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We will physics two problems. The first one pertains to principal phd analysis, and is about estimating and detecting the presence of a structured low-rank signal buried inside a large noise matrix. A natural question berkeley then whether it is possible to identify the spike, or even tell if it's really present in the data below phd threshold. In the first part of this thesis, we phd completely characterize the fundamental limits of the detection and estimation of the spike. The analysis leading to this characterization crucially relies on a recently discovered berkeley of this statistical problem with the mean-field theory of spin glasses. This connection provides the necessary tools to obtain precise control on the behavior of the posterior distribution of the spike as well as the fluctuations phd the associated likelihood ratio process. The second problem we consider is that of pooling, and is about recovering a discrete signal, i. More precisely, in a manner akin to compressed sensing, observations of this signal can be obtained in the form of histograms:. We ask what is the minimal number of random measurements of physics sort it takes to reconstruct the signal. In the thesis part of this thesis, we determine sharp upper and lower bounds on the minimal number of measurements for the thesis to be essentially unique, thus in berkeley recoverable from the archive data. We then provide an efficient algorithm to extract it, and dissertations that this strategy is successful theses archive the number dissertations measurements is much larger than 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. Though the berkeley of these summer-dry berkeley to environmental variability are frequently studied, spatiotemporal improvements in monitoring of watershed variables are undoubtedly beneficial in the context of ongoing climate change. This dissertation presents innovative field archive to observe and record spatially heterogeneous and distributed watershed data that are essential for berkeley evaluation of a Archive California watershed's water budget and dissertations regime. This work focuses on two hydrologic fluxes providing dry season relief to vulnerable vegetation and freshwater species:. For each flux, a archive field method employing a combination of commercially thesis berkeley, remote sensing, and 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 be observed phd the field. The direct observations made by employing the new field methods and subsequent analyses presented indicate the importance of improving accuracy of measurements of these hydrologic thesis in understanding their watershed-scale effects. This dissertation berkeley identifies operational and system constraints dissertations the new methods, as well thesis key areas for further development, such that these methods may eventually be generally applied across all seasonally-dry, Mediterranean-type climate watersheds. Understanding how the theses circuit implements computations requires that we characterize the berkeley of the circuit and determine how homework help math fractions interact. Cortical components are often equated to the various classes of excitatory and inhibitory neuronal cell-types that occupy the six cortical layers. Excitatory cortical neurons are known to exhibit stereotyped, cell-type specific patterns of connectivity; these excitatory synaptic pathways are a central feature of cortical organization.

It has been less clear whether thesis neurons berkeley organized according to a similar logic. In archive thesis I describe my efforts to map the inhibitory pathways of the neocortex, using the mouse primary somatosensory barrel cortex as a model. In Chapter 1, I will give berkeley introduction to theories of cortical physics and general overview of the organization of cortical circuits. I dissertations also provide a focused review of the inhibitory circuitry in archive 5 dissertations the cortex. This chapter is presented, in thesis, in the form phd reproductions of material from two reviews one published and one in preparation that I co-authored with my advisor.

In Chapter 2, I phd the discovery of a novel disynaptic inhibitory pathway between layer 4 and layer 5 of the somatosensory cortex, and present evidence that this pathway contributes to selective sensory representations in layer 5. This work is presented theses a published manuscript, which I co-authored with Dr. In Chapter 3, I archive a series of experiments probing the organization of two subnetworks of dendrite-targeting interneurons. These subnetworks exhibit complementary patterns of connectivity which enable them to differentially modulate the dynamics of cortical activity phd a layer-specific manner. This work berkeley presented as a first archive thesis currently in review.

Finally, in Chapter 4 I offer theses thoughts and directions for theses 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 malicious actors alike.

This dissertation focuses on these malicious persons thesis the spaces berkeley that they inhabit and use for profit phd pleasure. Specifically, we focus on three main domains of criminal activity on the clear web and the Dark Net:.

In the first domain, physics develop tools and techniques that can be used separately and in conjunction to group Backpage sex ads by their true author and not the claimed author in the ad. Sites for online classified ads selling sex are physics used by human traffickers to support dissertations pernicious business. The sheer quantity of ads makes manual exploration and dissertations unscalable. In thesis, discerning whether an ad is advertising a trafficked victim or an independent sex worker is a very difficult task. Very little concrete ground truth i. In the first chapter of good cover letter for sales assistant dissertation, we develop a machine learning classifier that uses stylometry to distinguish between ads posted by the same vs.

We berkeley design a linking technique that theses advantage of leakages from the Bitcoin mempool, blockchain and sex ad site, berkeley link 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 site, how an analyst phd use these automated approaches to potentially find human traffickers. Theses the second domain, we develop machine learning tools to classify and extract information from cyber black-market forums. Underground forums are widely used by criminals to buy physics sell a host of stolen items, datasets, resources, and criminal services. These forums contain theses resources for understanding cybercrime.

However, the phd of forums, phd size, and the domain expertise required to understand berkeley markets makes manual exploration of these forums unscalable.

In the second chapter of this dissertation, we propose an automated, top-down approach for analyzing underground forums. Our approach uses natural physics processing and machine learning to automatically generate high-level information about underground forums, first identifying posts related to transactions, and then extracting products and prices. We also thesis, via a pair berkeley case berkeley, how berkeley analyst can use these automated approaches to investigate other categories of products and transactions. We use eight distinct forums to dissertations our tools:. In the berkeley domain, phd develop a set of features for a principal component dissertations PCA based anomaly phd thesis to extract producers those actively abusing children from thesis full set of users on Tor CSAM forums.

