
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral
The spectacular success of deep generative models calls for quantitative...
read it

Sample Efficient Linear MetaLearning by Alternating Minimization
Metalearning synthesizes and leverages the knowledge from a given set o...
read it

SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics
Modern machine learning increasingly requires training on a large collec...
read it

Robust and Differentially Private Mean Estimation
Differential privacy has emerged as a standard requirement in a variety ...
read it

Efficient Algorithms for Federated Saddle Point Optimization
We consider strongly convexconcave minimax problems in the federated se...
read it

Eliminating Sharp Minima from SGD with Truncated Heavytailed Noise
The empirical success of deep learning is often attributed to SGD's myst...
read it

ReedMuller Subcodes: Machine LearningAided Design of Efficient Soft Recursive Decoding
ReedMuller (RM) codes are conjectured to achieve the capacity of any bi...
read it

Projection Efficient Subgradient Method and Optimal Nonsmooth FrankWolfe Method
We consider the classical setting of optimizing a nonsmooth Lipschitz co...
read it

Deepcode and ModuloSK are Designed for Different Settings
We respond to [1] which claimed that "ModuloSK scheme outperforms Deepc...
read it

Robust Metalearning for Mixed Linear Regression with Small Batches
A common challenge faced in practical supervised learning, such as medic...
read it

Metalearning for mixed linear regression
In modern supervised learning, there are a large number of tasks, but ma...
read it

Turbo Autoencoder: Deep learning based channel codes for pointtopoint communication channels
Designing codes that combat the noise in a communication medium has rema...
read it

ProofofStake Longest Chain Protocols Revisited
The Nakamoto longest chain protocol has served Bitcoin well in its decad...
read it

Barracuda: The Power of ℓpolling in ProofofStake Blockchains
A blockchain is a database of sequential events that is maintained by a ...
read it

PrivacyUtility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks
Payment channel networks (PCNs) are viewed as one of the most promising ...
read it

Optimal transport mapping via input convex neural networks
In this paper, we present a novel and principled approach to learn the o...
read it

Efficient Algorithms for Smooth Minimax Optimization
This paper studies first order methods for solving smooth minimax optimi...
read it

InfoGANCR: Disentangling Generative Adversarial Networks with Contrastive Regularizers
Training disentangled representations with generative adversarial networ...
read it

Robust conditional GANs under missing or uncertain labels
Matching the performance of conditional Generative Adversarial Networks ...
read it

Learning in Gated Neural Networks
Gating is a key feature in modern neural networks including LSTMs, GRUs ...
read it

Minimax Rates of Estimating Approximate Differential Privacy
Differential privacy has become a widely accepted notion of privacy, lea...
read it

DeepTurbo: Deep Turbo Decoder
Presentday communication systems routinely use codes that approach the ...
read it

Number of Connected Components in a Graph: Estimation via Counting Patterns
Due to the limited resources and the scale of the graphs in modern datas...
read it

LEARN Codes: Inventing Lowlatency Codes via Recurrent Neural Networks
Designing channel codes under low latency constraints is one of the most...
read it

Robustness of Conditional GANs to Noisy Labels
We study the problem of learning conditional generators from noisy label...
read it

Rate Distortion For Model Compression: From Theory To Practice
As the size of neural network models increases dramatically today, study...
read it

Learning Onehiddenlayer Neural Networks under General Input Distributions
Significant advances have been made recently on training neural networks...
read it

Compounding of Wealth in ProofofStake Cryptocurrencies
Proofofstake (PoS) is a promising approach for designing efficient blo...
read it

Deepcode: Feedback Codes via Deep Learning
The design of codes for communicating reliably over a statistically well...
read it

Communication Algorithms via Deep Learning
Coding theory is a central discipline underpinning wireline and wireless...
read it

Attentionbased Graph Neural Network for Semisupervised Learning
Recently popularized graph neural networks achieve the stateoftheart ...
read it

PacGAN: The power of two samples in generative adversarial networks
Generative adversarial networks (GANs) are innovative techniques for lea...
read it

Discovering Potential Correlations via Hypercontractivity
Discovering a correlation from one variable to another variable is of fu...
read it

Learning from Comparisons and Choices
When tracking userspecific online activities, each user's preference is...
read it

Spectrum Estimation from a Few Entries
Singular values of a data in a matrix form provide insights on the struc...
read it

Iterative Bayesian Learning for Crowdsourced Regression
Crowdsourcing platforms emerged as popular venues for purchasing human i...
read it

Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation
Estimators of information theoretic measures such as entropy and mutual ...
read it

Computational and Statistical Tradeoffs in Learning to Rank
For massive and heterogeneous modern datasets, it is of fundamental inte...
read it

Demystifying Fixed kNearest Neighbor Information Estimators
Estimating mutual information from i.i.d. samples drawn from an unknown ...
read it

TopK Ranking from Pairwise Comparisons: When Spectral Ranking is Optimal
We explore the topK rank aggregation problem. Suppose a collection of i...
read it

Optimal Inference in Crowdsourced Classification via Belief Propagation
Crowdsourcing systems are popular for solving largescale labelling task...
read it

Achieving Budgetoptimality with Adaptive Schemes in Crowdsourcing
Crowdsourcing platforms provide marketplaces where task requesters can p...
read it

Conditional Dependence via Shannon Capacity: Axioms, Estimators and Applications
We conduct an axiomatic study of the problem of estimating the strength ...
read it

Datadriven Rank Breaking for Efficient Rank Aggregation
Rank aggregation systems collect ordinal preferences from individuals to...
read it

Collaboratively Learning Preferences from Ordinal Data
In applications such as recommendation systems and revenue management, i...
read it

Learning Mixed Multinomial Logit Model from Ordinal Data
Motivated by generating personalized recommendations using ordinal (or p...
read it

Minimaxoptimal Inference from Partial Rankings
This paper studies the problem of inferring a global preference based on...
read it

Learning Mixtures of Discrete Product Distributions using Spectral Decompositions
We study the problem of learning a distribution from samples, when the u...
read it

Rank Centrality: Ranking from Pairwise Comparisons
The question of aggregating pairwise comparisons to obtain a global ran...
read it

BudgetOptimal Task Allocation for Reliable Crowdsourcing Systems
Crowdsourcing systems, in which numerous tasks are electronically distri...
read it
Sewoong Oh
verfied profile
Associate Professor at University of Washington