Browsing by FAS Department "Engineering and Applied Sciences - Computer Science"
Now showing items 1-20 of 51
-
A Theory of Depth From Differential Defocus
(2019-01-25)This document describes a class of computationally-efficient visual depth sensors. Inspired by the visual system of the jumping spider, these sensors are thin lens cameras that observe small changes in optical defocus. ... -
Accurately Predicting the Reflectance of Rough Metal Surfaces From One-Dimensional Surface Profile Measurements
(2018-09-25)This thesis investigates the problem of using surface microgeometry measurements to predict the reflectance of rough metal surfaces. Because light cannot penetrate much into metals, the observable reflectance of a metal ... -
Acquiring and Aggregating Information from Strategic Sources
(2016-07-28)This thesis considers, from a theoretical perspective, the design of mechanisms to accomplish the objective described in the title. Two cases of this problem are considered: information as represented by data points in a ... -
Advances in Monte Carlo Variational Inference and Applied Probabilistic Modeling
(2018-05-10)Galvanized by the accelerated pace and ease of data collection, researchers in more and more disciplines are turning to large, heterogeneous datasets to answer scientific questions. Divining insight from massive and complex ... -
Advancing System-Level Analysis and Design of Specialized Architectures
(2018-08-31)Over the course of the past decade, computation has increasingly spread to the cloud and mobile devices. With the growing computation demands placed by contemporary cloud and mobile workloads, architects have increasingly ... -
An Exploration of Two-Party Reconciliation Problems
(2018-08-31)This thesis explores various two-party reconciliation problems from a theoretical perspective. We define a reconciliation problem to be one in which Alice and Bob each have some data, and their data is in some problem ... -
Analyzing Brain Connectivity and Computing Machine Perception
(2019-04-25)Artificial intelligence is loosely inspired by neuroscientific discoveries. However, existing computational intelligence methods are fragile and do not generalize well. In contrast, the brain allows humans to reliably ... -
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 ... -
Composable Enhancements for Gradual Assurances
(2017-07-12)This dissertation presents three enhancements to software components that increase the trustworthiness and usability of the systems they comprise. The enhancements are composable: they are local to the components they ... -
Computational Notions of Entropy: Classical, Quantum, and Applications
(2019-05-21)Entropy notions from information theory have many applications in cryptographic analyses and constructions, where it is most common to consider adversaries with only (polynomially) bounded computational power. Therefore, ... -
Dealing with Interference on Experimentation Platforms
(2018-09-16)The theory of causal inference, as formalized by the potential outcomes framework, relies on an assumption that the experimental units are independent. When independence is not tenable, we say there is interference, and ... -
Decision Making With Heterogeneous Agents: Elicitation, Aggregation, and Causal Effects
(2019-05-18)The methods of artificial intelligence and statistical machine learning are finding tremendous success in various fields, with applications ranging from cancer screening to machine translation. However, continued improvement ... -
Deep Learning for Music Composition: Generation, Recommendation and Control
(2019-05-21)Technology has always helped expand the range of musical expression, from the fortepiano to synthesizers to electronic sequencers. Could machine learning further extend human creativity? We explore three ways deep learning ... -
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 ... -
Detecting Meaningful Relationships in Large Data Sets
(2018-05-01)As data sets grow and algorithms scale, two questions have become central to data-rich science. The first is the exploration question: how can we avoid only testing hypotheses consistent with current models and instead ... -
Efficiency in warehouse-scale computers: a datacenter tax study
(2017-01-25)Computation has been steadily migrating from isolated on-premise deployments to the datacenters of a small number of large-scale cloud providers. The datacenters powering the cloud, also known as warehouse-scale computers ... -
Efficient Implementations of Sparse and Quantized Deep Neural Networks Using Systolic Arrays
(2019-05-16)Deep Neural Networks (DNNs) have achieved state-of-the-art performance across a variety of domains, including many natural language processing and computer vision tasks. Though DNNs span such a wide assortment of applications, ... -
Experimental Studies of Human Behavior in Social Computing Systems
(2015-05-18)Social computing systems, fueled by the ability of the Internet to engage millions of individuals, have redefined computation to include not only the application of algorithms but also the participation of people. Yet, the ... -
Extensible Proof Engineering in Intensional Type Theory
(2015-02-24)We increasingly rely on large, complex systems in our daily lives---from the computers that park our cars to the medical devices that regulate insulin levels to the servers that store our personal information in the cloud. ... -
A Foundational Proof Framework for Cryptography
(2015-05-18)I present a state-of-the-art mechanized framework for developing and checking proofs of security for cryptographic schemes in the computational model. This system, called the Foundational Cryptography Framework (FCF) is ...