How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression?

Vidya Muthukumar Vidya K. Muthukumar

Kuo-Wei Lai Guanghui Wang Molei Tao Vidya Muthukumar How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression? 2026 March abs/2603.04895 CoRR https://doi.org/10.48550/arXiv.2603.04895 db/journals/corr/corr2603.html#abs-2603-04895 streams/journals/corr

Kuo-Wei Lai Vidya Muthukumar General Loss Functions Lead to (Approximate) Interpolation in High Dimensions. 244:1-244:72 2025 26 J. Mach. Learn. Res. https://jmlr.org/papers/v26/23-1078.html db/journals/jmlr/jmlr26.html#LaiM25

Vidya Muthukumar Soham Phade Anant Sahai On the Impossibility of Convergence of Mixed Strategies with Optimal No-Regret Learning. 2794-2833 2025 50 Math. Oper. Res. 4 https://doi.org/10.1287/moor.2022.0016 db/journals/mor/mor50.html#MuthukumarPS25 streams/journals/mor

Tyler LaBonte Kuo-Wei Lai Vidya Muthukumar Task Shift: From Classification to Regression in Overparameterized Linear Models. 3934-3942 2025 AISTATS https://proceedings.mlr.press/v258/labonte25a.html conf/aistats/2025 db/conf/aistats/aistats2025.html#LaBonteLM25 streams/conf/aistats Milind Nakul Vidya Muthukumar Ashwin Pananjady Estimating stationary mass, frequency by frequency. 4359 2025 COLT https://proceedings.mlr.press/v291/nakul25a.html conf/colt/2025 db/conf/colt/colt2025.html#NakulMP25 streams/conf/colt Rohan Ghuge Vidya Muthukumar Sahil Singla 0001 Improved and Oracle-Efficient Online ℓ1-Multicalibration. 2025 ICML https://proceedings.mlr.press/v267/ghuge25a.html https://openreview.net/forum?id=Qu3jbojB5Q conf/icml/2025 db/conf/icml/icml2025.html#GhugeM025

Guanghui Wang Krishna Acharya Lokranjan Lakshmikanthan Vidya Muthukumar Juba Ziani Multi-Agent Performative Prediction Beyond the Insensitivity Assumption: A Case Study for Mortgage Competition. 2025 February abs/2502.08063 CoRR https://doi.org/10.48550/arXiv.2502.08063 db/journals/corr/corr2502.html#abs-2502-08063 streams/journals/corr

Tyler LaBonte Kuo-Wei Lai Vidya Muthukumar Task Shift: From Classification to Regression in Overparameterized Linear Models. 2025 February abs/2502.13285 CoRR https://doi.org/10.48550/arXiv.2502.13285 db/journals/corr/corr2502.html#abs-2502-13285 streams/journals/corr

Milind Nakul Vidya Muthukumar Ashwin Pananjady Estimating stationary mass, frequency by frequency. 2025 March abs/2503.12808 CoRR https://doi.org/10.48550/arXiv.2503.12808 db/journals/corr/corr2503.html#abs-2503-12808 streams/journals/corr

Rohan Ghuge Vidya Muthukumar Sahil Singla 0001 Improved and Oracle-Efficient Online ℓ<sub>1</sub>-Multicalibration. 2025 May abs/2505.17365 CoRR https://doi.org/10.48550/arXiv.2505.17365 db/journals/corr/corr2505.html#abs-2505-17365 streams/journals/corr

Chiraag Kaushik Justin Romberg Vidya Muthukumar A general technique for approximating high-dimensional empirical kernel matrices. 2025 November abs/2511.03892 CoRR https://doi.org/10.48550/arXiv.2511.03892 db/journals/corr/corr2511.html#abs-2511-03892 streams/journals/corr

John C. Hill Tyler LaBonte Xinchen Zhang Vidya Muthukumar On the Unreasonable Effectiveness of Last-layer Retraining. 2025 December abs/2512.01766 CoRR https://doi.org/10.48550/arXiv.2512.01766 db/journals/corr/corr2512.html#abs-2512-01766 streams/journals/corr

Chi-Heng Lin Chiraag Kaushik Eva L. Dyer Vidya Muthukumar The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective. 91:1-91:85 2024 25 J. Mach. Learn. Res. https://jmlr.org/papers/v25/22-1312.html db/journals/jmlr/jmlr25.html#LinKDM24

