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2020 – today
- 2024
[j17]Yuxuan Zhao, Madeleine Udell
:
gcimpute: A Package for Missing Data Imputation. J. Stat. Softw. 108(4) (2024)- [c36]Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell:
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models. ICML 2024 - [c35]Pratik Rathore, Weimu Lei, Zachary Frangella, Lu Lu, Madeleine Udell:
Challenges in Training PINNs: A Loss Landscape Perspective. ICML 2024 - [i50]Pratik Rathore, Weimu Lei, Zachary Frangella, Lu Lu, Madeleine Udell:
Challenges in Training PINNs: A Loss Landscape Perspective. CoRR abs/2402.01868 (2024) - [i49]Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell:
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models. CoRR abs/2402.10172 (2024) - [i48]Mike Van Ness, Madeleine Udell:
Interpretable Prediction and Feature Selection for Survival Analysis. CoRR abs/2404.14689 (2024) - [i47]Pratik Rathore, Zachary Frangella, Madeleine Udell:
Have ASkotch: Fast Methods for Large-scale, Memory-constrained Kernel Ridge Regression. CoRR abs/2407.10070 (2024) - [i46]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 abs/2407.19633 (2024) - [i45]Keith Tyser, Ben Segev, Gaston Longhitano, Xin-Yu Zhang, Zachary Meeks, Jason Lee, Uday Garg, Nicholas Belsten, Avi Shporer, Madeleine Udell, Dov Te'eni, Iddo Drori:
AI-Driven Review Systems: Evaluating LLMs in Scalable and Bias-Aware Academic Reviews. CoRR abs/2408.10365 (2024) - 2023
- [j16]Lijun Ding, Madeleine Udell:
A strict complementarity approach to error bound and sensitivity of solution of conic programs. Optim. Lett. 17(7): 1551-1574 (2023) - [j15]Zachary Frangella, Joel A. Tropp, Madeleine Udell:
Randomized Nyström Preconditioning. SIAM J. Matrix Anal. Appl. 44(2): 718-752 (2023) - [j14]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) - [c34]Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister:
Data-Efficient and Interpretable Tabular Anomaly Detection. KDD 2023: 190-201 - [c33]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: 3947-3955 - [c32]Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell:
The Missing Indicator Method: From Low to High Dimensions. KDD 2023: 5004-5015 - [c31]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: 574-593 - [i44]Zachary Frangella, Pratik Rathore, Shipu Zhao, Madeleine Udell:
PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates. CoRR abs/2309.02014 (2023) - [i43]Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell:
OptiMUS: Optimization Modeling Using MIP Solvers and large language models. CoRR abs/2310.06116 (2023) - [i42]Mike Van Ness, Tomas M. Bosschieter, Natasha Din, Andrew Ambrosy, Alexander Sandhu, Madeleine Udell:
Interpretable Survival Analysis for Heart Failure Risk Prediction. CoRR abs/2310.15472 (2023) - [i41]Wenzhi Gao, Zhaonan Qu, Madeleine Udell, Yinyu Ye:
Scalable Approximate Optimal Diagonal Preconditioning. CoRR abs/2312.15594 (2023) - 2022
- [c30]Yuxuan Zhao, Eric Landgrebe, Eliot Shekhtman, Madeleine Udell:
Online Missing Value Imputation and Change Point Detection with the Gaussian Copula. AAAI 2022: 9199-9207 - [c29]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 - [c28]Shipu Zhao, Zachary Frangella, Madeleine Udell:
NysADMM: faster composite convex optimization via low-rank approximation. ICML 2022: 26824-26840 - [c27]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 - [c26]Yuxuan Zhao, Alex Townsend, Madeleine Udell:
Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data. NeurIPS 2022 - [i40]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 abs/2201.03668 (2022) - [i39]Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister:
