DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization
Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He
working paper
present at NeurIPS 2023 workshop on Federated Learning in the Age of Foundation Models
Uncertainty Quantification with User-level Differential Privacy
Abhradeep Guha Thakurta, Dj Dvijotham, Georgie Evans, Peter Kairouz, Ryan McKenna, Sewoong Oh
working paper
present at Theory and Practice of Differential Privacy 2023
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning
Collins, Liam, Shanshan Wu, Sewoong Oh, and Khe Chai Sim
working paper
present at International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023
One-shot Empirical Privacy Estimation for Federated Learning
Andrew, Galen, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, and Vinith Suriyakumar
working paper
International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023
Can Public Large Language Models Help Private Cross-device Federated Learning?
Boxin Wang, Yibo Jacky Zhang, Yuan Cao, Bo Li, H Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer
working paper
present at ICML 2023 workshop on Efficient Systems for Foundation Models
present at ICML 2023 workshop on Challenges of Deploying Generative AI
Challenges towards the Next Frontier in Privacy
Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang
working paper,
MAUVE Scores for Generative Models: Theory and Practice
Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaid Harchaoui
working paper
Stochastic optimization on matrices and a graphon McKean-Vlasov limit
Zaid Harchaoui, Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi
working paper,
Efficient Algorithms for Federated Saddle Point Optimization
Charlie Hou, Kiran K. Thekumparampil, Giulia Fanti, Sewoong Oh
working paper,
Label Poisoning is All You Need
Rishi D. Jha, Jonathan Hayase, Sewoong Oh
NeurIPS, 2023
presentation at NeurIPS 2023 workshop on Federated Learning in the Age of Foundation Models
Unleashing the power of randomization in auditing differentially private ML
Krishna Pillutla, Galen Andrew, Peter Kairouz, Brendan McMahan, Alina Oprea, Sewoong Oh
NeurIPS 2023
presented at Boston Privacy Day, Google, and MSR
presented at ICML 2023 Federated Learning workshop
Presented at CRYPTO 2023 Privacy Preserving Machine Learning (PPML) workshop
Near Optimal Private and Robust Linear Regression
Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala
NeurIPS 2023
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks
Arun Ganesh, Daogao Liu, Sewoong Oh, Abhradeep Thakurta
NeurIPS 2023 (Spotlight presentation)
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness
Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ludwig Schmidt, Ali Farhadi
NeurIPS 2023 (Spotlight presentation)
Improving multimodal datasets with image captioning
Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt
NeurIPS 2023, Datasets and Benchmarks Track
presentation at ICML 2023 workshop on Data-centric Machine Learning Research (DMLR)
DataComp: In search of the next generation of multimodal datasets
Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt
NeurIPS 2023, Datasets and Benchmarks Track (Oral presentation)
check out our benchmark competition at datacomp.ai
Private federated learning with autotuned compression
Enayat Ullah, Christopher Choquette, Peter Kairouz, Sewoong Oh
ICML 2023,
Why Is Public Pretraining Necessary for Private Model Training?
Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Thakurta, Lun Wang
ICML 2023,
CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family
S Ashwin Hebbar, Viraj Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath
ICML 2023,
Learning to Generate Image Embeddings with User-level Differential Privacy
Zheng Xu, Maxwell Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan
CVPR 2023,
Few-shot Backdoor Attacks via Neural Tangent Kernels
Jonathan Hayase, Sewoong Oh
ICLR, 2023
poster presented at NeurIPS 2022 workshop on Trustworthy and Socially Responsible Machine Learning (TSRML)
Zonotope Domains for Lagrangian Neural Network Verification
Matt Jordan, Jonathan Hayase, Alexandros G Dimakis, Sewoong Oh
NeurIPS 2022,
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP
Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt
NeurIPS 2022, (Oral presentation)
presented at ICML 2022 workshop on Benchmarking Data for Data-Centric AI (DataPerf)
Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization
Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He
NeurIPS 2022,
DP-PCA: Statistically Optimal and Differentially Private PCA
Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
NeurIPS 2022,
MAML and ANIL Provably Learn Representations
Liam Collins, Aryan Mokhtari, Sewoong Oh, Sanjay Shakkottai
ICML, 2022
De novo mass spectrometry peptide sequencing with a transformer model
Melih Yilmaz, William E. Fondrie, Wout Bittremieux, Sewoong Oh, William Stafford Noble
ICML, 2022
5 minutes presentation by Melih Yilmaz at ICML is available here
Differential privacy and robust statistics in high dimensions
Xiyang Liu, Weihao Kong, Sewoong Oh
COLT, 2022
Presented at the third AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-22), the recording of a 12 minute presentation is available here
video of a talk on Nov 2021 at SNAPP seminar series is available here
slides from my talk at SNAPP seminar is available here
slides from my talk at Google is available here
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization
Kiran Koshy Thekumparampil, Niao He, Sewoong Oh
AISTATS, 2022 (Oral presentation)
video of a presention on Feb 2022 at Simons institute by Niao He is here
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise
Xingyu Wang, Sewoong Oh, Chang-Han Rhee
ICLR, 2022
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning
Charlie Hou, Kiran K. Thekumparampil, Giulia Fanti, Sewoong Oh
ICLR, 2022
presented at the ICML 2021 Workshop on Federated Learning for User Privacy and Data Confidentiality (ICML-FL 2021)
Robust and Differentially Private Mean Estimation
Xiyang Liu, Weihao Kong, Sham Kakade, Sewoong Oh
NeurIPS 2021,
presented at the ICML 2021 Workshop on Federated Learning for User Privacy and Data Confidentiality (ICML-FL 2021)
presented at the CCS 2021 workshop Privacy Preserving Machine Learning (PPML’21)
video of a talk on Oct 2021 at Simons Institute is available here
slides from my talk is available here
code is available here
Sample Efficient Linear Meta-Learning by Alternating Minimization
Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
NeurIPS, 2021
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral
Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui
NeurIPS, 2021
Gradient Inversion with Generative Image Prior
Jaechang Kim, Jinwoo Jeon, Kangwook Lee, Sewoong Oh, and Jungseul Ok,
NeurIPS, 2021
presented at the ICML 2021 Workshop on Federated Learning for User Privacy and Data Confidentiality (ICML-FL 2021)
SPECTRE: Defending against backdoor attacks using robust covariance estimation
Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
ICML, 2021
KO codes: Inventing Nonlinear Encoding and Decoding for Reliable WirelessCommunication via Deep-Learning
Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
ICML, 2021
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding
Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
ISIT, 2021
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method
Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
NeurIPS, 2020 (Spotlight presentation)
Robust Meta-learning for Mixed Linear Regression with Small Batches
Weihao Kong, Raghav Somani, Sham Kakade, Sewoong Oh
