula. CoRR (2020)
Jicong Fan, Lijun Ding, Chengrun Yang, Madeleine Udell
Low-Rank Tensor Recovery with Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization. CoRR (2020)
Brian Liu, Madeleine Udell
Impact of Accuracy on Model Interpretations. CoRR (2020)
Jicong Fan, Yuqian Zhang, Madeleine Udell
Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning. AAAI (2020)
Iddo Drori, Anant Kharkar, William R. Sickinger, Brandon Kates, Qiang Ma, Suwen Ge, Eden Dolev, Brenda Dietrich, David P. Williamson, Madeleine Udell
Learning to Solve Combinatorial Optimization Problems on Real-World Graphs in Linear Time. CoRR (2020)
Jicong Fan, Lijun Ding, Yudong Chen, Madeleine Udell
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery. CoRR (2019)
Chengrun Yang, Yuji Akimoto, Dae Won Kim, Madeleine Udell
OBOE: Collaborative Filtering for AutoML Model Selection. KDD (2019)
Madeleine Udell, Oliver Toole
Optimal Design of Efficient Rooftop Photovoltaic Arrays. INFORMS J. Appl. Anal. 49 (4) (2019)
Iddo Drori, Lu Liu, Yi Nian, Sharath C. Koorathota, Jie S. Li, Antonio Khalil Moretti, Juliana Freire, Madeleine Udell
AutoML using Metadata Language Embeddings. CoRR (2019)
Jicong Fan, Madeleine Udell
Online High Rank Matrix Completion. CVPR (2019)
Madeleine Udell, Alex Townsend
Why Are Big Data Matrices Approximately Low Rank? SIAM J. Math. Data Sci. 1 (1) (2019)
Lijun Ding, Alp Yurtsever, Volkan Cevher, Joel A. Tropp, Madeleine Udell
An Optimal-Storage Approach to Semidefinite Programming using Approximate Complementarity. CoRR (2019)
Jicong Fan, Lijun Ding, Yudong Chen, Madeleine Udell
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery. NeurIPS (2019)
Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher
Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation. SIAM J. Sci. Comput. 41 (4) (2019)
Yiming Sun, Yang Guo, Charlene Luo, Joel A. Tropp, Madeleine Udell
Low-Rank Tucker Approximation of a Tensor From Streaming Data. CoRR (2019)
Jiahao Chen, Nathan Kallus, Xiaojie Mao, Geoffry Svacha, Madeleine Udell
Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved. FAT (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan R. Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
SysML: The New Frontier of Machine Learning Systems. CoRR (2019)
Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher
Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation. CoRR (2019)
Jicong Fan, Yuqian Zhang, Madeleine Udell
Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning. CoRR (2019)
Nathan Kallus, Xiaojie Mao, Madeleine Udell
Causal Inference with Noisy and Missing Covariates via Matrix Factorization. NeurIPS (2018)
Nathan Kallus, Xiaojie Mao, Madeleine Udell
Causal Inference with Noisy and Missing Covariates via Matrix Factorization. CoRR (2018)
Chengrun Yang, Yuji Akimoto, Dae Won Kim, Madeleine Udell
OBOE: Collaborative Filtering for AutoML Initialization. CoRR (2018)
Song Zhou, Swati Gupta, Madeleine Udell
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives. NeurIPS (2018)
Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data. CoRR (2017)
Mihir Paradkar, Madeleine Udell
Graph-Regularized Generalized Low-Rank Models. CVPR Workshops (2017)
Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data. NIPS (2017)
Madeleine Udell, Alex Townsend
Nice latent variable models have log-rank. CoRR (2017)
Alp Yurtsever, Madeleine Udell, Joel A. Tropp, Volkan Cevher
Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage. AISTATS (2017)
Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher
Practical Sketching Algorithms for Low-Rank Matrix Approximation. SIAM J. Matrix Anal. Appl. 38 (4) (2017)
Madeleine Udell, Stephen P. Boyd
Bounding duality gap for separable problems with linear constraints. Comput. Optim. Appl. 64 (2) (2016)
Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher
Randomized single-view algorithms for low-rank matrix approximation. CoRR (2016)
Alejandro Schuler, Vincent X. Liu, Joe Wan, Alison Callahan, Madeleine Udell, David E. Stark, Nigam H. Shah
Discovering Patient Phenotypes Using Generalized Low Rank Models. PSB (2016)
Nathan Kallus, Madeleine Udell
Revealed Preference at Scale: Learning Personalized Preferences from Assortment Choices. EC (2016)
Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen P. Boyd
Generalized Low Rank Models. Found. Trends Mach. Learn. 9 (1) (2016)
Damek Davis, Brent Edmunds, Madeleine Udell
The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM. NIPS (2016)
Haleema Mehmood, Madeleine Udell, John M. Cioffi
Revenue Maximization for Broadband Service Providers Using Revenue Capacity. GLOBECOM (2015)
Edward H. Lee, Madeleine Udell, S. Simon Wong
Factorization for analog-to-digital matrix multiplication. ICASSP (2015)
Nathan Kallus, Madeleine Udell
Learning Preferences from Assortment Choices in a Heterogeneous Population. CoRR (2015)
Madeleine Udell, Karanveer Mohan, David Zeng, Jenny Hong, Steven Diamond, Stephen P. Boyd
Convex optimization in Julia. HPTCDL@SC (2014)
Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen P. Boyd
Generalized Low Rank Models. CoRR (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Madeleine Udell