Data-Efficient and Interpretable Tabular Anomaly Detection. CoRR abs/2203.02034 (2022) - [i38]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 abs/2204.07615 (2022) - [i37]Brian Liu, Miaolan Xie, Haoyue Yang, Madeleine Udell:
ControlBurn: Nonlinear Feature Selection with Sparse Tree Ensembles. CoRR abs/2207.03935 (2022) - [i36]Zachary Frangella, Pratik Rathore, Shipu Zhao, Madeleine Udell:
SketchySGD: Reliable Stochastic Optimization via Robust Curvature Estimates. CoRR abs/2211.08597 (2022) - [i35]Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell:
The Missing Indicator Method: From Low to High Dimensions. CoRR abs/2211.09259 (2022) - 2021
- [j13]Ramchandran Muthukumar, Drew P. Kouri, Madeleine Udell:
Randomized Sketching Algorithms for Low-Memory Dynamic Optimization. SIAM J. Optim. 31(2): 1242-1275 (2021) - [j12]Lijun Ding, Madeleine Udell:
On the Simplicity and Conditioning of Low Rank Semidefinite Programs. SIAM J. Optim. 31(4): 2614-2637 (2021) - [j11]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): 2695-2725 (2021) - [j10]Alp Yurtsever, Joel A. Tropp, Olivier Fercoq, Madeleine Udell, Volkan Cevher:
Scalable Semidefinite Programming. SIAM J. Math. Data Sci. 3(1): 171-200 (2021) - [j9]Jicong Fan, Chengrun Yang, Madeleine Udell:
Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering. IEEE Trans. Signal Process. 69: 1755-1770 (2021) - [c25]Chengrun Yang, Lijun Ding, Ziyang Wu, Madeleine Udell:
TenIPS: Inverse Propensity Sampling for Tensor Completion. AISTATS 2021: 3160-3168 - [c24]Mike Van Ness, Madeleine Udell:
CDF Normalization for Controlling the Distribution of Hidden Nodes. ICBINB@NeurIPS 2021: 64-68 - [c23]Brian Liu, Miaolan Xie, Madeleine Udell:
ControlBurn: Feature Selection by Sparse Forests. KDD 2021: 1045-1054 - [c22]William T. Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick:
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression. NeurIPS 2021: 24352-24364 - [i34]Chengrun Yang, Lijun Ding, Ziyang Wu, Madeleine Udell:
TenIPS: Inverse Propensity Sampling for Tensor Completion. CoRR abs/2101.00323 (2021) - [i33]Yiming Sun, Yang Guo, Joel A. Tropp, Madeleine Udell:
Tensor Random Projection for Low Memory Dimension Reduction. CoRR abs/2105.00105 (2021) - [i32]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 abs/2106.09686 (2021) - [i31]Nikhil Singh, Brandon Kates, Jeff Mentch, Anant Kharkar, Madeleine Udell, Iddo Drori:
Privileged Zero-Shot AutoML. CoRR abs/2106.13743 (2021) - [i30]Brian Liu, Miaolan Xie, Madeleine Udell:
ControlBurn: Feature Selection by Sparse Forests. CoRR abs/2107.00219 (2021) - [i29]William T. Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick:
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression. CoRR abs/2107.09194 (2021) - [i28]Zachary Frangella, Joel A. Tropp, Madeleine Udell:
Randomized Nyström Preconditioning. CoRR abs/2110.02820 (2021) - 2020
- [j8]Nathan Kallus, Madeleine Udell:
Dynamic Assortment Personalization in High Dimensions. Oper. Res. 68(4): 1020-1037 (2020) - [j7]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): 1123-1150 (2020) - [c21]Jicong Fan, Yuqian Zhang, Madeleine Udell:
Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning. AAAI 2020: 3842-3849 - [c20]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: 19-24 - [c19]Yuxuan Zhao, Madeleine Udell:
Missing Value Imputation for Mixed Data via Gaussian Copula. KDD 2020: 636-646 - [c18]Chengrun Yang, Jicong Fan, Ziyang Wu, Madeleine Udell:
AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space. KDD 2020: 1446-1456 - [c17]William T. Stephenson, Madeleine Udell, Tamara Broderick:
Approximate Cross-Validation with Low-Rank Data in High Dimensions. NeurIPS 2020 - [c16]Yuxuan Zhao, Madeleine Udell:
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula. NeurIPS 2020 - [i27]Jicong Fan, Madeleine Udell:
Online high rank matrix completion. CoRR abs/2002.08934 (2020) - [i26]Lijun Ding, Madeleine Udell:
On the regularity and conditioning of low rank semidefinite programs. CoRR abs/2002.10673 (2020) - [i25]Jicong Fan, Chengrun Yang, Madeleine Udell:
Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering. CoRR abs/2005.01317 (2020) - [i24]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 abs/2006.03750 (2020) - [i23]Chengrun Yang, Jicong Fan, Ziyang Wu, Madeleine Udell:
Efficient AutoML Pipeline Search with Matrix and Tensor Factorization. CoRR abs/2006.04216 (2020) - [i22]Yuxuan Zhao, Madeleine Udell:
Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula. CoRR abs/2006.10829 (2020) - [i21]Lijun Ding, Jicong Fan, Madeleine Udell:
kFW: A Frank-Wolfe style algorithm with stronger subproblem oracles. CoRR abs/2006.16142 (2020) - [i20]William T. Stephenson, Madeleine Udell, Tamara Broderick:
Approximate Cross-Validation with Low-Rank Data in High Dimensions. CoRR abs/2008.10547 (2020) - [i19]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 abs/2009.01168 (2020) - [i18]Yuxuan Zhao, Eric Landgrebe, Eliot Shekhtman, Madeleine Udell:
Online Missing Value Imputation and Correlation Change Detection for Mixed-type Data via Gaussian Copula. CoRR abs/2009.12326 (2020) - [i17]Brian Liu, Madeleine Udell:
Impact of Accuracy on Model Interpretations. CoRR abs/2011.09903 (2020) - [i16]Jicong Fan, Lijun Ding, Chengrun Yang, Madeleine Udell:
Low-Rank Tensor Recovery with Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization. CoRR abs/2012.03436 (2020)
2010 – 2019
- 2019
- [j6]Madeleine Udell, Oliver Toole:
Optimal Design of Efficient Rooftop Photovoltaic Arrays. INFORMS J. Appl. Anal. 49(4): 281-294 (2019) - [j5]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): A2430-A2463 (2019) - [j4]Madeleine Udell, Alex Townsend:
Why Are Big Data Matrices Approximately Low Rank? SIAM J. Math. Data Sci. 1(1): 144-160 (2019) - [c15]Jicong Fan, Madeleine Udell:
Online High Rank Matrix Completion. CVPR 2019: 8690-8698 - [c14]Jiahao Chen, Nathan Kallus, Xiaojie Mao, Geoffry Svacha, Madeleine Udell:
Fairness Under Unawareness: Assessing Disparity When Protected Class Is Unobserved. FAT 2019: 339-348 - [c13]Chengrun Yang, Yuji Akimoto, Dae Won Kim, Madeleine Udell:
OBOE: Collaborative Filtering for AutoML Model Selection. KDD 2019: 1173-1183 - [c12]Jicong Fan, Lijun Ding, Yudong Chen, Madeleine Udell:
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery. NeurIPS 2019: 5105-5115 - [i15]Lijun Ding, Alp Yurtsever, Volkan Cevher, Joel A. Tropp, Madeleine Udell:
An Optimal-Storage Approach to Semidefinite Programming using Approximate Complementarity. CoRR abs/1902.03373 (2019) - [i14]Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher:
Streaming Low-Rank Matrix Approximation with an Application to Scientific Simulation. CoRR abs/1902.08651 (2019) - [i13]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. 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 Randall 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 abs/1904.03257 (2019) - [i12]Yiming Sun, Yang Guo, Charlene Luo, Joel A. Tropp, Madeleine Udell:
