activity
20132019
most citedMulti-layer graph analysis for dynamic social networks

47 citations · 65 across the 6 of their papers we have counts for

collaborators

9 papers

eess.SP2019

Time-Varying Interaction Estimation Using Ensemble Methods

Brandon Oselio, Amir Sadeghian, Silvio Savarese +1

Directed information (DI) is a useful tool to explore time-directed interactions in multivariate data. However, as originally formulated DI is not well suited to interactions that…

stat.ME2019★ 6 cited

Hierarchical network models for structured exchangeable interaction processes

Walter Dempsey, Brandon Oselio, Alfred Hero

Network data often arises via a series of structured interactions among a population of constituent elements. E-mail exchanges, for example, have a single sender followed by potent…

cs.IT2018

Learning to Bound the Multi-class Bayes Error

Salimeh Yasaei Sekeh, Brandon Oselio, Alfred O. Hero

In the context of supervised learning, meta learning uses features, metadata and other information to learn about the difficulty, behavior, or composition of the problem. Using thi…

cs.IT2018

A Dimension-Independent discriminant between distributions

Salimeh Yasaei Sekeh, Brandon Oselio, Alfred O. Hero

Henze-Penrose divergence is a non-parametric divergence measure that can be used to estimate a bound on the Bayes error in a binary classification problem. In this paper, we show t…

cs.CL2017★ 5 cited

Consistent Alignment of Word Embedding Models

Cem Safak Sahin, Rajmonda S. Caceres, Brandon Oselio +1

Word embedding models offer continuous vector representations that can capture rich contextual semantics based on their word co-occurrence patterns. While these word vectors can pr…

stat.ML2017★ 1 cited

Similarity Function Tracking using Pairwise Comparisons

Kristjan Greenewald, Stephen Kelley, Brandon Oselio +1

Recent work in distance metric learning has focused on learning transformations of data that best align with specified pairwise similarity and dissimilarity constraints, often supp…

cs.SI2015★ 5 cited

Information Extraction from Larger Multi-layer Social Networks

Brandon Oselio, Alex Kulesza, Alfred Hero

Social networks often encode community structure using multiple distinct types of links between nodes. In this paper we introduce a novel method to extract information from such mu…

cs.SI2015★ 1 cited

Socio-Spatial Pareto Frontiers of Twitter Networks

Brandon Oselio, Alex Kulesza, Alfred Hero

Social media provides a rich source of networked data. This data is represented by a set of nodes and a set of relations (edges). It is often possible to obtain or infer multiple t…

cs.SI2013★ 47 cited

Multi-layer graph analysis for dynamic social networks

Brandon Oselio, Alex Kulesza, Alfred O. Hero

Modern social networks frequently encompass multiple distinct types of connectivity information; for instance, explicitly acknowledged friend relationships might complement behavio…