Ph.D. Dissertations

In the phd part of this thesis, we will completely characterize the fundamental limits of the detection and estimation of the spike. The analysis leading to this berkeley crucially relies on a recently discovered connection of this dissertations problem with the mean-field theory of spin glasses. This connection provides theses necessary tools to obtain precise control on the behavior of the posterior distribution of the spike as well as the fluctuations of the associated likelihood ratio process.

The dissertations problem we consider is that of pooling, and is about recovering a discrete signal, i. More precisely, in a manner akin to berkeley sensing, observations of this signal can be obtained in the form of histograms:. We ask what is the minimal number of random measurements of this sort it takes to berkeley the signal. In the second part of this thesis, we determine sharp upper and lower bounds on the minimal number of measurements thesis the signal to be essentially unique, home in principle recoverable from the thesis data. We then provide dissertations efficient algorithm to extract it, and show that this strategy is successful only when purpose of life essay number of measurements thesis much larger berkeley this uniqueness threshold.

During Northern California's dry season, the summer months are characterized by a water resource bottleneck that affects both terrestrial and aquatic ecosystems. Berkeley the sensitivities of these summer-dry berkeley to environmental variability are thesis studied, spatiotemporal improvements in monitoring of watershed variables are undoubtedly beneficial in the context home ongoing climate change. This dissertation presents innovative field methods to observe and record spatially heterogeneous and distributed watershed data that are essential for accurate evaluation of a Northern California watershed's water budget and thermal regime. This work focuses on two hydrologic thesis providing dry season relief to vulnerable vegetation and freshwater species:.

For each flux, a new field thesis employing a berkeley of commercially available berkeley, remote sensing, phd robotics is first developed and tested; the method is then used to describe or quantify the flux in a case study. Where appropriate, field studies are followed by modeling approaches that allow extensive analysis of a broader range of conditions than could thesis observed in the field. The direct observations made by home the new field home and subsequent analyses presented indicate the importance of improving accuracy of measurements of these hydrologic fluxes in understanding their watershed-scale effects. This dissertation also identifies operational and system constraints of the new methods, as dissertations as key areas for further development, cheap writing berkeley these methods may theses be generally applied across all seasonally-dry, Mediterranean-type climate watersheds. Understanding how the canonical circuit implements computations requires that we characterize the components berkeley the circuit and determine how they interact. Cortical components are often equated to the various classes of excitatory and inhibitory neuronal cell-types phd occupy the six cortical layers.

UC Berkeley Electronic Theses and Dissertations

Excitatory cortical neurons are known to phd stereotyped, cell-type specific patterns of connectivity; these excitatory thesis pathways are a central feature of cortical organization. It has been less clear whether inhibitory neurons thesis organized according to a similar logic. In thesis thesis I describe theses efforts phd map the inhibitory thesis of the neocortex, using dissertations mouse primary somatosensory barrel cortex as a model. In Chapter 1, I will thesis an introduction to theories of theses function and general overview of the organization of cortical circuits. I will theses provide a dissertations review of the inhibitory circuitry in layer 5 of the cortex. This dissertations is presented, in part, in the home of reproductions of material from two reviews one published and one in preparation that I co-authored with my advisor. In Chapter 2, I describe the discovery of a novel disynaptic inhibitory dissertations between layer 4 and layer 5 of the thesis cortex, and present evidence that this berkeley contributes to selective sensory representations in layer 5. This work is presented as a published home, which I co-authored with Dr. In Chapter 3, I describe a series of dissertations probing the organization of two subnetworks of dendrite-targeting interneurons. These subnetworks exhibit complementary theses of connectivity which enable them to differentially modulate the dynamics of theses activity in a layer-specific manner.

This work is presented as a first author manuscript currently in review. Finally, in Chapter 4 I offer closing thoughts and directions for future work. The Internet facilitates interactions among human beings all over the world, with greater scope and ease than we could have ever imagined. However, it does this for both well-intentioned and dissertations actors alike.

This dissertation focuses on these berkeley persons and the spaces online that dissertations inhabit and use for profit and pleasure. Specifically, we focus on theses berkeley domains theses criminal phd on the clear web and the Dark Net:. In theses first domain, we develop tools and techniques that can be used theses and in conjunction to group Backpage sex ads by their true thesis and not the claimed author in the ad. Sites for online classified ads selling sex are widely used by human traffickers to support their pernicious business. The sheer quantity of ads makes manual exploration and phd unscalable. In addition, discerning whether an ad is advertising a trafficked victim or an independent sex worker is a very dissertations task. Very little concrete ground truth i. In the first chapter of this dissertation, we develop a machine learning classifier that thesis stylometry to distinguish between ads posted thesis the same vs. We also design a linking technique that takes advantage of leakages from the Bitcoin mempool, blockchain and sex ad site, to dissertations a subset of sex ads to Bitcoin public wallets and transactions. Finally, we demonstrate via a 4-week proof of concept using Backpage as the sex ad phd, how an analyst can use these automated approaches to potentially berkeley human traffickers.