Ashwin Pananjady Vidya Muthukumar Andrew Thangaraj Just Wing It: Near-Optimal Estimation of Missing Mass in a Markovian Sequence. 312:1-312:43 2024 25 J. Mach. Learn. Res. https://jmlr.org/papers/v25/24-0511.html db/journals/jmlr/jmlr25.html#PananjadyMT24

Chiraag Kaushik Andrew D. McRae Mark A. Davenport Vidya Muthukumar New Equivalences between Interpolation and SVMs: Kernels and Structured Features. 761-787 2024 6 SIAM J. Math. Data Sci. 3 https://doi.org/10.1137/23m1568764 db/journals/simods/simods6.html#KaushikMDM24 streams/journals/simods

Jonathan Lee 0002 Weihao Kong Aldo Pacchiano Vidya Muthukumar Emma Brunskill Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity. 2024 2024 Trans. Mach. Learn. Res. https://openreview.net/forum?id=RUNiIDU8P7 db/journals/tmlr/tmlr2024.html#0002KPMB24

Chiraag Kaushik Ran Liu Chi-Heng Lin Amrit Khera Matthew Y. Jin Wenrui Ma Vidya Muthukumar Eva L. Dyer Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance. 2024 ICML https://proceedings.mlr.press/v235/kaushik24a.html https://openreview.net/forum?id=s4EYBJ30WY conf/icml/2024 db/conf/icml/icml2024.html#KaushikLLKJMMD24 23343-23366 Kuo-Wei Lai Vidya Muthukumar Sharp Analysis of Out-of-Distribution Error for "Importance-Weighted" Estimators in the Overparameterized Regime. 3701-3706 2024 ISIT https://doi.org/10.1109/ISIT57864.2024.10619252 conf/isit/2024 db/conf/isit/isit2024.html#LaiM24 Chiraag Kaushik Justin Romberg Vidya Muthukumar Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks. 2024 NeurIPS http://papers.nips.cc/paper_files/paper/2024/hash/df77cca99e2785eafb5b2416d688ae24-Abstract-Conference.html conf/nips/2024 db/conf/nips/neurips2024.html#KaushikRM24 Tyler LaBonte John C. Hill Xinchen Zhang Vidya Muthukumar Abhishek Kumar 0001 The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations. 2024 NeurIPS http://papers.nips.cc/paper_files/paper/2024/hash/dc4db2ff2c1aefce3b594f821ea82fe6-Abstract-Conference.html conf/nips/2024 db/conf/nips/neurips2024.html#LaBonteHZM024 Etash Guha Jim James Krishna Acharya Vidya Muthukumar Ashwin Pananjady One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits. 1491-1512 2024 UAI https://proceedings.mlr.press/v244/guha24a.html conf/uai/2024 db/conf/uai/uai2024.html#GuhaJAMP24

Chiraag Kaushik Ran Liu Chi-Heng Lin Amrit Khera Matthew Y. Jin Wenrui Ma Vidya Muthukumar Eva L. Dyer Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance. 2024 abs/2402.11742 CoRR https://doi.org/10.48550/arXiv.2402.11742 db/journals/corr/corr2402.html#abs-2402-11742

Ashwin Pananjady Vidya Muthukumar Andrew Thangaraj Just Wing It: Optimal Estimation of Missing Mass in a Markovian Sequence. 2024 abs/2404.05819 CoRR https://doi.org/10.48550/arXiv.2404.05819 db/journals/corr/corr2404.html#abs-2404-05819

Kuo-Wei Lai Vidya Muthukumar Sharp analysis of out-of-distribution error for "importance-weighted" estimators in the overparameterized regime. 2024 abs/2405.06546 CoRR https://doi.org/10.48550/arXiv.2405.06546 db/journals/corr/corr2405.html#abs-2405-06546

Chiraag Kaushik Justin Romberg Vidya Muthukumar Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks. 2024 abs/2406.02769 CoRR https://doi.org/10.48550/arXiv.2406.02769 db/journals/corr/corr2406.html#abs-2406-02769 streams/journals/corr

Tyler LaBonte John C. Hill Xinchen Zhang Vidya Muthukumar Abhishek Kumar 0001 The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations. 2024 abs/2407.13957 CoRR https://doi.org/10.48550/arXiv.2407.13957 db/journals/corr/corr2407.html#abs-2407-13957 streams/journals/corr

