Dissertation Defenses

Integrating visualization grammars with the task language of data analysts

Sample-Efficient Algorithms for Hard-Exploration Problems in Reinforcement Learning

Sample-Efficient Algorithms for Hard-Exploration Problems in Reinforcement Learning

Integrating visualization grammars with the task language of data analysts

Toward Practical Application-Aware Big Data Systems

Modeling Trading Strategies in Financial Markets with Data, Simulation, and Deep Reinforcement Learning

Advances in Deep Reinforcement Learning: Intrinsic Rewards, Temporal Credit Assignment, State Representations, and Value-equivalent Models

Improving Application Connectivity with Network-conscious Systems

Assessment of Privacy Risks in Mobile and Web Applications

Application-Aware Scheduling in Deep Learning Software Stacks

Dynamic Connectivity, Hopsets, and Byzantine Agreement

Advancing Digital Safety for High-Risk Communities

The Value Equivalence Principle for Model-Based Reinforcement Learning

Context-Aware Detection and Resolution of Data Anomalies for Semi-Autonomous Cyber-Physical Systems

On Addressing the Problem of Discovery for Reinforcement Learning

Augmenting Structure with Text for Improved Graph Learning

Predictable Performance and Low Cost for Geo-Distributed Applications

Constructing Meaning, Piece by Piece: A Computational Cognitive Model of Human Sentence Comprehension

Towards Free, Open, and Ubiquitous Hardware Design

Incorporating Expert Interpretation and Reasoning to Guide Model Selection in Machine Learning

In-Memory Acceleration for General Data Parallel Applications

Improving Mobile Internet Performance with Cross-Device Network Transport and Cross-Layer Application Adaptation