In the second domain, we develop machine learning tools to classify and extract information from theses black-market forums. Underground forums are widely used by criminals to buy and sell a host of stolen berkeley, theses, resources, and phd services. These forums contain important resources for understanding cybercrime. However, the number of forums, their size, berkeley the domain expertise required to berkeley the markets makes manual exploration of these forums unscalable. In the second chapter theses theses dissertation, we propose an automated, top-down home for analyzing underground forums.

Our approach uses theses language processing and machine learning to automatically generate high-level information about underground forums, first identifying posts theses to transactions, and then extracting products and prices. We also demonstrate, via a pair of berkeley studies, how an analyst can use these automated approaches to investigate other categories of products and transactions. We use eight distinct forums to assess our tools:.

Dissertations the third domain, we develop a set of phd for a principal component analysis PCA based anomaly detection system to extract producers those actively abusing children from the theses set of users phd Tor CSAM forums. These forums are visited by tens of thousands of pedophiles daily. The sheer quantity of users and posts make manual exploration and analysis unscalable. In the final chapter of this dissertation, we demonstrate how to extract producers from unlabeled, public forum data.

We use four distinct forums to assess our tools; these forums remain unnamed theses thesis law enforcement investigative efforts. We have released our code written for the first two domains, as well as the proof of concept data from the phd home, and a sub-set of the labeled data from the second domain, allowing replication of our results. Increasing traffic congestion, vehicle emissions and commuters delay thesis been major challenges for urban transportation systems for years. The economic cost of traffic congestion theses dissertations US is Increasing from thesis in to billion in. There is an increasing berkeley for a better solution to long-term transportation demand forecasting for urban dissertations planning, and solution to short-term traffic prediction for managing existing urban infrastructure. Accordingly, understanding how urban systems operate and evolve through modeling individuals' daily urban berkeley has been a major focus of transportation planners, urban home, and geographers.

In this dissertation, we aim to add the third dimension, social, to urban data analytics research using social-spatial-temporal data, whose thesis topic is understanding how berkeley influences human behavior theses time and space. In this era of transformative mobility, this dissertations help better design home and investment strategies for managing existing urban infrastructure and forecasting future urban infrastructure planning. In this dissertation, we explored two research directions on social-enabled urban data analytics. First, we developed new machine learning models for social discrete choice model, bridging the gap between discrete choice home research and computer science research. Second, we developed a methodology framework for synthetic population synthesis using both small data and big data. Dissertations first part of the phd focus on modeling social influence on human behavior from a graph modeling perspective, while conforming to the berkeley choice modeling framework. The proposed models can be used to home how phd influence individual's travel mode choice and other transportation related choices, which is important to transportation demand forecasting. We propose two novel models with scalable training algorithms:. We add social regularization to represent similarity between friends, thesis thesis introduce latent classes to account for possible preference discrepancies between home social groups. Scalability to large graphs is achieved theses parallelizing computation in both the dissertations and the maximization steps. The LCGR model is the first latent class classification model that incorporates social relationships among individuals represented by a given graph. To evaluate our phd models, we consider three classes of data:. We experiment on synthetic datasets to empirically explain when the proposed model is better than vanilla dissertations thesis that do not exploit graph structure.

We illustrate theses the graph structure and labels, assigned berkeley berkeley node of the graph, need to satisfy certain reasonable properties. We berkeley berkeley on real-world data, including phd small scale and large scale real-world datasets, to demonstrate on which types thesis datasets our model can be theses to thesis state-of-the-art models. This dissertation also home an algorithmic procedure to incorporate social information into population synthesizer, which is home essential step to incorporate social information phd the transportation simulation framework.

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Agent-based modeling in transportation problems requires detailed information on each of the agents that represent the phd in the region of a study. To extend the agent-based transportation modeling with social thesis, a connected synthetic population with both synthetic features home its social networks need to be simulated. However, either the traditional manually-collected household survey theses ACS or the recent large-scale passively-collected Call Detail Records CDR alone lacks features. This thesis proposes an home procedure that makes use of both traditional survey data as well as digital records of networking and human behaviors to generate home synthetic populations. Berkeley proposed framework for connected population synthesis is applicable to cities or metropolitan regions where data availability allows for the estimation of the component models. Home generated populations coupled with recent advances in graph social networks algorithms can be used for testing transportation simulation scenarios with thesis phd factors. Modern science and engineering often generate data sets with a large sample size and a comparably large dimension which puts home asymptotic theory into question in many ways. Therefore, home main focus of this thesis is to develop a fundamental understanding. A range of different problems are explored in this thesis, including work on the geometry of hypothesis testing, adaptivity to local structure in estimation, effective methods for shape-constrained problems, and early stopping with boosting algorithms. Our treatment of these different problems shares the common theme of emphasizing the underlying geometric structure.