Learning low rank matrices from O(n) entries. - Raghunandan H. Keshavan; Andrea Montanari; Sewoong Oh (Allerton, 2008)

The slope scaling parameter for general channels, decoders, and ensembles. - Jeremie Ezri; Andrea Montanari; Sewoong Oh; Rüdiger L. Urbanke (ISIT, 2008)

Computing the threshold shift for general channels. - Jeremie Ezri; Rüdiger L. Urbanke; Andrea Montanari; Sewoong Oh (ISIT, 2008)

Low-rank matrix completion with noisy observations: A quantitative comparison. - Raghunandan H. Keshavan; Andrea Montanari; Sewoong Oh (Allerton, 2009)

A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion - Raghunandan H. Keshavan; Sewoong Oh (CoRR, 2009)

Distributed sensor network localization from local connectivity: performance analysis for the HOP-TERRAIN algorithm. - Amin Karbasi; Sewoong Oh (SIGMETRICS, 2010)

Calibration for Ultrasound Breast Tomography Using Matrix Completion - Reza Parhizkar; Amin Karbasi; Sewoong Oh; Martin Vetterli (CoRR, 2010)

Matrix Completion from Noisy Entries. - Raghunandan H. Keshavan; Andrea Montanari; Sewoong Oh (J. Mach. Learn. Res., 2010)

Matrix completion from a few entries. - Raghunandan H. Keshavan; Andrea Montanari; Sewoong Oh (IEEE Trans. Inf. Theory, 2010)

Budget-optimal crowdsourcing using low-rank matrix approximations. - David R. Karger; Sewoong Oh; Devavrat Shah (Allerton, 2011)

Iterative Learning for Reliable Crowdsourcing Systems. - David R. Karger; Sewoong Oh; Devavrat Shah (NIPS, 2011)

Gossip PCA. - Satish Babu Korada; Andrea Montanari; Sewoong Oh (SIGMETRICS, 2011)

Iterative ranking from pair-wise comparisons. - Sahand Negahban; Sewoong Oh; Devavrat Shah (NIPS, 2012)

Counting with the Crowd. - Adam Marcus 002; David R. Karger; Samuel Madden 001; Rob Miller 001; Sewoong Oh (Proc. VLDB Endow., 2012)

Efficient crowdsourcing for multi-class labeling. - David R. Karger; Sewoong Oh; Devavrat Shah (SIGMETRICS, 2013)

The Composition Theorem for Differential Privacy. - Sewoong Oh; Pramod Viswanath (CoRR, 2013)

Robust Localization From Incomplete Local Information. - Amin Karbasi; Sewoong Oh (IEEE/ACM Trans. Netw., 2013)

Calibration Using Matrix Completion With Application to Ultrasound Tomography. - Reza Parhizkar; Amin Karbasi; Sewoong Oh; Martin Vetterli (IEEE Trans. Signal Process., 2013)

Learning Mixtures of Discrete Product Distributions using Spectral Decompositions. - Prateek Jain 002; Sewoong Oh (COLT, 2014)

Provable Tensor Factorization with Missing Data. - Prateek Jain 002; Sewoong Oh (NIPS, 2014)

Minimax-optimal Inference from Partial Rankings. - Bruce E. Hajek; Sewoong Oh; Jiaming Xu 002 (NIPS, 2014)

Learning Mixed Multinomial Logit Model from Ordinal Data. - Sewoong Oh; Devavrat Shah (NIPS, 2014)

Assessment of ENC sounding by Delaunay Triangulation method in aspect of fine compilation for safe navigation. - Dongwoo Kang; Wooseong Shim; Sewoong Oh; Sunyoung Kim (SCIS&ISIS, 2014)

What's your choice?: learning the mixed multi-nomial. - Ammar Ammar; Sewoong Oh; Devavrat Shah; Luis Filipe Voloch (SIGMETRICS, 2014)

Optimality of Non-Interactive Randomized Response. - Peter Kairouz; Sewoong Oh; Pramod Viswanath (CoRR, 2014)

Spy vs. Spy: Rumor Source Obfuscation. - Peter Kairouz; Sewoong Oh; Pramod Viswanath (CoRR, 2014)

Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems. - David R. Karger; Sewoong Oh; Devavrat Shah (Oper. Res., 2014)

