Google Scholar Profiles
Recent Publications
- 2022
- Efficient Active Learning with Abstention
Y. Zhu, and R. Nowak
NeurIPS 2022 - Active learning with neural networks: Insights from nonparametric statistics
Y. Zhu, and R. Nowak
NeurIPS 2022 - One for All: Simultaneous Metric and Preference Learning over Multiple Users
G. Canal, B. Mason, R. K. Vinayak, and R. Nowak
NeurIPS 2022 - Rare Gems: Finding Lottery Tickets at Initialization
K. Sreenivasan, J. Sohn, L. Yang, M. Grinde, A. Nagle, H. Wang, E. P. Xing, K. Lee, and D. Papailiopoulos
NeurIPS 2022 - LIFT: Language-Interfaced FineTuning for Non-Language Machine Learning Tasks
T. Dinh, Y. Zeng, R. Zhang, Z. Lin, S. Rajput, M. Gira, J. Sohn, D. Papailiopoulos, and K. Lee
NeurIPS 2022 - Score-based generative modeling secretly minimizes the Wasserstein distance
D. Kwon, Y. Fan, and K. Lee
NeurIPS 2022 - Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment
T. Dinh, J. Sohn, S. Rajput, T. Ossowski, Y. Ming, J. Hu, D. Papailiopoulos, and K. Lee
Findings of EMNLP 2022 - Near-minimax optimal estimation with shallow ReLU neural networksR. Parhi, and R. Nowak
IEEE Transactions on Information Theory - ReVar: Strengthening policy evaluation via reduced variance sampling
S. Mukherjee, J. P. Hanna, R. Nowak
UAI 2022 - Similarity search for efficient active learning and search of rare concepts
C. Coleman, E. Chou, J. Katz-Samuels, S. Culatana, P. Bailis, A. C. Berg, R. Nowak, R. Sumbaly, M. Zaharia, and I. Z. Yalniz
AAAI 2022 - On Continuous-Domain Inverse Problems with Sparse Superpositions of Decaying Sinusoids as Solutions
R. Parhi, and R. Nowak
ICASSP 2022 - A stochastic Farris transform for genetic data under the multispecies coalescent with applications to data requirements
G. Dasarathy, E. Mossel, R. Nowak, and S. Roch
Journal of Mathematical Biology 84 (5), 1-37 - What kinds of functions do deep neural networks learn? Insights from variational spline theory
R. Parhi, and R. Nowak
SIAM Journal on Mathematics of Data Science 4 (2), 464-489 - Near Instance Optimal Model Selection for Pure Exploration Linear Bandits
Y. Zhu, J. Katz-Samuels, and R. Nowak
AISTATS 2022 - Pareto optimal model selection in linear bandits
Y. Zhu, and R. Nowak
AISTATS 2022 - Finding Nearly Everything within Random Binary Networks
K. Sreenivasan, S. Rajput, J. Sohn, D. Papailiopoulos
AISTATS 2022 - Learning Preference Distributions From Distance Measurements
G. Tatli, R. Nowak, and R. K. Vinayak
Allerton Conference on Communication, Control, and Computing 2022 - Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics
Z. Miao, W. Kong, R. K. Vinayak, W. Sun, and F. Han
Journal of the American Statistical Association 2022 - Breaking Fair Binary Classification with Optimal Flipping Attacks
C. Jo, J. Sohn, and K. Lee
ISIT 2022 - GALAXY: Graph-based Active Learning at the Extreme
J. Zhang, J. Katz-Samuels, and R. Nowak
ICML 2022 - Training ood detectors in their natural habitats
J. Katz-Samuels, J. B. Nakhleh, R. Nowak, Y. Li
ICML 2022 - GenLabel: Mixup Relabeling using Generative Models
J. Sohn, L. Shang, H. Chen, J. Moon, D. Papailiopoulos, and K. Lee
ICML 2022 - Permutation-Based SGD: Is Random Optimal?
