2 citations · 6 across the 15 of their papers we have counts for
15 papers
Approximate Simulation-Based Verification of Compatibility of the Friedkin-Johnsen Model with Binary Observations
Yu Xing, Aneesh Raghavan, Michael T. Schaub +1
We consider a verification problem for opinion dynamics based on binary observations. The opinion dynamics is governed by a Friedkin-Johnsen (FJ) model, where only a sequence of bi…
Almost Exact Recovery in Gossip Opinion Dynamics over Stochastic Block Models
Yu Xing, Karl H. Johansson
We study community detection based on state observations from gossip opinion dynamics over stochastic block models (SBM). It is assumed that a network is generated from a two-commu…
Joint Learning of Network Topology and Opinion Dynamics Based on Bandit Algorithms
Yu Xing, Xudong Sun, Karl H. Johansson
We study joint learning of network topology and a mixed opinion dynamics, in which agents may have different update rules. Such a model captures the diversity of real individual in…
What is the Expected Transient Behavior of Opinion Evolution for Two Communities?
Yu Xing, Karl H. Johansson
We study the transient behavior of a gossip model, in which agents randomly interact pairwise over a weighted graph with two communities. Edges within each community have identical…
Concentration in Gossip Opinion Dynamics over Random Graphs
Yu Xing, Karl Henrik Johansson
We study concentration inequalities in gossip opinion dynamics over random graphs. In the model, a network is generated from a random graph model with independent edges, and agents…
Transient Behavior of Gossip Opinion Dynamics with Community Structure
Yu Xing, Karl H. Johansson
We study transient behavior of gossip opinion dynamics, in which agents randomly interact pairwise over a weighted graph with two communities. Edges within a community have identic…
On the Convergence of mSGD and AdaGrad for Stochastic Optimization
Ruinan Jin, Yu Xing, Xingkang He
As one of the most fundamental stochastic optimization algorithms, stochastic gradient descent (SGD) has been intensively developed and extensively applied in machine learning in t…
Identification of Linear Systems with Multiplicative Noise from Multiple Trajectory Data
Yu Xing, Benjamin Gravell, Xingkang He +2
The paper studies identification of linear systems with multiplicative noise from multiple-trajectory data. An algorithm based on the least-squares method and multiple-trajectory d…
Event-Triggered Distributed Estimation With Decaying Communication Rate
Xingkang He, Yu Xing, Junfeng Wu +1
We study distributed estimation of a high-dimensional static parameter vector through a group of sensors whose communication network is modeled by a fixed directed graph. Different…
Community Structure Recovery and Interaction Probability Estimation for Gossip Opinion Dynamics
Yu Xing, Xingkang He, Haitao Fang +1
We study how to jointly recover the community structure and estimate the interaction probabilities of gossip opinion dynamics. In this process, agents randomly interact pairwise, a…
Community Detection for Gossip Dynamics with Stubborn Agents
Yu Xing, Xingkang He, Haitao Fang +1
We consider a community detection problem for gossip dynamics with stubborn agents in this paper. It is assumed that the communication probability matrix for agent pairs has a bloc…
Linear System Identification Under Multiplicative Noise from Multiple Trajectory Data
Yu Xing, Ben Gravell, Xingkang He +2
The study of multiplicative noise models has a long history in control theory but is re-emerging in the context of complex networked systems and systems with learning-based control…
Recursive Network Estimation From Binary-Valued Observation Data
Yu Xing, Xingkang He, Haitao Fang +1
This paper studies the problem of recursively estimating the weighted adjacency matrix of a network out of a temporal sequence of binary-valued observations. The observation sequen…
Network Weight Estimation for Binary-Valued Observation Models
Yu Xing, Xingkang He, Haitao Fang +1
This paper studies the estimation of network weights for a class of systems with binary-valued observations. In these systems only quantized observations are available for the netw…
A Strategic Learning Algorithm for State-based Games
Changxi Li, Yu Xing, Fenghua He +1
Learning algorithm design for state-based games is investigated. A heuristic uncoupled learning algorithm, which is a two memory better reply with inertia dynamics, is proposed. Un…