Secure Multi-party Differential Privacy. - Peter Kairouz; Sewoong Oh; Pramod Viswanath (NIPS, 2015)

Collaboratively Learning Preferences from Ordinal Data. - Sewoong Oh; Kiran Koshy Thekumparampil; Jiaming Xu 002 (NIPS, 2015)

Spy vs. Spy: Rumor Source Obfuscation. - Giulia Fanti; Peter Kairouz; Sewoong Oh; Pramod Viswanath (SIGMETRICS, 2015)

The Staircase Mechanism in Differential Privacy. - Quan Geng; Peter Kairouz; Sewoong Oh; Pramod Viswanath (IEEE J. Sel. Top. Signal Process., 2015)

Differentially private multi-party computation. - Peter Kairouz; Sewoong Oh; Pramod Viswanath (CISS, 2016)

Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications. - Weihao Gao; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (ICML, 2016)

Optimality of Belief Propagation for Crowdsourced Classification. - Jungseul Ok; Sewoong Oh; Jinwoo Shin; Yung Yi (ICML, 2016)

Computational and Statistical Tradeoffs in Learning to Rank. - Ashish Khetan; Sewoong Oh (NIPS, 2016)

Achieving budget-optimality with adaptive schemes in crowdsourcing. - Ashish Khetan; Sewoong Oh (NIPS, 2016)

Rumor Source Obfuscation on Irregular Trees. - Giulia Fanti; Peter Kairouz; Sewoong Oh; Kannan Ramchandran; Pramod Viswanath (SIGMETRICS, 2016)

Causal Strength via Shannon Capacity: Axioms, Estimators and Applications. - Weihao Gao; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (CoRR, 2016)

Top-K Ranking from Pairwise Comparisons: When Spectral Ranking is Optimal. - Minje Jang; Sunghyun Kim 001; Changho Suh; Sewoong Oh (CoRR, 2016)

Reliable Crowdsourcing under the Generalized Dawid-Skene Model. - Ashish Khetan; Sewoong Oh (CoRR, 2016)

Extremal Mechanisms for Local Differential Privacy. - Peter Kairouz; Sewoong Oh; Pramod Viswanath (J. Mach. Learn. Res., 2016)

Data-driven Rank Breaking for Efficient Rank Aggregation. - Ashish Khetan; Sewoong Oh (J. Mach. Learn. Res., 2016)

Detecting Sponsored Recommendations. - Subhashini Krishnasamy; Rajat Sen; Sanjay Shakkottai; Sewoong Oh (ACM Trans. Model. Perform. Evaluation Comput. Syst., 2016)

Metadata-Conscious Anonymous Messaging. - Giulia Fanti; Peter Kairouz; Sewoong Oh; Kannan Ramchandran; Pramod Viswanath (IEEE Trans. Signal Inf. Process. over Networks, 2016)

Density functional estimators with k-nearest neighbor bandwidths. - Weihao Gao; Sewoong Oh; Pramod Viswanath (ISIT, 2017)

Estimating Mutual Information for Discrete-Continuous Mixtures. - Weihao Gao; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (NIPS, 2017)

Optimal Sample Complexity of M-wise Data for Top-K Ranking. - Minje Jang; Sunghyun Kim 001; Changho Suh; Sewoong Oh (NIPS, 2017)

Matrix Norm Estimation from a Few Entries. - Ashish Khetan; Sewoong Oh (NIPS, 2017)

Matrix Factorization at the Frontier of Non-convex Optimizations: Abstract for SIGMETRICS 2017 Rising Star Award Talk. - Sewoong Oh (SIGMETRICS (Abstracts), 2017)

Efficient Learning for Crowdsourced Regression. - Jungseul Ok; Sewoong Oh; Jinwoo Shin; Yunhun Jang; Yung Yi (CoRR, 2017)

Discovering Potential Correlations via Hypercontractivity. - Hyeji Kim; Weihao Gao; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (Entropy, 2017)

Rank Centrality: Ranking from Pairwise Comparisons. - Sahand Negahban; Sewoong Oh; Devavrat Shah (Oper. Res., 2017)

Hiding the Rumor Source. - Giulia Fanti; Peter Kairouz; Sewoong Oh; Kannan Ramchandran; Pramod Viswanath (IEEE Trans. Inf. Theory, 2017)

