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Investigating Non-Periodic Solids Using First Principles Calculations and Machine Learning Algorithms
(2016-05-18)
Computational methods are expected to play an increasingly important role in materials design. In order to live up to these expectations, simulations need to have predictive power. To achieve this, there are two hurdles, ...
Modeling, Inference and Optimization With Composable Differentiable Procedures
(2016-05-14)
This thesis presents five contributions to machine learning, with themes of differentiability and Bayesian inference.
We present Firefly Monte Carlo, an auxiliary variable Markov chain Monte Carlo algorithm that only ...
Design and Modeling of Specialized Architectures
(2016-05-19)
Hardware acceleration in the form of customized datapath and control circuitry tuned to specific applications has gained popularity for its promise to utilize transistors more efficiently. However, architectural research ...
Bayesian Methods for Discovering Structure in Neural Spike Trains
(2016-05-18)
Neuroscience is entering an exciting new age. Modern recording technologies enable simultaneous measurements of thousands of neurons in organisms performing complex behaviors. Such recordings offer an unprecedented opportunity ...
Graph-Based Data Mining in Neuroimaging of Neurological Diseases
(2016-05-02)
The human brain is one of the most complex network systems. Understanding the organization of the brain is crucial for the diagnosis and treatment of brain disorders. Recent advances in neuroimaging enable a non-invasive ...
New Separations in the Complexity of Differential Privacy
(2016-08-03)
In this thesis, we study when algorithmic tasks can be performed on sensitive data while protecting the privacy of individuals whose information is collected. We focus on the notion of differential privacy, which gives a ...
Making Peer Prediction Practical
(2016-07-13)
My dissertation is on crowdsourcing---using crowds of people to accomplish tasks that are impractical or far more expensive otherwise. I focus specifically on crowdsourcing of information, where workers do tasks such as ...
Software Contracts for Security
(2016-08-11)
Component-based software engineering facilitates the design of complex systems by subdividing the programming task into separate components that interact via clearly defined interfaces. A component-based system is correct ...
Building Interpretable Models: From Bayesian Networks to Neural Networks
(2016-09-13)
This dissertation explores the design of interpretable models based on Bayesian networks, sum-product networks and neural networks.
As briefly discussed in Chapter 1, it is becoming increasingly important for machine ...
Upper and Lower Bounds for Privacy and Adaptivity in Algorithmic Data Analysis
(2016-08-03)
The increasing collection and use of sensitive personal data raises important privacy concerns. Another concern arising from the use of data in empirical sciences is the danger of producing results that are not statistically ...