Low-Rank Tucker Approximation of a Tensor From Streaming Data. CoRR abs/1904.10951 (2019) - [i11]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 abs/1910.03698 (2019) - [i10]Jicong Fan, Lijun Ding, Yudong Chen, Madeleine Udell:
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery. CoRR abs/1911.05774 (2019) - [i9]Jicong Fan, Yuqian Zhang, Madeleine Udell:
Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning. CoRR abs/1912.06989 (2019) - 2018
- [c11]Song Zhou, Swati Gupta, Madeleine Udell:
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives. NeurIPS 2018: 4419-4429 - [c10]Nathan Kallus, Xiaojie Mao, Madeleine Udell:
Causal Inference with Noisy and Missing Covariates via Matrix Factorization. NeurIPS 2018: 6921-6932 - [i8]Nathan Kallus, Xiaojie Mao, Madeleine Udell:
Causal Inference with Noisy and Missing Covariates via Matrix Factorization. CoRR abs/1806.00811 (2018) - [i7]Chengrun Yang, Yuji Akimoto, Dae Won Kim, Madeleine Udell:
OBOE: Collaborative Filtering for AutoML Initialization. CoRR abs/1808.03233 (2018) - 2017
- [j3]Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher:
Practical Sketching Algorithms for Low-Rank Matrix Approximation. SIAM J. Matrix Anal. Appl. 38(4): 1454-1485 (2017) - [c9]Alp Yurtsever, Madeleine Udell, Joel A. Tropp, Volkan Cevher:
Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage. AISTATS 2017: 1188-1196 - [c8]Mihir Paradkar, Madeleine Udell:
Graph-Regularized Generalized Low-Rank Models. CVPR Workshops 2017: 1921-1926 - [c7]Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher:
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data. NIPS 2017: 1225-1234 - [i6]Madeleine Udell, Alex Townsend:
Nice latent variable models have log-rank. CoRR abs/1705.07474 (2017) - [i5]Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher:
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data. CoRR abs/1706.05736 (2017) - 2016
- [j2]Madeleine Udell, Stephen P. Boyd:
Bounding duality gap for separable problems with linear constraints. Comput. Optim. Appl. 64(2): 355-378 (2016) - [j1]Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen P. Boyd:
Generalized Low Rank Models. Found. Trends Mach. Learn. 9(1): 1-118 (2016) - [c6]Damek Davis, Brent Edmunds, Madeleine Udell:
The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM. NIPS 2016: 226-234 - [c5]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: 144-155 - [c4]Nathan Kallus, Madeleine Udell:
Revealed Preference at Scale: Learning Personalized Preferences from Assortment Choices. EC 2016: 821-837 - [i4]Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher:
Randomized single-view algorithms for low-rank matrix approximation. CoRR abs/1609.00048 (2016) - 2015
- [c3]Haleema Mehmood, Madeleine Udell, John M. Cioffi:
Revenue Maximization for Broadband Service Providers Using Revenue Capacity. GLOBECOM 2015: 1-7 - [c2]Edward H. Lee, Madeleine Udell, S. Simon Wong:
Factorization for analog-to-digital matrix multiplication. ICASSP 2015: 1061-1065 - [i3]Nathan Kallus, Madeleine Udell:
Learning Preferences from Assortment Choices in a Heterogeneous Population. CoRR abs/1509.05113 (2015) - 2014
- [c1]Madeleine Udell, Karanveer Mohan, David Zeng, Jenny Hong, Steven Diamond, Stephen P. Boyd:
Convex optimization in Julia. HPTCDL@SC 2014: 18-28 - [i2]Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen P. Boyd:
Generalized Low Rank Models. CoRR abs/1410.0342 (2014) - [i1]Madeleine Udell, Karanveer Mohan, David Zeng, Jenny Hong, Steven Diamond, Stephen P. Boyd:
Convex Optimization in Julia. CoRR abs/1410.4821 (2014)
Coauthor Index
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