The Composition Theorem for Differential Privacy. - Peter Kairouz; Sewoong Oh; Pramod Viswanath (IEEE Trans. Inf. Theory, 2017)

Communication Algorithms via Deep Learning. - Hyeji Kim; Yihan Jiang; Ranvir Rana; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (ICLR (Poster), 2018)

Robustness of conditional GANs to noisy labels. - Kiran Koshy Thekumparampil; Ashish Khetan; Zinan Lin 001; Sewoong Oh (NeurIPS, 2018)

Attention-based Graph Neural Network for Semi-supervised Learning. - Kiran Koshy Thekumparampil; Chong Wang 002; Sewoong Oh; Li-Jia Li 001 (CoRR, 2018)

Rate Distortion For Model Compression: From Theory To Practice. - Weihao Gao; Chong Wang 002; Sewoong Oh (CoRR, 2018)

Number of Connected Components in a Graph: Estimation via Counting Patterns. - Ashish Khetan; Harshay Shah; Sewoong Oh (CoRR, 2018)

Generalized Rank-Breaking: Computational and Statistical Tradeoffs. - Ashish Khetan; Sewoong Oh (J. Mach. Learn. Res., 2018)

Learning from Comparisons and Choices. - Sahand Negahban; Sewoong Oh; Kiran Koshy Thekumparampil; Jiaming Xu 002 (J. Mach. Learn. Res., 2018)

Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation. - Weihao Gao; Sewoong Oh; Pramod Viswanath (IEEE Trans. Inf. Theory, 2018)

Demystifying Fixed k-Nearest Neighbor Information Estimators. - Weihao Gao; Sewoong Oh; Pramod Viswanath (IEEE Trans. Inf. Theory, 2018)

Optimal Inference in Crowdsourced Classification via Belief Propagation. - Jungseul Ok; Sewoong Oh; Jinwoo Shin; Yung Yi (IEEE Trans. Inf. Theory, 2018)

Learning One-hidden-layer Neural Networks under General Input Distributions. - Weihao Gao; Ashok Vardhan Makkuva; Sewoong Oh; Pramod Viswanath (AISTATS, 2019)

Iterative Bayesian Learning for Crowdsourced Regression. - Jungseul Ok; Sewoong Oh; Yunhun Jang; Jinwoo Shin; Yung Yi (AISTATS, 2019)

Compounding of Wealth in Proof-of-Stake Cryptocurrencies. - Giulia Fanti; Leonid Kogan; Sewoong Oh; Kathleen Ruan; Pramod Viswanath; Gerui Wang (Financial Cryptography, 2019)

Rate Distortion For Model Compression: From Theory To Practice. - Weihao Gao; Yu-Han Liu; Chong Wang 002; Sewoong Oh (ICML, 2019)

Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms. - Ashok Vardhan Makkuva; Pramod Viswanath; Sreeram Kannan; Sewoong Oh (ICML, 2019)

Barracuda: The Power of ℓ-polling in Proof-of-Stake Blockchains. - Giulia Fanti; Jiantao Jiao; Ashok Vardhan Makkuva; Sewoong Oh; Ranvir Rana; Pramod Viswanath (MobiHoc, 2019)

Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels. - Yihan Jiang; Hyeji Kim; Himanshu Asnani; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (NeurIPS, 2019)

Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases. - Xiyang Liu; Sewoong Oh (NeurIPS, 2019)

Efficient Algorithms for Smooth Minimax Optimization. - Kiran Koshy Thekumparampil; Prateek Jain 002; Praneeth Netrapalli; Sewoong Oh (NeurIPS, 2019)

DEEPTURBO: Deep Turbo Decoder. - Yihan Jiang; Sreeram Kannan; Hyeji Kim; Sewoong Oh; Himanshu Asnani; Pramod Viswanath (SPAWC, 2019)

Minimax Rates of Estimating Approximate Differential Privacy. - Xiyang Liu; Sewoong Oh (CoRR, 2019)

Robust conditional GANs under missing or uncertain labels. - Kiran Koshy Thekumparampil; Sewoong Oh; Ashish Khetan (CoRR, 2019)

InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers. - Zinan Lin 001; Kiran Koshy Thekumparampil; Giulia Fanti; Sewoong Oh (CoRR, 2019)

Proof-of-Stake Longest Chain Protocols Revisited. - Xuechao Wang; Govinda M. Kamath; Vivek Kumar Bagaria; Sreeram Kannan; Sewoong Oh; David Tse; Pramod Viswanath (CoRR, 2019)