Ke Wang 0035 Vidya Muthukumar Christos Thrampoulidis Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation. 7909-7952 2023 December 69 IEEE Trans. Inf. Theory 12 https://doi.org/10.1109/TIT.2023.3320098 db/journals/tit/tit69.html#WangMT23

Yujia Jin Vidya Muthukumar Aaron Sidford The Complexity of Infinite-Horizon General-Sum Stochastic Games. 76:1-76:20 2023 ITCS https://doi.org/10.4230/LIPIcs.ITCS.2023.76 conf/innovations/2023 db/conf/innovations/innovations2023.html#JinMS23 Tyler LaBonte Vidya Muthukumar Abhishek Kumar 0001 Towards Last-layer Retraining for Group Robustness with Fewer Annotations. 2023 NeurIPS http://papers.nips.cc/paper_files/paper/2023/hash/265bee74aee86df77e8e36d25e786ab5-Abstract-Conference.html conf/nips/2023 db/conf/nips/neurips2023.html#LaBonteM023 Guanghui Wang Zihao Hu Vidya Muthukumar Jacob D. Abernethy Faster Margin Maximization Rates for Generic Optimization Methods. 2023 NeurIPS http://papers.nips.cc/paper_files/paper/2023/hash/c4cfdc27b46659e70a142ac249485a49-Abstract-Conference.html conf/nips/2023 db/conf/nips/neurips2023.html#WangHMA23

Jonathan N. Lee Weihao Kong Aldo Pacchiano Vidya Muthukumar Emma Brunskill Estimating Optimal Policy Value in General Linear Contextual Bandits. 2023 abs/2302.09451 CoRR https://doi.org/10.48550/arXiv.2302.09451 db/journals/corr/corr2302.html#abs-2302-09451

Kuo-Wei Lai Vidya Muthukumar General Loss Functions Lead to (Approximate) Interpolation in High Dimensions. 2023 abs/2303.07475 CoRR https://doi.org/10.48550/arXiv.2303.07475 db/journals/corr/corr2303.html#abs-2303-07475

Chiraag Kaushik Andrew D. McRae Mark A. Davenport Vidya Muthukumar New Equivalences Between Interpolation and SVMs: Kernels and Structured Features. 2023 abs/2305.02304 CoRR https://doi.org/10.48550/arXiv.2305.02304 db/journals/corr/corr2305.html#abs-2305-02304

Guanghui Wang Zihao Hu Vidya Muthukumar Jacob D. Abernethy Faster Margin Maximization Rates for Generic Optimization Methods. 2023 abs/2305.17544 CoRR https://doi.org/10.48550/arXiv.2305.17544 db/journals/corr/corr2305.html#abs-2305-17544

Tyler LaBonte Vidya Muthukumar Abhishek Kumar 0001 Towards Last-layer Retraining for Group Robustness with Fewer Annotations. 2023 abs/2309.08534 CoRR https://doi.org/10.48550/arXiv.2309.08534 db/journals/corr/corr2309.html#abs-2309-08534

Andrew D. McRae Santhosh Karnik Mark A. Davenport Vidya K. Muthukumar Harmless interpolation in regression and classification with structured features. 5853-5875 2022 AISTATS https://proceedings.mlr.press/v151/mcrae22a.html conf/aistats/2022 db/conf/aistats/aistats2022.html#McRaeKDM22 Wenshuo Guo Kumar Krishna Agrawal Aditya Grover Vidya K. Muthukumar Ashwin Pananjady Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. 6357-6386 2022 AISTATS https://proceedings.mlr.press/v151/guo22b.html conf/aistats/2022 db/conf/aistats/aistats2022.html#GuoAGMP22 Vidya K. Muthukumar Akshay Krishnamurthy Universal and data-adaptive algorithms for model selection in linear contextual bandits. 16197-16222 2022 ICML https://proceedings.mlr.press/v162/muthukumar22a.html conf/icml/2022 db/conf/icml/icml2022.html#MuthukumarK22 Guanghui Wang Zihao Hu Vidya Muthukumar Jacob D. Abernethy Adaptive Oracle-Efficient Online Learning. 2022 conf/nips/2022 NeurIPS http://papers.nips.cc/paper_files/paper/2022/hash/948106cb5a114684a64c89a1e517e3fe-Abstract-Conference.html db/conf/nips/neurips2022.html#WangHMA22

