Michtom School of Computer Science

Complexity in Coevolution and Deep Learning

Turning Machine Learning Inward: Automating Cloud Databases

Robust and Efficient Techniques in Deep Learning with applications in Computer Vision and Language Understanding 

Problem Solving Markov Models and Recursive Pedagogy

Learning to Perform Actions from Demonstrations with Sequential Modeling

Abstract Meaning Representation Parsing

Learning-based Interactive Data Exploration

Monte Carlo Simulation Generation Through Operationalization of Spatial Primitives

Profiling and Quality Assessment of Query Optimizers

Toward a Theory of the Evolution of Modularity Using Sequential-Subtask Environments and Development

Devel-Op: An Optimizer Development Environment