Oh, Sewoong

106 publications

ICLRW 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, Yejin Choi, Yulia Tsvetkov, Sewoong Oh, Pang Wei Koh

TMLR 2025 Characterizing the Training Dynamics of Private Fine-Tuning with Langevin Diffusion Shuqi Ke, Charlie Hou, Sewoong Oh, Giulia Fanti

ICML 2025 Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic Agents Eric Frankel, Kshitij Kulkarni, Dmitriy Drusvyatskiy, Sewoong Oh, Lillian J. Ratliff

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

ICML 2025 Position: When Incentives Backfire, Data Stops Being Human Sebastin Santy, Prasanta Bhattacharya, Manoel Horta Ribeiro, Kelsey R Allen, Sewoong Oh

ICML 2025 S4S: Solving for a Fast Diffusion Model Solver Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh

NeurIPS 2025 Scalable Fingerprinting of Large Language Models Anshul Nasery, Jonathan Hayase, Creston Brooks, Peiyao Sheng, Himanshu Tyagi, Pramod Viswanath, Sewoong Oh

ICLRW 2025 Scalable Fingerprinting of Large Language Models Anshul Nasery, Jonathan Hayase, Creston Brooks, Peiyao Sheng, Himanshu Tyagi, Pramod Viswanath, Sewoong Oh

NeurIPS 2025 Understanding the Gain from Data Filtering in Multimodal Contrastive Learning Divyansh Pareek, Sewoong Oh, Simon Shaolei Du

NeurIPS 2025 Zeroth-Order Optimization Finds Flat Minima Liang Zhang, Bingcong Li, Kiran Koshy Thekumparampil, Sewoong Oh, Michael Muehlebach, Niao He

NeurIPSW 2024 A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-Level Privacy Leakage Rui Xin, Niloofar Mireshghallah, Shuyue Stella Li, Hyunwoo Kim, Michael Duan, Yejin Choi, Yulia Tsvetkov, Sewoong Oh, Pang Wei Koh

NeurIPSW 2024 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, Yejin Choi, Yulia Tsvetkov, Sewoong Oh, Pang Wei Koh

NeurIPSW 2024 Characterizing the Training Dynamics of Private Fine-Tuning with Langevin Diffusion Shuqi Ke, Charlie Hou, Sewoong Oh, Giulia Fanti

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

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

ICMLW 2024 Data Mixture Inference: What Do BPE Tokenizers Reveal About Their Training Data? Jonathan Hayase, Alisa Liu, Yejin Choi, 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 Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Chandu, Thao Nguyen, Igor Vasiljevic, Sham Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

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 Improved Communication-Privacy Trade-Offs in $l_2$ Mean Estimation Under Streaming Differential Privacy Wei-Ning Chen, Berivan Isik, Peter Kairouz, Albert No, Sewoong Oh, Zheng Xu

COLT 2024 Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract Gavin Brown, Jonathan Hayase, Samuel Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C Perdomo, Adam Smith

NeurIPS 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

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

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

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

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

ICMLW 2023 Can Public Large Language Models Help Private Cross-Device Federated Learning? Boxin Wang, Yibo Jacky Zhang, Yuan Cao, Bo Li, Hugh Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer

NeurIPSW 2023 DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He

NeurIPS 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, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei W Koh, Olga Saukh, Alexander J Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt

ICLR 2023 Few-Shot Backdoor Attacks via Neural Tangent Kernels Jonathan Hayase, Sewoong Oh

NeurIPS 2023 Improving Multimodal Datasets with Image Captioning Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt

NeurIPS 2023 Label Poisoning Is All You Need Rishi Jha, Jonathan Hayase, Sewoong Oh

NeurIPS 2023 Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Suggala

CVPR 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

JMLR 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, Zaid Harchaoui

NeurIPS 2023 On the Connection Between Pre-Training Data Diversity and Fine-Tuning Robustness Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ali Farhadi, Ludwig Schmidt