Yujia Jin Vidya Muthukumar Aaron Sidford The Complexity of Infinite-Horizon General-Sum Stochastic Games. 2022 abs/2204.04186 CoRR https://doi.org/10.48550/arXiv.2204.04186 db/journals/corr/corr2204.html#abs-2204-04186

Chi-Heng Lin Chiraag Kaushik Eva L. Dyer Vidya Muthukumar The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective. 2022 abs/2210.05021 CoRR https://doi.org/10.48550/arXiv.2210.05021 db/journals/corr/corr2210.html#abs-2210-05021

Guanghui Wang Zihao Hu Vidya Muthukumar Jacob D. Abernethy Adaptive Oracle-Efficient Online Learning. 2022 abs/2210.09385 CoRR https://doi.org/10.48550/arXiv.2210.09385 db/journals/corr/corr2210.html#abs-2210-09385

Vidya Muthukumar Adhyyan Narang Vignesh Subramanian Mikhail Belkin Daniel Hsu 0001 Anant Sahai Classification vs regression in overparameterized regimes: Does the loss function matter? 222:1-222:69 2021 22 J. Mach. Learn. Res. https://jmlr.org/papers/v22/20-603.html db/journals/jmlr/jmlr22.html#MuthukumarNSBHS21

Daniel Hsu 0001 Vidya Muthukumar Ji Xu 0003 On the proliferation of support vectors in high dimensions. 91-99 2021 AISTATS http://proceedings.mlr.press/v130/hsu21a.html conf/aistats/2021 db/conf/aistats/aistats2021.html#0001MX21 Jonathan N. Lee Aldo Pacchiano Vidya Muthukumar Weihao Kong Emma Brunskill Online Model Selection for Reinforcement Learning with Function Approximation. 3340-3348 2021 AISTATS http://proceedings.mlr.press/v130/lee21d.html conf/aistats/2021 db/conf/aistats/aistats2021.html#LeePMKB21 Ke Wang 0035 Vidya Muthukumar Christos Thrampoulidis Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation. 24164-24179 2021 NeurIPS https://proceedings.neurips.cc/paper/2021/hash/caaa29eab72b231b0af62fbdff89bfce-Abstract.html conf/nips/2021 db/conf/nips/neurips2021.html#WangMT21

Ke Wang 0035 Vidya Muthukumar Christos Thrampoulidis Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation. 2021 abs/2106.10865 CoRR https://arxiv.org/abs/2106.10865 db/journals/corr/corr2106.html#abs-2106-10865

Wenshuo Guo Kumar Krishna Agrawal Aditya Grover Vidya Muthukumar Ashwin Pananjady Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. 2021 abs/2106.14866 CoRR https://arxiv.org/abs/2106.14866 db/journals/corr/corr2106.html#abs-2106-14866

Yehuda Dar Vidya Muthukumar Richard G. Baraniuk A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning. 2021 abs/2109.02355 CoRR https://arxiv.org/abs/2109.02355 db/journals/corr/corr2109.html#abs-2109-02355

Adhyyan Narang Vidya Muthukumar Anant Sahai Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective. 2021 abs/2109.13215 CoRR https://arxiv.org/abs/2109.13215 db/journals/corr/corr2109.html#abs-2109-13215

Vidya Muthukumar Akshay Krishnamurthy Universal and data-adaptive algorithms for model selection in linear contextual bandits. 2021 abs/2111.04688 CoRR https://arxiv.org/abs/2111.04688 db/journals/corr/corr2111.html#abs-2111-04688

Andrew D. McRae Santhosh Karnik Mark A. Davenport Vidya Muthukumar Harmless interpolation in regression and classification with structured features. 2021 abs/2111.05198 CoRR https://arxiv.org/abs/2111.05198 db/journals/corr/corr2111.html#abs-2111-05198

Vidya Muthukumar Kailas Vodrahalli Vignesh Subramanian Anant Sahai Harmless Interpolation of Noisy Data in Regression. 67-83 2020 1 IEEE J. Sel. Areas Inf. Theory 1 https://doi.org/10.1109/jsait.2020.2984716 db/journals/jsait/jsait1.html#MuthukumarVSS20

