×
We study learning in three networks capturing different features of real-world social networks: Erdös–Rényi (a baseline for connections among homogeneous individuals), Stochastic Block (reflecting network homophily), and Royal Family (that accommodates “influential individuals” along with local interactions).
Feb 9, 2023
Feb 9, 2023 · We study learning dynam- ics in three large-scale networks capturing features of real-world social networks: Erdös–Rényi, Stochastic Block ( ...
We study learning dynamics in three large-scale networks capturing features of real-world social networks: Erdös–Rényi, Stochastic Block (reflecting network ...
We study learning dynamics in three large-scale networks capturing features of real-world social networks: Erdös–Rényi, Stochastic Block (reflecting network ...
We study learning dynamics in three large-scale networks capturing features of real-world social networks: Erdös–Rényi, Stochastic Block (reflecting network ...
People also ask
A rich research programme on how social networks shape individual and collective learning. The present paper provides a summary of this research.
Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 × 2 games used by Selten and Chmura [1].
We theoretically and empirically study an incomplete information model of social learning. Agents initially guess the binary state of the world after ...
Machine Learning on Real World Networks (MLN) is an interdisciplinary graduate-level course that focuses on networks and their applications to natural and ...
Our experiments focus on two common prediction tasks in networks: a multi-label classification task, where every node is assigned one or more class labels and a ...