6 citations · 6 across the 4 of their papers we have counts for
6 papers
Parameterized Explanations for Investor / Company Matching
Simerjot Kaur, Ivan Brugere, Andrea Stefanucci +3
Matching companies and investors is usually considered a highly specialized decision making process. Building an AI agent that can automate such recommendation process can signific…
Privacy Shadow: Measuring Node Predictability and Privacy Over Time
Ivan Brugere, Tanya y. Berger-Wolf
The structure of network data enables simple predictive models to leverage local correlations between nodes to high accuracy on tasks such as attribute and link prediction. While t…
Inferring Network Structure From Data
Ivan Brugere, Tanya Y. Berger-Wolf
Networks are complex models for underlying data in many application domains. In most instances, raw data is not natively in the form of a network, but derived from sensors, logs, i…
Network Model Selection Using Task-Focused Minimum Description Length
Ivan Brugere, Tanya Y. Berger-Wolf
Networks are fundamental models for data used in practically every application domain. In most instances, several implicit or explicit choices about the network definition impact t…
Network Model Selection for Task-Focused Attributed Network Inference
Ivan Brugere, Chris Kanich, Tanya Y. Berger-Wolf
Networks are models representing relationships between entities. Often these relationships are explicitly given, or we must learn a representation which generalizes and predicts ob…
Evaluating Social Networks Using Task-Focused Network Inference
Ivan Brugere, Chris Kanich, Tanya Y. Berger-Wolf
Networks are representations of complex underlying social processes. However, the same given network may be more suitable to model one behavior of individuals than another. In many…