NeurIPSW 2023 One-Shot Empirical Privacy Estimation for Federated Learning Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, Hugh McMahan, Vinith Suriyakumar

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

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

NeurIPSW 2023 Profit: Benchmarking Personalization and Robustness Trade-Off in Federated Prompt Tuning Liam Collins, Shanshan Wu, Sewoong Oh, Khe Chai Sim

TMLR 2023 Towards a Defense Against Federated Backdoor Attacks Under Continuous Training Shuaiqi Wang, Jonathan Hayase, Giulia Fanti, Sewoong Oh

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

ICMLW 2023 Unleashing the Power of Randomization in Auditing Differentially Private ML Krishna Pillutla, Galen Andrew, Peter Kairouz, Hugh Brendan McMahan, Alina Oprea, 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 Guha Thakurta, Lun Wang

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

NeurIPS 2022 Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization Liang Zhang, Kiran K Thekumparampil, Sewoong Oh, Niao He

NeurIPS 2022 DP-PCA: Statistically Optimal and Differentially Private PCA Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh

ICML 2022 De Novo Mass Spectrometry Peptide Sequencing with a Transformer Model Melih Yilmaz, William Fondrie, Wout Bittremieux, Sewoong Oh, William S Noble

COLT 2022 Differential Privacy and Robust Statistics in High Dimensions Xiyang Liu, Weihao Kong, Sewoong Oh

ICLR 2022 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 Koshy Thekumparampil, Giulia Fanti, Sewoong Oh

NeurIPSW 2022 Few-Shot Backdoor Attacks via Neural Tangent Kernels Jonathan Hayase, Sewoong Oh

ICML 2022 MAML and ANIL Provably Learn Representations Liam Collins, Aryan Mokhtari, Sewoong Oh, Sanjay Shakkottai

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 Zonotope Domains for Lagrangian Neural Network Verification Matt Jordan, Jonathan Hayase, Alex Dimakis, 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, Zaid Harchaoui

NeurIPS 2021 Gradient Inversion with Generative Image Prior Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok

ICML 2021 KO Codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-Learning Ashok V Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath

NeurIPS 2021 Robust and Differentially Private Mean Estimation Xiyang Liu, Weihao Kong, Sham Kakade, Sewoong Oh

ICML 2021 SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh

NeurIPS 2021 Statistically and Computationally Efficient Linear Meta-Representation Learning Kiran K Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh

ICML 2020 InfoGAN-CR and ModelCentrality: Self-Supervised Model Training and Selection for Disentangling GANs Zinan Lin, Kiran Thekumparampil, Giulia Fanti, Sewoong Oh

AISTATS 2020 Learning in Gated Neural Networks Ashok Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath

ICML 2020 Meta-Learning for Mixed Linear Regression Weihao Kong, Raghav Somani, Zhao Song, Sham Kakade, Sewoong Oh

ICML 2020 Optimal Transport Mapping via Input Convex Neural Networks Ashok Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason Lee

NeurIPS 2020 Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method Kiran K Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh

NeurIPS 2020 Robust Meta-Learning for Mixed Linear Regression with Small Batches Weihao Kong, Raghav Somani, Sham Kakade, Sewoong Oh

ICML 2019 Breaking the Gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms Ashok Makkuva, Pramod Viswanath, Sreeram Kannan, Sewoong Oh

NeurIPS 2019 Efficient Algorithms for Smooth Minimax Optimization Kiran K Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh

AISTATS 2019 Iterative Bayesian Learning for Crowdsourced Regression Jungseul Ok, Sewoong Oh, Yunhun Jang, Jinwoo Shin, Yung Yi

AISTATS 2019 Learning One-Hidden-Layer Neural Networks Under General Input Distributions Weihao Gao, Ashok V. Makkuva, Sewoong Oh, Pramod Viswanath

NeurIPS 2019 Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases Xiyang Liu, Sewoong Oh

ICML 2019 Rate Distortion for Model Compression:From Theory to Practice Weihao Gao, Yu-Han Liu, Chong Wang, Sewoong Oh