Spectrum Estimation from a Few Entries. - Ashish Khetan; Sewoong Oh (J. Mach. Learn. Res., 2019)

Learning in Gated Neural Networks. - Ashok Vardhan Makkuva; Sewoong Oh; Sreeram Kannan; Pramod Viswanath (AISTATS, 2020)

Feedback Turbo Autoencoder. - Yihan Jiang; Hyeji Kim; Himanshu Asnani; Sewoong Oh; Sreeram Kannan; Pramod Viswanath (ICASSP, 2020)

InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs. - Zinan Lin 001; Kiran Koshy Thekumparampil; Giulia Fanti; Sewoong Oh (ICML, 2020)

Meta-learning for Mixed Linear Regression. - Weihao Kong; Raghav Somani; Zhao Song 002; Sham M. Kakade; Sewoong Oh (ICML, 2020)

Optimal transport mapping via input convex neural networks. - Ashok Vardhan Makkuva; Amirhossein Taghvaei; Sewoong Oh; Jason D. Lee (ICML, 2020)

Robust Meta-learning for Mixed Linear Regression with Small Batches. - Weihao Kong; Raghav Somani; Sham M. Kakade; Sewoong Oh (NeurIPS, 2020)

Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method. - Kiran Koshy Thekumparampil; Prateek Jain 002; Praneeth Netrapalli; Sewoong Oh (NeurIPS, 2020)

Joint Channel Coding and Modulation via Deep Learning. - Yihan Jiang; Hyeji Kim; Himanshu Asnani; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (SPAWC, 2020)

Deepcode and Modulo-SK are Designed for Different Settings. - Hyeji Kim; Yihan Jiang; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (CoRR, 2020)

Guest Editorial. - Richard G. Baraniuk; Alex Dimakis; Negar Kiyavash; Sewoong Oh; Rebecca Willett (IEEE J. Sel. Areas Inf. Theory, 2020)

LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks. - Yihan Jiang; Hyeji Kim; Himanshu Asnani; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (IEEE J. Sel. Areas Inf. Theory, 2020)

Deepcode: Feedback Codes via Deep Learning. - Hyeji Kim; Yihan Jiang; Sreeram Kannan; Sewoong Oh; Pramod Viswanath (IEEE J. Sel. Areas Inf. Theory, 2020)

Physical Layer Communication via Deep Learning. - Hyeji Kim; Sewoong Oh; Pramod Viswanath (IEEE J. Sel. Areas Inf. Theory, 2020)

PacGAN: The Power of Two Samples in Generative Adversarial Networks. - Zinan Lin 001; Ashish Khetan; Giulia Fanti; Sewoong Oh (IEEE J. Sel. Areas Inf. Theory, 2020)

Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks. - Weizhao Tang; Weina Wang 001; Giulia Fanti; Sewoong Oh (Proc. ACM Meas. Anal. Comput. Syst., 2020)

Defense against backdoor attacks via robust covariance estimation. - Jonathan Hayase; Weihao Kong; Raghav Somani; Sewoong Oh (ICML, 2021)

KO codes: inventing nonlinear encoding and decoding for reliable wireless communication 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)

Gradient Inversion with Generative Image Prior. - Jinwoo Jeon; Jaechang Kim 001; Kangwook Lee 001; Sewoong Oh; Jungseul Ok (NeurIPS, 2021)

Robust and differentially private mean estimation. - Xiyang Liu; Weihao Kong; Sham M. Kakade; Sewoong Oh (NeurIPS, 2021)

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals. - Lang Liu; Krishna Pillutla; Sean Welleck; Sewoong Oh; Yejin Choi 001; Zaïd Harchaoui (NeurIPS, 2021)

Statistically and Computationally Efficient Linear Meta-representation Learning. - Kiran Koshy Thekumparampil; Prateek Jain 002; Praneeth Netrapalli; Sewoong Oh (NeurIPS, 2021)

Efficient Algorithms for Federated Saddle Point Optimization. - Charlie Hou; Kiran Koshy Thekumparampil; Giulia Fanti; Sewoong Oh (CoRR, 2021)

SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. - Jonathan Hayase; Weihao Kong; Raghav Somani; Sewoong Oh (CoRR, 2021)