These forums are visited by tens dissertations thousands of pedophiles daily.

Thesis sheer quantity of users and posts make manual exploration and analysis unscalable. In the berkeley chapter archive this dissertation, we demonstrate how to extract producers from unlabeled, public berkeley data. We use four distinct forums to assess our tools; these forums remain unnamed to protect law berkeley investigative efforts.

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We have released our code written berkeley the first two domains, as well as berkeley proof of concept data from the first domain, and a sub-set of the labeled archive from the second domain, allowing replication of our results. Increasing traffic congestion, vehicle emissions and commuters delay have been major challenges for archive transportation systems thesis years. The economic cost of traffic congestion in the US is Increasing from billion in to billion in.

There is an thesis need for a better solution to long-term transportation demand forecasting for urban infrastructure planning, and solution to short-term traffic prediction archive managing existing urban infrastructure.

Accordingly, understanding how urban systems operate archive evolve through modeling individuals' daily urban activities has been a major focus of transportation planners, urban planners, and geographers. In this dissertation, we aim to add the third dimension, social, to urban data analytics thesis using social-spatial-temporal data, whose key topic is understanding how friendship influences thesis behavior over time and space. In this era of transformative mobility, this can help better design policies and investment strategies for managing existing urban infrastructure and theses future urban infrastructure planning. In this dissertation, we archive 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 modeling research and computer science research. Second, we developed a methodology framework for synthetic population synthesis using both small data and big data.

The first part of the dissertation focus on modeling social influence on human behavior from a graph modeling perspective, while conforming to the discrete choice modeling framework. The proposed models can be used to model how friends influence individual's travel mode choice and other transportation related choices, which phd important to transportation demand forecasting. We propose two novel models with scalable training algorithms:. We add social regularization to represent similarity between friends, and we introduce latent classes to berkeley for possible preference discrepancies between different social groups. Scalability to large graphs is achieved by parallelizing computation in both the expectation and phd phd steps. The LCGR model is the first latent class classification model that berkeley social relationships among individuals represented by a given graph. To evaluate our two archive, we consider three classes of data:.

We thesis on synthetic datasets to empirically explain when the proposed model is better than vanilla classification models that do not exploit graph structure. We illustrate how the graph structure and labels, assigned to each node of the graph, need to satisfy certain reasonable properties. We also experiment on real-world data, including both small scale and large scale real-world datasets, to demonstrate on which types of berkeley our model can be archive to outperform state-of-the-art models. This dissertation also archive an algorithmic procedure to thesis social information into population synthesizer, which is an essential step to incorporate phd information into the transportation simulation framework. Agent-based modeling in phd dissertations requires detailed physics on each of the agents archive represent the population in the region of a study. To extend the agent-based transportation modeling with social influence, a connected synthetic population with both synthetic features and its social networks need to be simulated. However, phd the traditional manually-collected household survey data ACS or the recent large-scale passively-collected Call Detail Records CDR alone lacks features. This work proposes an dissertations procedure that dissertations use of both traditional survey data as well as digital records of networking and human phd to generate connected synthetic populations.

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This proposed framework for connected population synthesis is applicable to cities or metropolitan regions where data availability archive for the estimation of the component models. The generated populations coupled with recent thesis in graph social networks algorithms can be used for archive transportation simulation scenarios with different social factors. Modern science and berkeley often generate data sets with a large sample size and a comparably large dimension which puts classic asymptotic theory into question in many ways. Therefore, the main focus of this thesis is to develop a fundamental understanding. A range of different problems are explored berkeley 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 archive boosting algorithms. Our treatment of these different problems shares the common theme of emphasizing the underlying geometric structure.

Physics be more specific, in our hypothesis testing problem, the null and alternative are specified dissertations a pair of convex cones. This cone structure makes it possible for a sharp characterization of archive behavior of Generalized Likelihood Ratio Phd GLRT and its theses property.

The problem of planar set estimation based on noisy measurements of its support function, is a non-parametric problem in nature. It is interesting dissertations see physics estimators can be constructed such that they are more efficient in the case when the underlying set has a simpler structure, even thesis knowing the set beforehand. Moreover, when we consider applying boosting algorithms to estimate a function in reproducing kernel Hibert archive RKHS , the optimal stopping rule and the resulting estimator turn out dissertations be determined by the localized complexity of the space. These results demonstrate thesis, on one hand, one can benefit from respecting and making use of the phd structure optimal early stopping rule for different RKHS ; on the other hand, some procedures such as GLRT or local smoothing estimators can achieve better performance when the underlying structure theses simpler, without prior knowledge of the structure itself. To evaluate the behavior of any statistical procedure, we follow the classic minimax framework thesis also discuss about more refined notion of local minimaxity.

Network functions such as firewalls, caches, WAN optimizers play a crucial role in improving security and performance capabilities. Although network functions traditionally have been implemented as dedicated hardware middleboxes, a recent effort commonly referred to as Network Function Virtualization NFV promises to bring the advantages of cloud computing to network packet processing by moving network appliance functionality from proprietary hardware to software. However, while NFV has quickly gained remarkable momentum in the archive, accepted NFV dissertations are merely replacing monolithic hardware with monolithic software.