NeurIPS, 2020
you can find the code for Robust PCA here.
Optimal transport mapping via input convex neural networks
Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee
ICML, 2020
Meta-learning for mixed linear regression
Weihao Kong, Raghav Somani, Zhao Song, Sham Kakade, Sewoong Oh
ICML, 2020
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs
Zinan Lin, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh
ICML, 2020
Learning in Gated Neural Networks
Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, and Pramod Viswanath
AISTATS, 2020
Turbo Autoencoder: Deep learning based channel code for point-to-point communication channels
Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
NeurIPS, 2019
Efficient Algorithms for Smooth Minimax Optimization
Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
NeurIPS, 2019
you can find the code for DIAG here
Minimax Rates of Estimating Approximate Differential Privacy
Xiyang Liu, Sewoong Oh
NeurIPS, 2019
Rate Distortion For Model Compression:From Theory To Practice
Weihao Gao, Yu-Han Liu, Chong Wang, Sewoong Oh
ICML, 2019
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms
Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, and Pramod Viswanath
ICML, 2019
DeepTurbo: Deep Turbo Decoder
Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, and Pramod Viswanath
2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2019
Barracuda: The Power of l-polling in Proof-of-Stake Blockchains
G Fanti, J Jiao, A Makkuva, S Oh, R Rana, and P Viswanath
ACM MobiHoc, 2019, (Best paper award)
LEARN Codes: Inventing Low-latency Codes via Recurrent Neural Networks
Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, and Pramod Viswanath
IEEE International Conference on Communications (ICC), 2019
Learning One-hidden-layer Neural Networks under General Input Distributions
Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, and Pramod Viswanath
AISTATS, 2019
Iterative Bayesian Learning for Crowdsourced Regression
Jungseul Ok, Yunhun Jang, Sewoong Oh, Jinwoo Shin, Yung Yi
AISTATS, 2019, [ code ]
Compounding of Wealth in Proof-of-Stake Cryptocurrencies
Giulia Fanti, Leonid Kogan, Sewoong Oh, Kathleen Ruan, Pramod Viswanath, and Gerui Wang
Financial Cryptography and Data Security, 2019
Robustness of conditional GANs to noisy labels
Kiran Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh
NIPS, 2018 (Spotlight presentation), [ code ]
Deepcode: Feedback Codes via Deep Learning
Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
NIPS, 2018, [ code by Hyeji Kim ],
[ code by Yihan Jiang ]
PacGAN: The power of two samples in generative adversarial networks
Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh
NIPS, 2018, [ code ], [ project page]
Communication Algorithms via Deep Learning
H. Kim, Y. Jiang, R. B. Rana, S. Kannan, S. Oh, and P. Viswanath
ICLR, 2018
Estimating Mutual Information for Discrete-Continuous Mixtures
Weihao Gao, Sreeram Kannan, Sewoong Oh, and Pramod Viswanath
NIPS, 2017 (Spotlight presentation) [ code ]
Discovering Potential Correlations via Hypercontractivity
Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, and Pramod Viswanath
NIPS, 2017 [ code ]
Matrix Norm Estimation from a Few Entries
Ashish Khetan, Sewoong Oh
NIPS, 2017, (Spotlight presentation) [ code ]
Top-K Ranking from Pairwise Comparisons: When Spectral Ranking is Optimal
Minje Jang, Sunghyun Kim, Changho Suh, Sewoong Oh
NIPS, 2017
Density Functional Estimators with k-Nearest Neighbor Bandwidths
Weihao Gao, Sewoong Oh, Pramod Viswanath
ISIT, 2017
Demystifying Fixed k-Nearest Neighbor Information Estimators
Weihao Gao, Sewoong Oh, Pramod Viswanath
ISIT, 2017, [ code ]
Achieving budget-optimality with adaptive schemes in crowdsourcing
Ashish Khetan, Sewoong Oh
NIPS, 2016
Computational and Statistical Tradeoffs in Learning to Rank
Ashish Khetan, Sewoong Oh
NIPS, 2016
Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation
Weihao Gao, Sewoong Oh, Pramod Viswanath
NIPS, 2016, [ code ]
Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications
Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
ICML, 2016, [ code ]
Data-driven Rank Breaking for Efficient Rank Aggregation