Sample Efficient Linear Meta-Learning by Alternating Minimization. - Kiran Koshy Thekumparampil; Prateek Jain 002; Praneeth Netrapalli; Sewoong Oh (CoRR, 2021)

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral. - Lang Liu; Krishna Pillutla; Sean Welleck; Sewoong Oh; Yejin Choi 001; Zaïd Harchaoui (CoRR, 2021)

Reducing the Communication Cost of Federated Learning through Multistage Optimization. - Charlie Hou; Kiran Koshy Thekumparampil; Giulia Fanti; Sewoong Oh (CoRR, 2021)

Gradient flows on graphons: existence, convergence, continuity equations. - Sewoong Oh; Soumik Pal; Raghav Somani; Raghav Tripathi (CoRR, 2021)

Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization. - Kiran Koshy Thekumparampil; Niao He; Sewoong Oh (AISTATS, 2022)

Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. - Sen Lin 001; Ming Shi 003; Anish Arora; Raef Bassily; Elisa Bertino; Constantine Caramanis; Kaushik R. Chowdhury; Eylem Ekici; Atilla Eryilmaz; Stratis Ioannidis; Nan Jiang 008; Gauri Joshi; et al. (CIC, 2022)

Differential privacy and robust statistics in high dimensions. - Xiyang Liu; Weihao Kong; Sewoong Oh (COLT, 2022)

Proof-of-Stake Longest Chain Protocols: Security vs Predictability. - Vivek Kumar Bagaria; Amir Dembo; Sreeram Kannan; Sewoong Oh; David Tse; Pramod Viswanath; Xuechao Wang; Ofer Zeitouni (ConsensusDay@CCS, 2022)

FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning. - Charlie Hou; Kiran Koshy Thekumparampil; Giulia Fanti; Sewoong Oh (ICLR, 2022)

Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise. - Xingyu Wang; Sewoong Oh; Chang-Han Rhee (ICLR, 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 Fondrie; Wout Bittremieux; Sewoong Oh; William S. Noble (ICML, 2022)

Zonotope Domains for Lagrangian Neural Network Verification. - Matt Jordan; Jonathan Hayase; Alex Dimakis; Sewoong Oh (NeurIPS, 2022)

DP-PCA: Statistically Optimal and Differentially Private PCA. - Xiyang Liu; Weihao Kong; Prateek Jain 002; 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)

Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization. - Liang Zhang; Kiran Koshy Thekumparampil; Sewoong Oh; Niao He (NeurIPS, 2022)

Towards a Defense against Backdoor Attacks in Continual Federated Learning. - Shuaiqi Wang; Jonathan Hayase; Giulia Fanti; Sewoong Oh (CoRR, 2022)

Stochastic optimization on matrices and a graphon McKean-Vlasov limit. - Zaïd Harchaoui; Sewoong Oh; Soumik Pal; Raghav Somani; Raghavendra Tripathi (CoRR, 2022)

Learning to Generate Image Embeddings with User-Level Differential Privacy. - Zheng Xu 002; Maxwell D. Collins; Yuxiao Wang 001; Liviu Panait; Sewoong Oh; Sean Augenstein; Ting Liu 005; Florian Schroff; H. Brendan McMahan (CVPR, 2023)

Few-shot Backdoor Attacks via Neural Tangent Kernels. - Jonathan Hayase; Sewoong Oh (ICLR, 2023)

Why Is Public Pretraining Necessary for Private Model Training? - Arun Ganesh; Mahdi Haghifam; Milad Nasr; Sewoong Oh; Thomas Steinke 002; Om Thakkar 001; Abhradeep Guha Thakurta; Lun Wang 001 (ICML, 2023)

CRISP: Curriculum based Sequential neural decoders for Polar code family. - S. Ashwin Hebbar; Viraj Vivek Nadkarni; Ashok Vardhan Makkuva; Suma Bhat; Sewoong Oh; Pramod Viswanath (ICML, 2023)

Private Federated Learning with Autotuned Compression. - Enayat Ullah; Christopher A. Choquette-Choo; Peter Kairouz; Sewoong Oh (ICML, 2023)

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 001; Eyal Orgad; Rahim Entezari; et al. (NeurIPS, 2023)

Label Poisoning is All You Need. - Rishi D. Jha; Jonathan Hayase; Sewoong Oh (NeurIPS, 2023)

