Search
Now showing items 1-10 of 11
Functional Query Languages with Categorical Types
(2014-02-25)
We study three category-theoretic types in the context of functional query languages (typed lambda-calculi extended with additional operations for bulk data processing). The types we study are:
A Uniform Min-Max Theorem and Characterizations of Computational Randomness
(2014-02-25)
This thesis develops several tools and techniques using ideas from information theory, optimization, and online learning, and applies them to a number of highly related fundamental problems in complexity theory, pseudorandomness ...
Data Mining Chemistry and Crystal Structure
(2014-06-06)
The availability of large amounts of data generated by high-throughput computing and experimentation has generated interest in the application of machine learning techniques to materials science. Machine learning of materials ...
Revisiting Random Utility Models
(2014-06-06)
This thesis explores extensions of Random Utility Models (RUMs), providing more flexible models and adopting a computational perspective. This includes building new models and understanding their properties such as ...
Limiting Disclosure in Annotated Graphs
(2014-06-06)
Data is increasingly represented in annotated graphs, but graphs pose novel security and privacy challenges that at present lack solutions. We begin by identifying the new challenges graphs introduce and explain why existing ...
Computations and Algorithms in Physical and Biological Problems
(2014-06-06)
This dissertation presents the applications of state-of-the-art computation techniques and data analysis algorithms in three physical and biological problems: assembling DNA pieces, optimizing self-assembly yield, and ...
Perception, Cognition, and Effectiveness of Visualizations with Applications in Science and Engineering
(2014-06-06)
Visualization is a powerful tool for data exploration and analysis. With data ever-increasing in quantity and becoming integrated into our daily lives, having effective visualizations is necessary. But how does one design ...
Stable and Efficient Sparse Recovery for Machine Learning and Wireless Communication
(2014-06-06)
Recent theoretical study shows that the sparsest solution to an underdetermined linear system is unique, provided the solution vector is sufficiently sparse, and the operator matrix has sufficiently incoherent column ...
Eliciting and Aggregating Truthful and Noisy Information
(2014-10-21)
In the modern world, making informed decisions requires obtaining and aggregating relevant information about events of interest. For many political, business, and entertainment events, the information of interest only ...
Accelerating Markov chain Monte Carlo via parallel predictive prefetching
(2014-10-21)
We present a general framework for accelerating a large class of widely used Markov chain Monte Carlo (MCMC) algorithms. This dissertation demonstrates that MCMC inference can be accelerated in a model of parallel computation ...