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20082024
most citedOptimal Pricing to Manage Electric Vehicles in Coupled Power and Transportation Networks

257 citations · 1.4k across the 55 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

stat.ML2021★ 1 cited

Open Problem: Tight Online Confidence Intervals for RKHS Elements

Sattar Vakili, Jonathan Scarlett, Tara Javidi

Confidence intervals are a crucial building block in the analysis of various online learning problems. The analysis of kernel based bandit and reinforcement learning problems utili…

math.OC2021

Decentralized Asynchronous Non-convex Stochastic Optimization on Directed Graphs

Vyacheslav Kungurtsev, Mahdi Morafah, Tara Javidi +1

Distributed Optimization is an increasingly important subject area with the rise of multi-agent control and optimization. We consider a decentralized stochastic optimization proble…

cs.LG2021

Trojan Signatures in DNN Weights

Greg Fields, Mohammad Samragh, Mojan Javaheripi +2

Deep neural networks have been shown to be vulnerable to backdoor, or trojan, attacks where an adversary has embedded a trigger in the network at training time such that the model…

cs.LG2021

Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo

Vyacheslav Kungurtsev, Adam Cobb, Tara Javidi +1

Federated learning performed by a decentralized networks of agents is becoming increasingly important with the prevalence of embedded software on autonomous devices. Bayesian appro…

cs.LG2021★ 167 cited

A Field Guide to Federated Optimization

Jianyu Wang, Zachary Charles, Zheng Xu +50

Federated learning and analytics are a distributed approach for collaboratively learning models (or statistics) from decentralized data, motivated by and designed for privacy prote…

eess.SP2021

Active and Dynamic Beam Tracking UnderStochastic Mobility

Nancy Ronquillo, Tara Javidi

We consider the problem of active and sequential beam tracking at mmWave frequencies and above. We focus on the dynamic scenario of a UAV to UAV communications where we formulate t…