Ashish Khetan, Sewoong Oh
ICML, 2016
Optimality of Belief Propagation for Crowdsourced Classification
Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi
ICML, 2016
Metadata-conscious Anonymous Messaging
Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran and Pramod Viswanath
ICML 2016
Rumor Source Obfuscation on Irregular Trees
Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran and Pramod Viswanath
SIGMETRICS 2016
Collaboratively Learning Preferences from Ordinal Data
Sewoong Oh, Kiran K. Thekumparampil, and Jiaming Xu
NIPS 2015
Detecting Sponsored Recommendations
Subhashini Krishnasamy, Rajat Sen, Sewoong Oh, and Sanjay Shakkottai
SIGMETRICS (short paper) 2015
Spy vs. Spy: Rumor Source Obfuscation
Giulia Fanti, Peter Kairouz, Sewoong Oh, and Pramod Viswanath
SIGMETRICS 2015 (Best paper award)
Secure Multi-party Differential Privacy
Peter Kairouz, Sewoong Oh, and Pramod Viswanath
NIPS 2015
Extremal Mechanisms for Local Differential Privacy
Peter Kairouz, Sewoong Oh, and Pramod Viswanath
NIPS 2014
Provable Tensor Factorization with Missing Data
Prateek Jain and Sewoong Oh
NIPS 2014, [code]
Minimax-optimal Inference from Partial Rankings
Bruce Hajek, Sewoong Oh, and Jiaming Xu
NIPS 2014
Learning Mixed Multinomial Logit Model from Ordinal Data
Sewoong Oh and Devavrat Shah
NIPS 2014
Learning Mixtures of Discrete Product Distributions using Spectral Decompositions
Prateek Jain and Sewoong Oh
COLT 2014
The Composition Theorem for Differential Privacy
Peter Kairouz, Sewoong Oh and Pramod Viswanath
ICML 2015
What's your choice? Learning the mixed multi-nomial logit model
Ammar Ammar, Sewoong Oh, Devavrat Shah, and Luis-Filipe Voloch
SIGMETRICS (short paper) 2014
Efficient Crowdsourcing for Multi-class Labeling
David Karger, Sewoong Oh, and Devavrat Shah
SIGMETRICS 2013
Iterative Ranking from Pairwise Comparisons
Sahand Negahban, Sewoong Oh, and Devavrat Shah
NIPS 2012, (Spotlight presentation)
Iterative Learning for Reliable Crowdsourcing Systems
David R. Karger, Sewoong Oh, and Devavrat Shah
NIPS 2011, (Oral presentation)
Budget-optimal Crowdsourcing using Low-rank Matrix Approximations
David R. Karger, Sewoong Oh, and Devavrat Shah
Allerton 2011
Gossip PCA
Satish Babu Korada, Andrea Montanari, and Sewoong Oh
ACM SIGMETRICS 2011
On Positioning via Distributed Matrix Completion
A. Montanari and S. Oh
Sensor Array and Multichannel Signal Processing Workshop 2010
Ultrasound Tomography Calibration using Structured Matrix Completion
Reza Parhizkar, Amin Karbasi, Sewoong Oh, and Martin Vetterli
The 20th International Congress on Acoustics, 2010
Distributed Sensor Network Localization from Local Connectivity: Performance Analysis for the HOP-TERRAIN Algorithm
Amin Karbasi and Sewoong Oh
ACM SIGMETRICS 2010, (Kenneth C. Sevcik Outstanding Student Paper Award)
Sensor Network Localization from Local Connectivity: Performance Analysis for the MDS-MAP Algorithm
Sewoong Oh, Amin Karbasi, and Andrea Montanari
Information Theory Workshop 2010
OptSpace: A Gradient Descent Algorithm on Grassmann Manifold for Matrix Completion
Raghunandan Keshavan and Sewoong Oh
Technical report
Low-rank Matrix Completion with Noisy Observations: a Quantitative Comparison
Raghunandan Keshavan, Andrea Montanari, and Sewoong Oh
Allerton 2009
Matrix Completion from Noisy Entries
Raghunandan Keshavan, Andrea Montanari, and Sewoong Oh
NIPS 2009
Matrix Completion from a Few Entries
Raghunandan Keshavan, Andrea Montanari, and Sewoong Oh
ISIT 2009
Generating Random Tanner-graphs with Large Girth
Mohsen Bayati, Raghunandan H. Keshavan, Andrea montanari, Sewoong Oh, and Amin Saberi
Information Theory Workshop 2009,
[ code ]
Learning low rank matrices from O(n) entries
Raghunandan Keshavan, Andrea Montanari, and Sewoong Oh
Allerton 2008
Computing the threshold shift for general channels
Jeremie Ezri, Andrea Montanari, Sewoong Oh, and Ruediger Urbanke
ISIT 2008
The Slope Scaling Parameter for General Channels, Decoders and Ensembles
Jeremie Ezri, Andrea Montanari, Sewoong Oh, and Ruediger Urbanke
ISIT 2008
Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaid Harchaoui
Journal of Machine Learning Research, 2023
Shuaiqi Wang, Jonathan Hayase, Giulia Fanti, Sewoong Oh
