Sewoong Oh

Orcid: 0000-0002-8975-8306

According to our database1, Sewoong Oh authored at least 144 papers between 2008 and 2024.

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Bibliography

2024
On the Convergence of Differentially-Private Fine-tuning: To Linearly Probe or to Fully Fine-tune?
CoRR, 2024

Privacy-Preserving Instructions for Aligning Large Language Models.
CoRR, 2024

DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning.
CoRR, 2024

2023
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes.
IEEE J. Sel. Areas Inf. Theory, 2023

DPZero: Dimension-Independent and Differentially Private Zeroth-Order Optimization.
CoRR, 2023

Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning.
CoRR, 2023

Can Public Large Language Models Help Private Cross-device Federated Learning?
CoRR, 2023

Challenges towards the Next Frontier in Privacy.
CoRR, 2023

One-shot Empirical Privacy Estimation for Federated Learning.
CoRR, 2023

Near Optimal Private and Robust Linear Regression.
CoRR, 2023

On the Connection between Pre-training Data Diversity and Fine-tuning Robustness.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unleashing the Power of Randomization in Auditing Differentially Private ML.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improving multimodal datasets with image captioning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Label Poisoning is All You Need.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023


Private Federated Learning with Autotuned Compression.
Proceedings of the International Conference on Machine Learning, 2023

CRISP: Curriculum based Sequential neural decoders for Polar code family.
Proceedings of the International Conference on Machine Learning, 2023

Why Is Public Pretraining Necessary for Private Model Training?
Proceedings of the International Conference on Machine Learning, 2023

Few-shot Backdoor Attacks via Neural Tangent Kernels.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning to Generate Image Embeddings with User-Level Differential Privacy.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
MAUVE Scores for Generative Models: Theory and Practice.
CoRR, 2022

Stochastic optimization on matrices and a graphon McKean-Vlasov limit.
CoRR, 2022

Towards a Defense against Backdoor Attacks in Continual Federated Learning.
CoRR, 2022

Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

DP-PCA: Statistically Optimal and Differentially Private PCA.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Zonotope Domains for Lagrangian Neural Network Verification.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

De novo mass spectrometry peptide sequencing with a transformer model.
Proceedings of the International Conference on Machine Learning, 2022

MAML and ANIL Provably Learn Representations.
Proceedings of the International Conference on Machine Learning, 2022

Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise.
Proceedings of the Tenth International Conference on Learning Representations, 2022

FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Proof-of-Stake Longest Chain Protocols: Security vs Predictability.
Proceedings of the 2022 ACM Workshop on Developments in Consensus, 2022

Differential privacy and robust statistics in high dimensions.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022


Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Gradient flows on graphons: existence, convergence, continuity equations.
CoRR, 2021

Reducing the Communication Cost of Federated Learning through Multistage Optimization.
CoRR, 2021

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral.
CoRR, 2021

Sample Efficient Linear Meta-Learning by Alternating Minimization.
CoRR, 2021

SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics.
CoRR, 2021

Efficient Algorithms for Federated Saddle Point Optimization.
CoRR, 2021

Statistically and Computationally Efficient Linear Meta-representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Robust and differentially private mean estimation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Gradient Inversion with Generative Image Prior.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding.
Proceedings of the IEEE International Symposium on Information Theory, 2021

KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Defense against backdoor attacks via robust covariance estimation.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks.
Proc. ACM Meas. Anal. Comput. Syst., 2020

PacGAN: The Power of Two Samples in Generative Adversarial Networks.
IEEE J. Sel. Areas Inf. Theory, 2020

Physical Layer Communication via Deep Learning.
IEEE J. Sel. Areas Inf. Theory, 2020

Deepcode: Feedback Codes via Deep Learning.
IEEE J. Sel. Areas Inf. Theory, 2020

LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks.
IEEE J. Sel. Areas Inf. Theory, 2020

Guest Editorial.
IEEE J. Sel. Areas Inf. Theory, 2020

Deepcode and Modulo-SK are Designed for Different Settings.
CoRR, 2020

Joint Channel Coding and Modulation via Deep Learning.
Proceedings of the 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2020

Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robust Meta-learning for Mixed Linear Regression with Small Batches.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimal transport mapping via input convex neural networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Meta-learning for Mixed Linear Regression.
Proceedings of the 37th International Conference on Machine Learning, 2020

InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs.
Proceedings of the 37th International Conference on Machine Learning, 2020

Feedback Turbo Autoencoder.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Learning in Gated Neural Networks.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Spectrum Estimation from a Few Entries.
J. Mach. Learn. Res., 2019

Proof-of-Stake Longest Chain Protocols Revisited.
CoRR, 2019

InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers.
CoRR, 2019

Robust conditional GANs under missing or uncertain labels.
CoRR, 2019

Minimax Rates of Estimating Approximate Differential Privacy.
CoRR, 2019

DEEPTURBO: Deep Turbo Decoder.
Proceedings of the 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2019

Efficient Algorithms for Smooth Minimax Optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Barracuda: The Power of ℓ-polling in Proof-of-Stake Blockchains.
Proceedings of the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2019

Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms.
Proceedings of the 36th International Conference on Machine Learning, 2019

Rate Distortion For Model Compression: From Theory To Practice.
Proceedings of the 36th International Conference on Machine Learning, 2019

Compounding of Wealth in Proof-of-Stake Cryptocurrencies.
Proceedings of the Financial Cryptography and Data Security, 2019

