Designing reinforcement learning algorithms for digital interventions: pre-implementation guidelines
Online reinforcement learning (RL) algorithms are increasingly used to personalize digital
interventions in the fields of mobile health and online education. Common challenges in …
interventions in the fields of mobile health and online education. Common challenges in …
Toward a taxonomy of trust for probabilistic machine learning
Probabilistic machine learning increasingly informs critical decisions in medicine,
economics, politics, and beyond. To aid the development of trust in these decisions, we …
economics, politics, and beyond. To aid the development of trust in these decisions, we …
Community Detection and Classification Guarantees Using Embeddings Learned by Node2Vec
Embedding the nodes of a large network into an Euclidean space is a common objective in
modern machine learning, with a variety of tools available. These embeddings can then be …
modern machine learning, with a variety of tools available. These embeddings can then be …
[PDF][PDF] Community Detection Guarantees Using Embeddings Learned by Node2Vec
Embedding the nodes of a large network into an Euclidean space is a common objective in
modern machine learning, with a variety of tools available. These embeddings can then be …
modern machine learning, with a variety of tools available. These embeddings can then be …
[图书][B] Latent Variable Models for Events on Social Networks
OG Ward - 2022 - search.proquest.com
Network data, particularly social network data, is widely collected in the context of
interactions between users of online platforms, but it can also be observed directly, such as …
interactions between users of online platforms, but it can also be observed directly, such as …
Scalable Community Detection in Massive Networks using Aggregated Relational Data
The mixed membership stochastic blockmodel (MMSB) is a popular Bayesian network
model for community detection. Fitting such large Bayesian network models quickly …
model for community detection. Fitting such large Bayesian network models quickly …