Colloquium- Multiplex Network Optimization: Capturing Cognition and Attention
April 16, 2018 -
11:15am to 12:15pm
University of Kansas
3-180 Keller Hall
Abstract: I will examine how procedures for optimally searching through "multiplex" networks (networks made of multiple simple graphs) capture human learning and search patterns. Prior work on semantic memory (people's memory for facts and concepts) has primarily focused on modeling similarity judgments of pairs of words as distances between points in a high-dimensional space (e.g., LSA by Landauer et al, 1998; Word2Vec by Mikolov et al. 2013). While these decisions seem to accurately account for human similarity judgments in some contexts, it is very difficult to interpret high dimensional spaces, making it hard to use such representations for scientific research. Further, it is difficult to adapt these spaces to a specific context or task. Instead, I define a series of simple networks that construct a multiplex network, where each network in the multiplex captures a "sense" or type of similarity between items -- for example the relationship between "moon" and "lamp" as compared to "moon" and "ball". I then optimize the "influence" of each of these feature networks within the multiplex framework where the weight of each network corresponds to the importance of each relationship. I use this approach to investigate how humans acquire language, and search through semantic memory. The resulting weighting of the multiplex can capture human attention and contextual information in these diverse domains. I explore how this approach can provide interpretability to multi-relational data and provide new insights in psychology and other fields by developing an optimization framework that considers not only the presence or absence of relationships but also the nature and importance of the relationships.
Biography: Nicole Beckage is an assistant professor at the University of Kansas in the Department of Electrical Engineering and Computer Science. She has dual PhDs from the University of Colorado, Boulder in Computer Science and Cognitive Science. She has published in venues such as Scientific Reports, PLOS ONE, and IEEE journals and has submitted grants to NSF, Google, Amazon, and others. She is the founding faculty member of the KU-Women in Computing Group and mentors underrepresented undergraduate and graduate students through CRA-W. Currently she is on leave from KU at University of Wisconsin-Madison as part of a DARPA grant focusing on scaleable cognitive models of social systems.