50 citations · 82 across the 23 of their papers we have counts for
25 papers
Fast Distributed Optimization over Directed Graphs under Malicious Attacks using Trust
Arif Kerem Dayı, Orhan Eren Akgün, Stephanie Gil +2
In this work, we introduce the Resilient Projected Push-Pull (RP3) algorithm designed for distributed optimization in multi-agent cyber-physical systems with directed communication…
Privacy Preserving Semi-Decentralized Mean Estimation over Intermittently-Connected Networks
Rajarshi Saha, Mohamed Seif, Michal Yemini +2
We consider the problem of privately estimating the mean of vectors distributed across different nodes of an unreliable wireless network, where communications between nodes can fai…
How Physicality Enables Trust: A New Era of Trust-Centered Cyberphysical Systems
Stephanie Gil, Michal Yemini, Arsenia Chorti +3
Multi-agent cyberphysical systems enable new capabilities in efficiency, resilience, and security. The unique characteristics of these systems prompt a reevaluation of their securi…
Exploiting Trust for Resilient Hypothesis Testing with Malicious Robots (evolved version)
Matthew Cavorsi, Orhan Eren Akgün, Michal Yemini +2
We develop a resilient binary hypothesis testing framework for decision making in adversarial multi-robot crowdsensing tasks. This framework exploits stochastic trust observations…
Collaborative Mean Estimation over Intermittently Connected Networks with Peer-To-Peer Privacy
Rajarshi Saha, Mohamed Seif, Michal Yemini +2
This work considers the problem of Distributed Mean Estimation (DME) over networks with intermittent connectivity, where the goal is to learn a global statistic over the data sampl…
Resilient Distributed Optimization for Multi-Agent Cyberphysical Systems
Michal Yemini, Angelia Nedić, Andrea J. Goldsmith +1
This work focuses on the problem of distributed optimization in multi-agent cyberphysical systems, where a legitimate agent's iterates are influenced both by the values it receives…
Exploiting Trust for Resilient Hypothesis Testing with Malicious Robots
Matthew Cavorsi, Orhan Eren Akgün, Michal Yemini +2
We develop a resilient binary hypothesis testing framework for decision making in adversarial multi-robot crowdsensing tasks. This framework exploits stochastic trust observations…
Multi-Armed Bandits with Self-Information Rewards
Nir Weinberger, Michal Yemini
This paper introduces the informational multi-armed bandit (IMAB) model in which at each round, a player chooses an arm, observes a symbol, and receives an unobserved reward in the…
Semi-Decentralized Federated Learning with Collaborative Relaying
Michal Yemini, Rajarshi Saha, Emre Ozfatura +2
We present a semi-decentralized federated learning algorithm wherein clients collaborate by relaying their neighbors' local updates to a central parameter server (PS). At every com…
Restless Multi-Armed Bandits under Exogenous Global Markov Process
Tomer Gafni, Michal Yemini, Kobi Cohen
We consider an extension to the restless multi-armed bandit (RMAB) problem with unknown arm dynamics, where an unknown exogenous global Markov process governs the rewards distribut…
Robust Federated Learning with Connectivity Failures: A Semi-Decentralized Framework with Collaborative Relaying
Michal Yemini, Rajarshi Saha, Emre Ozfatura +2
Intermittent connectivity of clients to the parameter server (PS) is a major bottleneck in federated edge learning frameworks. The lack of constant connectivity induces a large gen…
Learning in Restless Bandits under Exogenous Global Markov Process
Tomer Gafni, Michal Yemini, Kobi Cohen
We consider an extension to the restless multi-armed bandit (RMAB) problem with unknown arm dynamics, where an unknown exogenous global Markov process governs the rewards distribut…
Cloud-Cluster Architecture for Detection in Intermittently Connected Sensor Networks
Michal Yemini, Stephanie Gil, Andrea J. Goldsmith
We consider a centralized detection problem where sensors experience noisy measurements and intermittent connectivity to a centralized fusion center. The sensors collaborate locall…
Characterizing Trust and Resilience in Distributed Consensus for Cyberphysical Systems
Michal Yemini, Angelia Nedić, Andrea Goldsmith +1
This work considers the problem of resilient consensus where stochastic values of trust between agents are available. Specifically, we derive a unified mathematical framework to ch…
Interference Reduction in Virtual Cell Optimization
Michal Yemini, Elza Erkip, Andrea J. Goldsmith
Virtual cell optimization clusters cells into neighborhoods and performs optimized resource allocation over each neighborhood. In prior works we proposed resource allocation scheme…
Exploiting Local and Cloud Sensor Fusion in Intermittently Connected Sensor Networks
Michal Yemini, Stephanie Gil, Andrea Goldsmith
We consider a detection problem where sensors experience noisy measurements and intermittent communication opportunities to a centralized fusion center (or cloud). The objective of…
Virtual Cell Clustering with Optimal Resource Allocation to Maximize Capacity
Michal Yemini, Andrea J. Goldsmith
This work proposes a new resource allocation optimization and network management framework for wireless networks using neighborhood-based optimization rather than fully centralized…
The Restless Hidden Markov Bandit with Linear Rewards and Side Information
Michal Yemini, Amir Leshem, Anelia Somekh-Baruch
In this paper we present a model for the hidden Markovian bandit problem with linear rewards. As opposed to current work on Markovian bandits, we do not assume that the state is kn…
Virtual Cell Clustering with Optimal Resource Allocation to Maximize Cellular System Capacity
Michal Yemini, Andrea J. Goldsmith
This work presents a new network optimization framework for cellular networks using neighborhood-based optimization. Under this optimization framework resources are allocated withi…
Optimal Resource Allocation for Cellular Networks with Virtual Cell Joint Decoding
Michal Yemini, Andrea J. Goldsmith
This work presents a new resource allocation optimization framework for cellular networks using neighborhood-based optimization. Under this optimization framework resources are all…
"Fog" Optimization via Virtual Cells in Cellular Network Resource Allocation
Michal Yemini, Andrea J. Goldsmith
This work proposes a new resource allocation optimization framework for cellular networks using "fog" or neighborhood-based optimization rather than fully centralized or fully dece…
Phase Noise Compensation for OFDM Systems
Amir Leshem, Michal Yemini
We describe a low complexity method for time domain compensation of phase noise in OFDM systems. We extend existing methods in several respects. First we suggest using the Karhunen…
On Simultaneous Percolation with Two Disk Types
Michal Yemini, Anelia Somekh-Baruch, Reuven Cohen +1
In this paper we consider the simultaneous percolation of two Gilbert disk models. The two models are connected through excluding disks, which prevent elements of the second model…
On the Multiple Access Channel with Asynchronous Cognition
Michal Yemini, Anelia Somekh-Baruch, Amir Leshem
In this paper we introduce the two-user asynchronous cognitive multiple access channel (ACMAC). This channel model includes two transmitters, an uninformed one, and an informed one…