Niladri S. Chatterji Vidya Muthukumar Peter L. Bartlett OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits. 1844-1854 2020 AISTATS http://proceedings.mlr.press/v108/chatterji20b.html conf/aistats/2020 db/conf/aistats/aistats2020.html#ChatterjiMB20

Vidya Muthukumar Adhyyan Narang Vignesh Subramanian Mikhail Belkin Daniel J. Hsu Anant Sahai Classification vs regression in overparameterized regimes: Does the loss function matter? 2020 abs/2005.08054 CoRR https://arxiv.org/abs/2005.08054 db/journals/corr/corr2005.html#abs-2005-08054

Daniel Hsu 0001 Vidya Muthukumar Ji Xu 0003 On the proliferation of support vectors in high dimensions. 2020 abs/2009.10670 CoRR https://arxiv.org/abs/2009.10670 db/journals/corr/corr2009.html#abs-2009-10670

Jonathan N. Lee Aldo Pacchiano Vidya Muthukumar Weihao Kong Emma Brunskill Online Model Selection for Reinforcement Learning with Function Approximation. 2020 abs/2011.09750 CoRR https://arxiv.org/abs/2011.09750 db/journals/corr/corr2011.html#abs-2011-09750

Vidya Muthukumar Soham Phade Anant Sahai On the Impossibility of Convergence of Mixed Strategies with No Regret Learning. 2020 abs/2012.02125 CoRR https://arxiv.org/abs/2012.02125 db/journals/corr/corr2012.html#abs-2012-02125

Vidya Muthukumar Mitas Ray Anant Sahai Peter L. Bartlett Best of many worlds: Robust model selection for online supervised learning. 3177-3186 2019 AISTATS http://proceedings.mlr.press/v89/muthukumar19a.html conf/aistats/2019 db/conf/aistats/aistats2019.html#MuthukumarRSB19 Vidya Muthukumar Color-Theoretic Experiments to Understand Unequal Gender Classification Accuracy From Face Images. 2286-2295 2019 CVPR Workshops http://openaccess.thecvf.com/content_CVPRW_2019/html/BEFA/Muthukumar_Color-Theoretic_Experiments_to_Understand_Unequal_Gender_Classification_Accuracy_From_Face_CVPRW_2019_paper.html https://doi.org/10.1109/CVPRW.2019.00282 conf/cvpr/2019w db/conf/cvpr/cvprw2019.html#Muthukumar19 Vidya Muthukumar Anant Sahai Robust Commitments and Partial Reputation. 637-638 2019 EC https://doi.org/10.1145/3328526.3329647 conf/sigecom/2019 db/conf/sigecom/sigecom2019.html#MuthukumarS19 Vidya Muthukumar Kailas Vodrahalli Anant Sahai Harmless interpolation of noisy data in regression. 2299-2303 2019 ISIT https://doi.org/10.1109/ISIT.2019.8849614 conf/isit/2019 db/conf/isit/isit2019.html#MuthukumarVS19

Vidya Muthukumar Kailas Vodrahalli Anant Sahai Harmless interpolation of noisy data in regression. 2019 abs/1903.09139 CoRR http://arxiv.org/abs/1903.09139 db/journals/corr/corr1903.html#abs-1903-09139

Niladri S. Chatterji Vidya Muthukumar Peter L. Bartlett OSOM: A Simultaneously Optimal Algorithm for Multi-Armed and Linear Contextual Bandits. 2019 abs/1905.10040 CoRR http://arxiv.org/abs/1905.10040 db/journals/corr/corr1905.html#abs-1905-10040

Vidya Muthukumar Anant Sahai Robust Commitments and Partial Reputation. 2019 abs/1905.11555 CoRR http://arxiv.org/abs/1905.11555 db/journals/corr/corr1905.html#abs-1905-11555

Vidya Muthukumar Mitas Ray Anant Sahai Peter L. Bartlett Best of many worlds: Robust model selection for online supervised learning. 2018 abs/1805.08562 CoRR http://arxiv.org/abs/1805.08562 db/journals/corr/corr1805.html#abs-1805-08562