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency. - Xiyang Liu; Prateek Jain 002; Weihao Kong; Sewoong Oh; Arun Sai Suggala (NeurIPS, 2023)

Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks. - Daogao Liu; Arun Ganesh; Sewoong Oh; Abhradeep Guha Thakurta (NeurIPS, 2023)

Improving multimodal datasets with image captioning. - Thao Nguyen; Samir Yitzhak Gadre; Gabriel Ilharco; Sewoong Oh; Ludwig Schmidt (NeurIPS, 2023)

Unleashing the Power of Randomization in Auditing Differentially Private ML. - Krishna Pillutla; Galen Andrew; Peter Kairouz; H. Brendan McMahan; Alina Oprea; Sewoong Oh (NeurIPS, 2023)

On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. - Vivek Ramanujan; Thao Nguyen; Sewoong Oh; Ali Farhadi; Ludwig Schmidt (NeurIPS, 2023)

Near Optimal Private and Robust Linear Regression. - Xiyang Liu; Prateek Jain 002; Weihao Kong; Sewoong Oh; Arun Sai Suggala (CoRR, 2023)

Challenges towards the Next Frontier in Privacy. - Rachel Cummings; Damien Desfontaines; David Evans 001; Roxana Geambasu; Matthew Jagielski; Yangsibo Huang; Peter Kairouz; Gautam Kamath 001; Sewoong Oh; Olga Ohrimenko; Nicolas Papernot; Ryan Rogers 002; et al. (CoRR, 2023)

Can Public Large Language Models Help Private Cross-device Federated Learning? - Boxin Wang; Jacky Yibo Zhang; Yuan Cao; Bo Li 026; H. Brendan McMahan; Sewoong Oh; Zheng Xu 002; Manzil Zaheer (CoRR, 2023)

Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning. - Liam Collins; Shanshan Wu; Sewoong Oh; Khe Chai Sim (CoRR, 2023)

DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization. - Liang Zhang; Kiran Koshy Thekumparampil; Sewoong Oh; Niao He (CoRR, 2023)

MAUVE Scores for Generative Models: Theory and Practice. - Krishna Pillutla; Lang Liu; John Thickstun; Sean Welleck; Swabha Swayamdipta; Rowan Zellers; Sewoong Oh; Yejin Choi 001; Zaïd Harchaoui (J. Mach. Learn. Res., 2023)

Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes. - Mohammad Vahid Jamali; Xiyang Liu; Ashok Vardhan Makkuva; Hessam Mahdavifar; Sewoong Oh; Pramod Viswanath (IEEE J. Sel. Areas Inf. Theory, 2023)

Towards a Defense Against Federated Backdoor Attacks Under Continuous Training. - Shuaiqi Wang; Jonathan Hayase; Giulia Fanti; Sewoong Oh (Trans. Mach. Learn. Res., 2023)

AirGapAgent: Protecting Privacy-Conscious Conversational Agents. - Eugene Bagdasarian; Ren Yi; Sahra Ghalebikesabi; Peter Kairouz; Marco Gruteser; Sewoong Oh; Borja Balle; Daniel Ramage (CCS, 2024)

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract. - Gavin Brown 003; Jonathan Hayase; Samuel B. Hopkins 001; Weihao Kong; Xiyang Liu; Sewoong Oh; Juan C. Perdomo; Adam Smith 006 (COLT, 2024)

Better Alignment with Instruction Back-and-Forth Translation. - Thao Nguyen; Jeffrey Li; Sewoong Oh; Ludwig Schmidt; Jason Weston; Luke Zettlemoyer; Xian Li 003 (EMNLP (Findings), 2024)

One-shot Empirical Privacy Estimation for Federated Learning. - Galen Andrew; Peter Kairouz; Sewoong Oh; Alina Oprea; Hugh Brendan McMahan; Vinith Menon Suriyakumar (ICLR, 2024)

Improved Communication-Privacy Trade-offs in L2 Mean Estimation under Streaming Differential Privacy. - Wei-Ning Chen; Berivan Isik; Peter Kairouz; Albert No; Sewoong Oh; Zheng Xu 002 (ICML, 2024)

DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning. - S. Ashwin Hebbar; Sravan Kumar Ankireddy; Hyeji Kim; Sewoong Oh; Pramod Viswanath (ICML, 2024)