JMLR 2019 Spectrum Estimation from a Few Entries Ashish Khetan, Sewoong Oh

NeurIPS 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

ICLR 2018 Communication Algorithms via Deep Learning Hyeji Kim, Yihan Jiang, Ranvir B. Rana, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

NeurIPS 2018 Deepcode: Feedback Codes via Deep Learning Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

JMLR 2018 Generalized Rank-Breaking: Computational and Statistical Tradeoffs Ashish Khetan, Sewoong Oh

JMLR 2018 Learning from Comparisons and Choices Sahand Negahban, Sewoong Oh, Kiran K. Thekumparampil, Jiaming Xu

NeurIPS 2018 PacGAN: The Power of Two Samples in Generative Adversarial Networks Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh

NeurIPS 2018 Robustness of Conditional GANs to Noisy Labels Kiran K Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh

NeurIPS 2017 Discovering Potential Correlations via Hypercontractivity Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

NeurIPS 2017 Estimating Mutual Information for Discrete-Continuous Mixtures Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath

NeurIPS 2017 Matrix Norm Estimation from a Few Entries Ashish Khetan, Sewoong Oh

NeurIPS 2017 Optimal Sample Complexity of M-Wise Data for Top-K Ranking Minje Jang, Sunghyun Kim, Changho Suh, Sewoong Oh

NeurIPS 2016 Achieving Budget-Optimality with Adaptive Schemes in Crowdsourcing Ashish Khetan, Sewoong Oh

NeurIPS 2016 Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation Weihao Gao, Sewoong Oh, Pramod Viswanath

NeurIPS 2016 Computational and Statistical Tradeoffs in Learning to Rank Ashish Khetan, Sewoong Oh

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

ICML 2016 Data-Driven Rank Breaking for Efficient Rank Aggregation Ashish Khetan, Sewoong Oh

JMLR 2016 Data-Driven Rank Breaking for Efficient Rank Aggregation Ashish Khetan, Sewoong Oh

JMLR 2016 Extremal Mechanisms for Local Differential Privacy Peter Kairouz, Sewoong Oh, Pramod Viswanath

ICML 2016 Metadata-Conscious Anonymous Messaging Giulia Fanti, Peter Kairouz, Sewoong Oh, Kannan Ramchandran, Pramod Viswanath

ICML 2016 Optimality of Belief Propagation for Crowdsourced Classification Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi

NeurIPS 2015 Collaboratively Learning Preferences from Ordinal Data Sewoong Oh, Kiran K Thekumparampil, Jiaming Xu

NeurIPS 2015 Secure Multi-Party Differential Privacy Peter Kairouz, Sewoong Oh, Pramod Viswanath

ICML 2015 The Composition Theorem for Differential Privacy Peter Kairouz, Sewoong Oh, Pramod Viswanath

NeurIPS 2014 Extremal Mechanisms for Local Differential Privacy Peter Kairouz, Sewoong Oh, Pramod Viswanath

NeurIPS 2014 Learning Mixed Multinomial Logit Model from Ordinal Data Sewoong Oh, Devavrat Shah

COLT 2014 Learning Mixtures of Discrete Product Distributions Using Spectral Decompositions Prateek Jain, Sewoong Oh

NeurIPS 2014 Minimax-Optimal Inference from Partial Rankings Bruce Hajek, Sewoong Oh, Jiaming Xu

NeurIPS 2014 Provable Tensor Factorization with Missing Data Prateek Jain, Sewoong Oh

NeurIPS 2012 Iterative Ranking from Pair-Wise Comparisons Sahand Negahban, Sewoong Oh, Devavrat Shah

NeurIPS 2011 Iterative Learning for Reliable Crowdsourcing Systems David R. Karger, Sewoong Oh, Devavrat Shah

JMLR 2010 Matrix Completion from Noisy Entries Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh

NeurIPS 2009 Matrix Completion from Noisy Entries Raghunandan Keshavan, Andrea Montanari, Sewoong Oh