Vidya Muthukumar Tejaswini Pedapati Nalini K. Ratha Prasanna Sattigeri Chai-Wah Wu Brian Kingsbury Abhishek Kumar 0001 Samuel Thomas 0001 Aleksandra Mojsilovic Kush R. Varshney Understanding Unequal Gender Classification Accuracy from Face Images. 2018 abs/1812.00099 CoRR http://arxiv.org/abs/1812.00099 db/journals/corr/corr1812.html#abs-1812-00099

Vidya Muthukumar Anant Sahai Fundamental Limits on Ex-Post Enforcement and Implications for Spectrum Rights. 491-504 2017 3 IEEE Trans. Cogn. Commun. Netw. 3 https://doi.org/10.1109/TCCN.2017.2747579 db/journals/tccn/tccn3.html#MuthukumarS17

Vidya Muthukumar Anant Sahai Fundamental limits on ex-post enforcement and implications for spectrum rights. 1-10 2017 DySPAN https://doi.org/10.1109/DySPAN.2017.7920755 conf/dyspan/2017 db/conf/dyspan/dyspan2017.html#MuthukumarS17 Vidya Muthukumar Anant Sahai Commitment in regulatory spectrum games: Examining the first-player advantage. 2498-2502 2017 ISIT https://doi.org/10.1109/ISIT.2017.8006979 conf/isit/2017 db/conf/isit/isit2017.html#MuthukumarS17

Ashwin Pananjady Cheng Mao Vidya Muthukumar Martin J. Wainwright Thomas A. Courtade Worst-case vs Average-case Design for Estimation from Fixed Pairwise Comparisons. 2017 abs/1707.06217 CoRR http://arxiv.org/abs/1707.06217 db/journals/corr/corr1707.html#PananjadyMMWC17

Kate Harrison Vidya Muthukumar Anant Sahai Whitespace evaluation software (WEST) and its applications to whitespace in Canada and Australia. 47-58 2015 DySPAN https://doi.org/10.1109/DySPAN.2015.7343849 conf/dyspan/2015 db/conf/dyspan/dyspan2015.html#HarrisonMS15 Vidya Muthukumar Angel Daruna Vijay Kamble Kate Harrison Anant Sahai Whitespaces after the USA's TV incentive auction: A spectrum reallocation case study. 7582-7588 2015 ICC https://doi.org/10.1109/ICC.2015.7249539 conf/icc/2015 db/conf/icc/icc2015.html#MuthukumarDKHS15 Matthew Thill Vidya Muthukumar Babak Hassibi Frames from generalized group fourier transforms and SL2(Fq). 4923-4927 2014 ICASSP https://doi.org/10.1109/ICASSP.2014.6854538 conf/icassp/2014 db/conf/icassp/icassp2014.html#ThillMH14 Jacob D. Abernethy Krishna Acharya Kumar Krishna Agrawal Richard G. Baraniuk Peter L. Bartlett Mikhail Belkin Emma Brunskill Niladri S. Chatterji Thomas A. Courtade Yehuda Dar Angel Daruna Mark A. Davenport Eva L. Dyer Rohan Ghuge Aditya Grover Etash Guha Wenshuo Guo Kate Harrison Babak Hassibi John C. Hill Daniel Hsu 0001Daniel J. Hsu Zihao Hu Jim James Matthew JinMatthew Y. Jin Yujia Jin Vijay Kamble Santhosh Karnik Chiraag Kaushik Amrit Khera Brian Kingsbury Weihao Kong Akshay Krishnamurthy Abhishek Kumar 0001 Tyler LaBonte Kuo-Wei Lai Lokranjan Lakshmikanthan Jonathan Lee 0002Jonathan N. Lee Chi-Heng Lin Ran Liu Wenrui Ma Cheng Mao Andrew D. McRae Aleksandra Mojsilovic Milind Nakul Adhyyan Narang Aldo Pacchiano Ashwin Pananjady Tejaswini Pedapati Soham R. PhadeSoham Phade Nalini K. Ratha Mitas Ray Justin K. RombergJustin Romberg Anant Sahai Prasanna Sattigeri Aaron Sidford Sahil Singla 0001 Vignesh Subramanian Molei Tao Andrew Thangaraj Matthew Thill Samuel Thomas 0001 Christos Thrampoulidis Kush R. Varshney Kailas Vodrahalli Martin J. Wainwright Guanghui Wang Ke Wang 0035 Chai Wah WuChai-Wah Wu Ji Xu 0003 Xinchen Zhang Juba Ziani