Privacy-Preserving Instructions for Aligning Large Language Models. - Da Yu; Peter Kairouz; Sewoong Oh; Zheng Xu 002 (ICML, 2024)

DPZero: Private Fine-Tuning of Language Models without Backpropagation. - Liang Zhang; Bingcong Li; Kiran Koshy Thekumparampil; Sewoong Oh; Niao He (ICML, 2024)

Can Public Large Language Models Help Private Cross-device Federated Learning? - Boxin Wang; Yibo Zhang; Yuan Cao; Bo Li 026; Hugh McMahan; Sewoong Oh; Zheng Xu 002; Manzil Zaheer (NAACL-HLT (Findings), 2024)

Data Mixture Inference Attack: BPE Tokenizers Reveal Training Data Compositions. - Jonathan Hayase; Alisa Liu; Yejin Choi 001; Sewoong Oh; Noah A. Smith (NeurIPS, 2024)

DataComp-LM: In search of the next generation of training sets for language models. - Jeffrey Li; Alex Fang; Georgios Smyrnis; Maor Ivgi; Matt Jordan; Samir Yitzhak Gadre; Hritik Bansal; Etash Kumar Guha; Sedrick Scott Keh; Kushal Arora; Saurabh Garg; Rui Xin; et al. (NeurIPS, 2024)

Multilingual Diversity Improves Vision-Language Representations. - Thao Nguyen; Matthew Wallingford; Sebastin Santy; Wei-Chiu Ma; Sewoong Oh; Ludwig Schmidt; Pang Wei W. Koh; Ranjay Krishna (NeurIPS, 2024)

Understanding the Gains from Repeated Self-Distillation. - Divyansh Pareek; Simon S. Du; Sewoong Oh (NeurIPS, 2024)

A learned score function improves the power of mass spectrometry database search. - Varun Ananth; Justin Sanders; Melih Yilmaz; Bo Wen; Sewoong Oh; William Stafford Noble (Bioinform., 2024)

On the Convergence of Differentially-Private Fine-tuning: To Linearly Probe or to Fully Fine-tune? - Shuqi Ke; Charlie Hou; Giulia Fanti; Sewoong Oh (CoRR, 2024)

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares. - Gavin Brown 003; Jonathan Hayase; Samuel B. Hopkins 001; Weihao Kong; Xiyang Liu; Sewoong Oh; Juan C. Perdomo; Adam Smith 006 (CoRR, 2024)

Improved Communication-Privacy Trade-offs in L2 Mean Estimation under Streaming Differential Privacy. - Wei-Ning Chen; Berivan Isik; Peter Kairouz; Albert No; Sewoong Oh; Zheng Xu 002 (CoRR, 2024)

Air Gap: Protecting Privacy-Conscious Conversational Agents. - Eugene Bagdasaryan; Ren Yi; Sahra Ghalebikesabi; Peter Kairouz; Marco Gruteser; Sewoong Oh; Borja Balle; Daniel Ramage (CoRR, 2024)

Multilingual Diversity Improves Vision-Language Representations. - Thao Nguyen; Matthew Wallingford; Sebastin Santy; Wei-Chiu Ma; Sewoong Oh; Ludwig Schmidt; Pang Wei Koh; Ranjay Krishna (CoRR, 2024)

Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data? - Jonathan Hayase; Alisa Liu; Yejin Choi 001; Sewoong Oh; Noah A. Smith (CoRR, 2024)

Randomization Techniques to Mitigate the Risk of Copyright Infringement. - Wei-Ning Chen; Peter Kairouz; Sewoong Oh; Zheng Xu 002 (CoRR, 2024)

Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning. - Marshall Ball; James Bell-Clark; Adrià Gascón; Peter Kairouz; Sewoong Oh; Zhiye Xie (IACR Cryptol. ePrint Arch., 2024)

OML: Open, Monetizable, and Loyal AI. - Zerui Cheng; Edoardo Contente; Ben Finch; Oleg Golev; Jonathan Hayase; Andrew Miller 001; Niusha Moshrefi; Anshul Nasery; Sandeep Nailwal; Sewoong Oh; Himanshu Tyagi; Pramod Viswanath (IACR Cryptol. ePrint Arch., 2024)

