activity
20082021
most citedAnalysis of Distributed ADMM Algorithm for Consensus Optimization in Presence of Node Error

47 citations · 178 across the 34 of their papers we have counts for

collaborators

41 papers

cs.LG2021

How to Query An Oracle? Efficient Strategies to Label Data

Farshad Lahouti, Victoria Kostina, Babak Hassibi

We consider the basic problem of querying an expert oracle for labeling a dataset in machine learning. This is typically an expensive and time consuming process and therefore, we s…

cs.IT2019

Two-layer Coded Channel Access with Collision Resolution: Design and Analysis

MohammadReza Ebrahimi, Farshad Lahouti, Victoria Kostina

We propose a two-layer coding architecture for communication of multiple users over a shared slotted medium enabling joint collision resolution and decoding. Each user first encode…

eess.SP2019★ 47 cited

Analysis of Distributed ADMM Algorithm for Consensus Optimization in Presence of Node Error

Layla Majzoobi, Farshad Lahouti, Vahid Shah-Mansouri

Alternating Direction Method of Multipliers (ADMM) is a popular convex optimization algorithm, which can be employed for solving distributed consensus optimization problems. In thi…

q-bio.NC2018

Neuronal Synchronization Can Control the Energy Efficiency of Inter-Spike Interval Coding

Siavash Ghavami, Vahid Rahmati, Farshad Lahouti +1

The role of synchronous firing in sensory coding and cognition remains controversial. While studies, focusing on its mechanistic consequences in attentional tasks, suggest that syn…

cs.NI2018★ 3 cited

Resource Allocation in Heterogenous Full-duplex OFDMA Networks: Design and Analysis

Peyman Tehrani, Farshad Lahouti, Michele Zorzi

Recent studies indicate the feasibility of full-duplex (FD) bidirectional wireless communications. Due to its potential to increase the capacity, analyzing the performance of a cel…

cs.LG2017

Distributed Solution of Large-Scale Linear Systems via Accelerated Projection-Based Consensus

Navid Azizan-Ruhi, Farshad Lahouti, Salman Avestimehr +1

Solving a large-scale system of linear equations is a key step at the heart of many algorithms in machine learning, scientific computing, and beyond. When the problem dimension is…