S. Rajput, K. Lee, and D. Papailiopoulos
ICLR 2022
- Efficient Active Learning with Abstention
- 2021
- Pure exploration in kernel and neural bandits
Y. Zhu, D. Zhou, R. Jiang, Q. Gu, R. Willett, R. Nowak
NeurIPS 2021 - Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers
J. Katz-Samuels, B. Mason, K. Jamieson, R. Nowak
NeurIPS 2021 - An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks
S Rajput, K Sreenivasan, D Papailiopoulos, A Karbasi
NeurIPS 2021 - Sample Selection for Fair and Robust Training
Y. Roh, K. Lee, S. Whang, and C. Suh
NeurIPS 2021 - Gradient Inversion with Generative Image Prior
J. Kim, J. Jeon, K. Lee, S. Oh, and J. Ok
NeurIPS 2021 - Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics
Z. Miao, W. Kong, R. Korlakai Vinayak, W. Sun, and F. Han - Coded-InvNet for Resilient Prediction Serving Systems
T. Dinh and K. Lee
ICML 2021 - Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information
C. Jo and K. Lee
ICML 2021 - Pufferfish: Communication-efficient Models At No Extra Cost
H. Wang, S. Agarwal, and D. Papailiopoulos
MLSys 2021 - Tensor Methods for Nonlinear Matrix Completion
G Ongie, D Pimentel-Alarcón, L Balzano, R Willett, RD NowakSIAM Journal on Mathematics of Data Science 3 (1), 253-279
- Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification
S. Agarwal, H. Wang, K. Lee, S. Venkataraman, and D. Papailiopoulos
MLSys 2021 - FairBatch: Batch Selection for Model Fairness
Y. Roh, K. Lee, S. Whang, and C. Suh
ICLR 2021 - Banach space representer theorems for neural networks and ridge splines
R Parhi, RD NowakJournal of Machine Learning Research 22 (43), 1-40
- Pure exploration in kernel and neural bandits
- 2020
- Maximin active learning in overparameterized model classes
M Karzand, RD NowakIEEE Journal on Selected Areas in Information Theory 1 (1), 167-177
- Concentration inequalities for the empirical distribution of discrete distributions: beyond the method of types
J Mardia, J Jiao, E Tánczos, RD Nowak, T WeissmanInformation and Inference: A Journal of the IMA 9 (4), 813-850
- Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient
A. Pensia, S. Rajput, A. Nagle, H. Vishwakarma, D. Papailiopoulos
NeurIPS 2020 (spotlight) - Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
H. Wang, K. Sreenivasan, S. Rajput, H. Vishwakarma, S. Agarwal, J. Sohn, K. Lee, and D. Papailiopoulos
NeurIPS 2020 - Bad Global Minima Exist and SGD Can Reach Them
S. Liu, D. Papailiopoulos, D. Achlioptas
NeurIPS 2020 - Finding All ϵ -Good Arms in Stochastic Bandits
B Mason, L Jain, AS Tripathy, R Nowak
NeuIPS 2020 - Reprogramming GANs via Input Noise Design
K. Lee, C. Suh, and K. Ramchandran
ECML PKDD 2020 - Popular Imperceptibility Measures in Visual Adversarial Attacks are Far from Human Perception
A Sen, X Zhu, E Marshall, R NowakInternational Conference on Decision and Game Theory for Security 2020
- Robust Outlier Arm Identification
Y Zhu, S Katariya, R NowakICML 2020
- Estimating the number and effect sizes of non-null hypotheses
J. Brennan, R. Korlakai Vinayak, K. Jamieson
ICML 2020 - The role of neural network activation functions
R Parhi, RD NowakIEEE Signal Processing Letters 2020
- Federated Learning with Matched Averaging
H. Wang, M. Yurochkin, Y. Sun, D. Papailiopoulos, Y. Khazaeni
ICLR 2020 (oral) - FR-Train: A mutual information-based approach to fair and robust training
Y. Roh, K. Lee, S. Whang, and C. Suh
ICML 2020 - Closing the Convergence Gap of SGD without Replacement
S. Rajput, A. Gupta, D. Papailiopoulos
ICML 2020 - Linear bandits with feature feedback
U Oswal, A Bhargava, R NowakAAAI 2020
- Maximin active learning in overparameterized model classes
- 2019
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation?
S. Rajput, H. Wang, Z. Charles, and D. Papailiopoulos
NeurIPS 2019 - Maxgap bandit: Adaptive algorithms for approximate ranking
S Katariya, A Tripathy, R Nowak
NeurIPS 2019 - Learning nearest neighbor graphs from noisy distance samples
B Mason, A Tripathy, R Nowak
NeurIPS 2019 - Maximum Likelihood Estimation for Learning Populations of Parameters
R. Korlakai Vinayak, W. Kong, G. Valiant, and S. Kakade
ICML 2019 - Does Data Augmentation Lead to Positive Margin?
S. Rajput, Z. Feng, Z. Charles, P.-L. Loh, and D. Papailiopoulos
ICML 2019 - Bilinear bandits with low-rank structure
KS Jun, R Willett, S Wright, R NowakICML 2019
- The Illusion of Change: Correcting for Bias when Inferring Changes in Sparse, Societal-Scale Data
G. Cadamuro, R. Korlakai Vinayak, J. Blumenstock, S. Kakade, and J. N. Shapiro
WWW 2019 - Crash to Not Crash: Learn to Identify Dangerous Vehicles using a Simulator
H. Kim*, K. Lee*, G. Hwang, and C. Suh
AAAI 2019 (oral)
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation?
- <= 2018
- Binary Rating Estimation with Graph Side Information
K. Ahn, K. Lee, H. Cha, and C. Suh
NeurIPS 2018 - Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings
K. Lee*, H. Kim*, and C. Suh
ICLR 2018
- Binary Rating Estimation with Graph Side Information