Robert Lindland

Robert  Lindland
MIT EECS | Quick Undergraduate Research and Innovation Scholar
Advisor: Gregory W. Wornell
Department: EECS
Areas of Research: Theory of Computer Systems
Years: 2019-2020
Research Project Title:

Universal Features for Graphs and Markov Chains via Modal Decomposition

abstract:Many modern problems in inference and systems design require access to complex distributions over a large domain. In general, memory constraints and intractable computations make it infeasible to model joint distributions within the domain. Current models make a strong and often unfounded assumption of mutual independence at the cost of inaccurate approximations. The goal of this project is to develop a graphical model that accounts for dependence over the domain and does so in a way that minimizes memory usage and query latency. To do so, we propose a tree-structured model of the data and introduce a modal decomposition drawn from principles in information geometry to factor the distribution in a way that is accurate and does not exhaust memory.
About:

"This SuperUROP project is exciting because it allows me to explore concepts from and contribute to active research fields in information theory and machine learning. I hope to learn more about graphical models and information geometry and gain experience to improve my research skills."