POMACS V8, N3, December 2024 Editorial. - Sewoong Oh; Ramesh K. Sitaraman; Benny Van Houdt (Proc. ACM Meas. Anal. Comput. Syst., 2024)

PLeaS - Merging Models with Permutations and Least Squares. - Anshul Nasery; Jonathan Hayase; Pang Wei Koh; Sewoong Oh (CVPR, 2025)

POMACS V9, N2, June 2025 Editorial. - Sewoong Oh; Ramesh K. Sitaraman; Benny Van Houdt (Proc. ACM Meas. Anal. Comput. Syst., 2025)

Economics of Sourcing Human Data. - Sebastin Santy; Prasanta Bhattacharya; Manoel Horta Ribeiro; Kelsey Allen; Sewoong Oh (CoRR, 2025)

Scalable Fingerprinting of Large Language Models. - Anshul Nasery; Jonathan Hayase; Creston Brooks; Peiyao Sheng; Himanshu Tyagi; Pramod Viswanath; Sewoong Oh (CoRR, 2025)

Training AI to be Loyal. - Sewoong Oh; Himanshu Tyagi; Pramod Viswanath (CoRR, 2025)

S4S: Solving for a Diffusion Model Solver. - Eric Frankel; Sitan Chen; Jerry Li 001; Pang Wei Koh; Lillian J. Ratliff; Sewoong Oh (CoRR, 2025)

SuperBPE: Space Travel for Language Models. - Alisa Liu; Jonathan Hayase; Valentin Hofmann; Sewoong Oh; Noah A. Smith; Yejin Choi 001 (CoRR, 2025)

Open Deep Search: Democratizing Search with Open-source Reasoning Agents. - Salaheddin Alzubi; Creston Brooks; Purva Chiniya; Edoardo Contente; Chiara von Gerlach; Lucas Irwin; Yihan Jiang; Arda Kaz; Windsor Nguyen; Sewoong Oh; Himanshu Tyagi; Pramod Viswanath (CoRR, 2025)

POMACS V9, N1, March 2025 Editorial. - Sewoong Oh; Ramesh K. Sitaraman; Benny Van Houdt (Proc. ACM Meas. Anal. Comput. Syst., 2025)

A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage. - Rui Xin; Niloofar Mireshghallah; Shuyue Stella Li; Michael Duan; Hyunwoo Kim 002; Yejin Choi 001; Yulia Tsvetkov; Sewoong Oh; Pang Wei Koh (CoRR, 2025)

Foundation model for mass spectrometry proteomics. - Justin Sanders; Melih Yilmaz; Jacob H. Russell; Wout Bittremieux; William Fondrie; Nicholas M. Riley; Sewoong Oh; William Stafford Noble (CoRR, 2025)

OpenThoughts: Data Recipes for Reasoning Models. - Etash Kumar Guha; Ryan Marten; Sedrick Keh; Negin Raoof; Georgios Smyrnis; Hritik Bansal; Marianna Nezhurina; Jean Mercat; Trung Vu 002; Zayne Sprague; Ashima Suvarna; Benjamin Feuer; et al. (CoRR, 2025)

CHANCERY: Evaluating Corporate Governance Reasoning Capabilities in Language Models. - Lucas Irwin; Arda Kaz; Peiyao Sheng; Sewoong Oh; Pramod Viswanath (CoRR, 2025)

Recycling the Web: A Method to Enhance Pre-training Data Quality and Quantity for Language Models. - Thao Nguyen; Yang Li; Olga Golovneva; Luke Zettlemoyer; Sewoong Oh; Ludwig Schmidt; Xian Li 003 (CoRR, 2025)

Zeroth-Order Optimization Finds Flat Minima. - Liang Zhang; Bingcong Li; Kiran Koshy Thekumparampil; Sewoong Oh; Michael Muehlebach; Niao He (CoRR, 2025)

Spurious Rewards: Rethinking Training Signals in RLVR. - Rulin Shao; Shuyue Stella Li; Rui Xin; Scott Geng; Yiping Wang; Sewoong Oh; Simon Shaolei Du; Nathan Lambert 001; Sewon Min; Ranjay Krishna; Yulia Tsvetkov; Hannaneh Hajishirzi; et al. (CoRR, 2025)

Sampling from Your Language Model One Byte at a Time. - Jonathan Hayase; Alisa Liu; Noah A. Smith; Sewoong Oh (CoRR, 2025)