Transactions on Machine Learning Research (TMLR), 2023
Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
IEEE Transactions on Selected Areas in Information Theory (JSAIT) , 2023
Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi
Journal of Theoretical Probability, 2023,
presented at the NeurIPS 2021 workshop on Optimal Transport and Machine Learning
L Harris, WE Fondrie, S Oh, WS Noble
Journal of Proteome Research, 2023, 22 (11), 3427-3438
AB Dincer, Y Lu, DK Schweppe, S Oh, WS Noble
Journal of Proteome Research, 2022, 21 (7), 1771-1782
Hyeji Kim, Sewoong Oh, Pramod Viswanath
IEEE Transactions on Selected Areas in Information Theory (JSAIT), Vol.1, no.1, pp.5-18, 2020,
Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, and Pramod Viswanath
IEEE Transactions on Selected Areas in Information Theory (JSAIT), Vol.1, no.1, pp.207-216, 2020,
Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh
IEEE Transactions on Selected Areas in Information Theory (JSAIT), 2 Vol.1, no.1, pp.324-335, 2020,
[ code ], [ project page]
Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath
IEEE Transactions on Selected Areas in Information Theory (JSAIT), Vol.1, no.1, pp.194-206, 2020,
[ code by Hyeji Kim ],
[ code by Yihan Jiang ]
Ashish Khetan, Sewoong Oh
Journal of Machine Learning Research, Vol.20, Issue:21, January 2019
Sahand Negahban, Sewoong Oh, Kiran Thekumparampil, and Jiaming Xu,
Journal of Machine Learning Research, Vol.19, Issue:40, pp.1-95, September 2018
Ashish Khetan, Sewoong Oh
Journal of Machine Learning Research, Vol.19, Issue:28, pp.1-42, September 2018 [bibtex]
Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi
IEEE Transactions on Information Theory, Vol.64, Issue:9, pp.6127-6138, September 2018,
Weihao Gao, Sewoong Oh, Pramod Viswanath
IEEE Transactions on Information Theory, Vol.64, Issue:8, pp.5629-5661 February 2018, [bibtex]
Weihao Gao, Sewoong Oh, Pramod Viswanath
IEEE Transactions on Information Theory, Vol.64, Issue:5, pp.3313-3330, May 2018, [bibtex]
Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, and Pramod Viswanath
Entropy, Vol.19, Issue:11, pp.586, October 2017, [ code ], [bibtex]
Ashish Khetan, Sewoong Oh
Journal of Machine Learning Research, Vol.17, no.193, pp.1-54, October 2016 [bibtex]
Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, and Pramod Viswanath
IEEE Transactions on Information Theory, Vol.63, Issue:10, pp.6679-6713, October 2017 [bibtex]
Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, and Pramod Viswanath
IEEE Transactions on Signal and Information Processing over Networks, Volume: 2, Issue: 4, pp.582 - 594, December 2016
Subhashini Krishnasamy, Rajat Sen, Sewoong Oh, and Sanjay Shakkottai
ACM Transactions on Modeling and Performance Evaluation of Computing Systems, Volume 2, Issue 1, pp.6:1–6:29, November 2016
Peter Kairouz, Sewoong Oh and Pramod Viswanath
IEEE Transaction on Information Theory, Volume 63, Issue 6, pp.4037-4049, June 2017 [bibtex]
Peter Kairouz, Sewoong Oh, and Pramod Viswanath
Journal of Machine Learning Research, Volume 17, no.17, pp.1-51, April 2016 [bibtex]
Sahand Negahban, Sewoong Oh, and Devavrat Shah
Operations Research, Vol.65, no.1, pp.266-287, October 2016
[bibtex]
Q. Geng, P. Kairouz, S. Oh, and P. Viswanath
Selected Topics in Signal Processing, April 2015
David R. Karger, Sewoong Oh and Devavrat Shah
Operations Research, Volume 62 Issue 1, pp.1-24, January-February 2014 [bibtex]
Amin Karbasi and Sewoong Oh
IEEE Transactions on Networking, Vol 21, pp.1131-1144, August 2013, [bibtex]
Reza Parhizkar, Amin Karbai, Sewoong Oh and Martin Vetterli
IEEE Transactions on Signal Processing, Vol 61, pp.4923-4933, October 2013, [bibtex]
Adam Marcus, David Karger, Samuel Madden, Robert Miller, Sewoong Oh
Journal of the VLDB Endowment, Vol. 6, issue 2, pp.109-120, December 2012, [bibtex]
Raghunandan Keshavan, Andrea Montanari and Sewoong Oh
Journal of Machine Learning Research, vol. 11, pp.2057-2078, July 2010, [ bibtex ,
code ]
Raghunandan Keshavan, Andrea Montanari and Sewoong Oh
IEEE Transactions on Information Theory,vol. 56,no. 6, pp.2980-2998, June 2010, [ bibtex ,
code ]
Ph.D. Dissertation, Stanford Univesiry, December 2010