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Featured Co-authors

Zhangyang Wang
245 publications
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58 publications
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37 publications
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27 publications
Gonzalo Mateos
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Abolfazl Hashemi
19 publications
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research

∙ 08/28/2023

XVir: A Transformer-Based Architecture for Identifying Viral Reads from Cancer Samples

It is estimated that approximately 15 viral infections. The viruses that...

0 Shorya Consul, et al. ∙

research

∙ 02/21/2023

Automotive RADAR sub-sampling via object detection networks: Leveraging prior signal information

Automotive radar has increasingly attracted attention due to growing int...

0 Madhumitha Sakthi, et al. ∙

research

∙ 01/21/2023

The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation

Heterogeneity of data distributed across clients limits the performance ...

0 Huancheng Chen, et al. ∙

research

∙ 06/01/2022

Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data

Federated learning (FL) is a privacy-promoting framework that enables po...

0 Huancheng Chen, et al. ∙

research

∙ 05/13/2022

Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints

Federated learning systems facilitate training of global models in setti...

3 Mónica Ribero, et al. ∙

research

∙ 03/08/2022

End-to-end system for object detection from sub-sampled radar data

Robust and accurate sensing is of critical importance for advancing auto...

0 Madhumitha Sakthi, et al. ∙

research

∙ 12/18/2021

Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better

Federated learning (FL) enables distribution of machine learning workloa...

0 Sameer Bibikar, et al. ∙

research

∙ 03/24/2021

Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications

Pervasive computing applications commonly involve user's personal smartp...

0 Sangsu Lee, et al. ∙

research

∙ 11/20/2020

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization

In decentralized optimization, it is common algorithmic practice to have...

2 Abolfazl Hashemi, et al. ∙

research

∙ 11/16/2020

Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder

Identification of the type of communication technology and/or modulation...

0 Ziqi Ke, et al. ∙

research

∙ 07/30/2020

Communication-Efficient Federated Learning via Optimal Client Sampling

Federated learning is a private and efficient framework for learning mod...

0 Mónica Ribero, et al. ∙

research

∙ 03/01/2020

Federating Recommendations Using Differentially Private Prototypes

Machine learning methods allow us to make recommendations to users in ap...

0 Mónica Ribero, et al. ∙

research

∙ 12/27/2019

Evolutionary Clustering via Message Passing

We are often interested in clustering objects that evolve over time and ...

24 Natalia M. Arzeno, et al. ∙

research

∙ 12/25/2019

A Study of the Learnability of Relational Properties (Model Counting Meets Machine Learning)

Relational properties, e.g., the connectivity structure of nodes in a di...

0 Muhammad Usman, et al. ∙

research

∙ 11/27/2019

ComHapDet: A Spatial Community Detection Algorithm for Haplotype Assembly

Background: Haplotypes, the ordered lists of single nucleotide variation...

0 Abishek Sankararaman, et al. ∙

research

∙ 11/13/2019

A Graph Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction

Reconstructing components of a genomic mixture from data obtained by mea...

0 Ziqi Ke, et al. ∙

research

∙ 09/27/2019

Identifying Low-Dimensional Structures in Markov Chains: A Nonnegative Matrix Factorization Approach

A variety of queries about stochastic systems boil down to study of Mark...

0 Mahsa Ghasemi, et al. ∙

research

∙ 07/22/2019

Stochastic-Greedy++: Closing the Optimality Gap in Exact Weak Submodular Maximization

Many problems in discrete optimization can be formulated as the task of ...

0 Gustavo de Veciana, et al. ∙

research

∙ 10/29/2018

Evolutionary Self-Expressive Models for Subspace Clustering

The problem of organizing data that evolves over time into clusters is e...

0 Abolfazl Hashemi, et al. ∙

research

∙ 06/13/2018

Matrix Completion and Performance Guarantees for Single Individual Haplotyping

Single individual haplotyping is an NP-hard problem that emerges when at...

0 Somsubhra Barik, et al. ∙

research

∙ 10/31/2017

Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation

We study the problem of sampling a bandlimited graph signal in the prese...

0 Abolfazl Hashemi, et al. ∙

research

∙ 10/31/2017

Accelerated Sparse Subspace Clustering

State-of-the-art algorithms for sparse subspace clustering perform spect...

0 Abolfazl Hashemi, et al. ∙

research

∙ 08/08/2016

Sparse recovery via Orthogonal Least-Squares under presence of Noise

We consider the Orthogonal Least-Squares (OLS) algorithm for the recover...

0 Abolfazl Hashemi, et al. ∙

research

∙ 08/08/2016

Sampling Requirements and Accelerated Schemes for Sparse Linear Regression with Orthogonal Least-Squares

The Orthogonal Least Squares (OLS) algorithm sequentially selects column...

0 Abolfazl Hashemi, et al. ∙

research

∙ 02/22/2016

Sparse Linear Regression via Generalized Orthogonal Least-Squares

Sparse linear regression, which entails finding a sparse solution to an ...

0 Abolfazl Hashemi, et al. ∙

research

∙ 11/19/2014

Designing Optimal Mortality Risk Prediction Scores that Preserve Clinical Knowledge

Many in-hospital mortality risk prediction scores dichotomize predictive...

0 Natalia M. Arzeno, et al. ∙

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