research
∙
09/07/2023
Noisy Computing of the 𝖮𝖱 and 𝖬𝖠𝖷 Functions
We consider the problem of computing a function of n variables using noi...
share
research
∙
08/17/2023
Efficient Algorithms for Attributed Graph Alignment with Vanishing Edge Correlation
Graph alignment refers to the task of finding the vertex correspondence ...
research
∙
06/21/2023
On the Optimal Bounds for Noisy Computing
We revisit the problem of computing with noisy information considered in...
research
∙
05/09/2023
Constructions for Nonadaptive Tropical Group Testing
PCR testing is an invaluable diagnostic tool that has most recently seen...
research
∙
03/02/2023
Specformer: Spectral Graph Neural Networks Meet Transformers
Spectral graph neural networks (GNNs) learn graph representations via sp...
research
∙
02/14/2023
A Bandit Approach to Online Pricing for Heterogeneous Edge Resource Allocation
Edge Computing (EC) offers a superior user experience by positioning clo...
research
∙
11/14/2022
A Lego-Brick Approach to Coding for Network Communication
Coding schemes for several problems in network information theory are co...
research
∙
06/29/2022
Adversarial Ensemble Training by Jointly Learning Label Dependencies and Member Models
Training an ensemble of different sub-models has empirically proven to b...
research
∙
02/03/2022
Noisy Sorting Capacity
Sorting is the task of ordering n elements using pairwise comparisons. I...
research
∙
01/25/2022
On the Feasible Region of Efficient Algorithms for Attributed Graph Alignment
Graph alignment aims at finding the vertex correspondence between two co...
research
∙
05/11/2021
Variants on Block Design Based Gradient Codes for Adversarial Stragglers
Gradient coding is a coding theoretic framework to provide robustness ag...
research
∙
02/01/2021
Attributed Graph Alignment
Motivated by various data science applications including de-anonymizing ...
research
∙
06/04/2020
Universal Graph Compression: Stochastic Block Models
Motivated by the prevalent data science applications of processing and m...
research
∙
06/17/2019