Iterative Bayesian Learning for Crowdsourced Regression.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Learning One-hidden-layer Neural Networks under General Input Distributions.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Optimal Inference in Crowdsourced Classification via Belief Propagation.
IEEE Trans. Inf. Theory, 2018

Demystifying Fixed k-Nearest Neighbor Information Estimators.
IEEE Trans. Inf. Theory, 2018

Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation.
IEEE Trans. Inf. Theory, 2018

Learning from Comparisons and Choices.
J. Mach. Learn. Res., 2018

Generalized Rank-Breaking: Computational and Statistical Tradeoffs.
J. Mach. Learn. Res., 2018

Number of Connected Components in a Graph: Estimation via Counting Patterns.
CoRR, 2018

Rate Distortion For Model Compression: From Theory To Practice.
CoRR, 2018

Attention-based Graph Neural Network for Semi-supervised Learning.
CoRR, 2018

Robustness of conditional GANs to noisy labels.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Communication Algorithms via Deep Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
The Composition Theorem for Differential Privacy.
IEEE Trans. Inf. Theory, 2017

Hiding the Rumor Source.
IEEE Trans. Inf. Theory, 2017

Rank Centrality: Ranking from Pairwise Comparisons.
Oper. Res., 2017

Discovering Potential Correlations via Hypercontractivity.
Entropy, 2017

Efficient Learning for Crowdsourced Regression.
CoRR, 2017

Matrix Factorization at the Frontier of Non-convex Optimizations: Abstract for SIGMETRICS 2017 Rising Star Award Talk.
Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Urbana-Champaign, IL, USA, June 05, 2017

Matrix Norm Estimation from a Few Entries.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Optimal Sample Complexity of M-wise Data for Top-K Ranking.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Estimating Mutual Information for Discrete-Continuous Mixtures.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Density functional estimators with k-nearest neighbor bandwidths.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016
Metadata-Conscious Anonymous Messaging.
IEEE Trans. Signal Inf. Process. over Networks, 2016

Detecting Sponsored Recommendations.
ACM Trans. Model. Perform. Evaluation Comput. Syst., 2016

Data-driven Rank Breaking for Efficient Rank Aggregation.
J. Mach. Learn. Res., 2016

Extremal Mechanisms for Local Differential Privacy.
J. Mach. Learn. Res., 2016

Reliable Crowdsourcing under the Generalized Dawid-Skene Model.
CoRR, 2016

Top-K Ranking from Pairwise Comparisons: When Spectral Ranking is Optimal.
CoRR, 2016

Causal Strength via Shannon Capacity: Axioms, Estimators and Applications.
CoRR, 2016

Rumor Source Obfuscation on Irregular Trees.
Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science, 2016

Achieving budget-optimality with adaptive schemes in crowdsourcing.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Computational and Statistical Tradeoffs in Learning to Rank.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Optimality of Belief Propagation for Crowdsourced Classification.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Differentially private multi-party computation.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

2015
The Staircase Mechanism in Differential Privacy.
IEEE J. Sel. Top. Signal Process., 2015

Spy vs. Spy: Rumor Source Obfuscation.
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015

Collaboratively Learning Preferences from Ordinal Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Secure Multi-party Differential Privacy.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems.
Oper. Res., 2014

Spy vs. Spy: Rumor Source Obfuscation.
CoRR, 2014

Optimality of Non-Interactive Randomized Response.
CoRR, 2014

What's your choice?: learning the mixed multi-nomial.
Proceedings of the ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 2014

Assessment of ENC sounding by Delaunay Triangulation method in aspect of fine compilation for safe navigation.
Proceedings of the 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS), 2014

Learning Mixed Multinomial Logit Model from Ordinal Data.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Minimax-optimal Inference from Partial Rankings.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Provable Tensor Factorization with Missing Data.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Mixtures of Discrete Product Distributions using Spectral Decompositions.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Calibration Using Matrix Completion With Application to Ultrasound Tomography.
IEEE Trans. Signal Process., 2013

Robust Localization From Incomplete Local Information.
IEEE/ACM Trans. Netw., 2013

The Composition Theorem for Differential Privacy.
CoRR, 2013

Efficient crowdsourcing for multi-class labeling.
Proceedings of the ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 2013

2012
Counting with the Crowd.
Proc. VLDB Endow., 2012

Iterative ranking from pair-wise comparisons.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Gossip PCA.
Proceedings of the SIGMETRICS 2011, 2011

Iterative Learning for Reliable Crowdsourcing Systems.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Budget-optimal crowdsourcing using low-rank matrix approximations.
Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010
Matrix completion from a few entries.
IEEE Trans. Inf. Theory, 2010

Matrix Completion from Noisy Entries.
J. Mach. Learn. Res., 2010

Calibration for Ultrasound Breast Tomography Using Matrix Completion
CoRR, 2010

Distributed sensor network localization from local connectivity: performance analysis for the HOP-TERRAIN algorithm.
Proceedings of the SIGMETRICS 2010, 2010

2009
A Gradient Descent Algorithm on the Grassman Manifold for Matrix Completion
CoRR, 2009

Low-rank matrix completion with noisy observations: A quantitative comparison.
Proceedings of the 47th Annual Allerton Conference on Communication, 2009

2008
Computing the threshold shift for general channels.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008

The slope scaling parameter for general channels, decoders, and ensembles.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008

Learning low rank matrices from O(n) entries.
Proceedings of the 46th Annual Allerton Conference on Communication, 2008


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