VictorJuiz/thesis huggingface dataset:
Two graph-based tests for high-dimensional inference [electronic resource]

With modern science there is a growing emphasis on multivariate, complex data types. Some of these data are high dimensional. Others, such as survey preference, network, and tree data, cannot be characterized easily with standard models on Euclidean spaces. This dissertation details the investigation in this new setting of two classic statistical problems: change-point detection and two-sample comparison of categorical data. Change-point models are widely used in various fields for detecting lack of homogeneity in a sequence of observations. In many applications, the dimension of the observations in the sequence can be very high, even much larger than the length of the sequence. Testing the homogeneity of such sequences is a challenging but important problem. Existing approaches are limited in many ways. We proposed a new non-parametric approach that can be applied to data in high dimension, and even to non-Euclidean object data, as long as an informative similarity measure on the sample space can be defined. The approach is graph-based two-sample tests adapted to the scan-statistic setting. Graph-based two-sample tests are tests base on graphs connecting observations by similarity [Friedman and Rafsky, 1979, Rosenbaum, 2005]. We show that this new approach is powerful in high dimensions compared to parametric approaches. We also derive accurate analytic $-value approximations for very general situations, which lead to easy off-the-shelf homogeneity testing for large multivariate data sets. This approach has been applied on two data sets: The determination of authorship of a classic novel, and the detection of change in a social network over time. Two-sample comparison of categorical data is a classic problem in statistics. In many modern applications, the number of categories can be quite large, even comparable to the sample size, causing existing methods to have low power. When the number of categories is large, there is often underlying structure on the sample space that can be exploited. We propose a general non-parametric approach that makes use of similarity information on the space of categories in two-sample tests. Our approach addresses a shortcoming of existing graph-based two-sample tests by no longer requiring uniqueness of the underlying graph, thus allowing ties in the distance matrix defining the graph. We found two types of statistics that are both powerful and fast to compute. We show that their permutation null distributions are asymptotically normal and that their $-value approximations under typical settings are quite accurate, facilitating the application of this approach.

Keywords: Statistics.
Advisor: Siegmund David
Zhang Nancy R. (Nancy Ruonan) primary advisor. Thesis advisor
Friedman J. H. (Jerome H.) primary advisor
`Two souls, two thoughts', two self-schemas [electronic resource] : positive social and academic consequences of double consciousness in African-Americans

African-Americans have long been theorized to experience double consciousness— a two-ness characterized by a sense of self as American and African-American. Six studies examined the hypothesis that this double consciousness, although forged and fueled by racism and inequality, can facilitate positive social and academic consequences for African-Americans. First, Studies 1-3 provided evidence that double consciousness can function as two self-schemas, two ways of thinking about the self that develop through elaborated engagement with two American cultures. Specifically, African-American participants were shown to shift their social behaviors (i.e., giving a speech, making cooperative decisions) in schema-relevant ways from more independent when primed with mainstream-American culture to more interdependent when primed with African-American culture. Study 3 showed that self-construal mediated this capacity to cultural frame-switch. Then, Studies 4 and 5 tested and supported the prediction that mainstream university settings that encourage frame-switching, through the inclusion of African-American ideas and practices, can enhance academic motivation and performance (i.e., persistence, verbal and creative problem solving) for African-Americans. Finally, using a national data set, Study 6A/B provides further evidence that educational settings which are inclusive of diverse cultural practices can promote achievement behaviors, as well as belongingness (positive interdependence), among African-American undergraduates. The discussion examines double consciousness as a basic psychological phenomenon that may arise with subordinate status (e.g., female or working class identities, situational positions of low power), and suggests the benefits of mainstream settings that promote frame-switching through the inclusion of non-dominant cultural ideas and practices.

Keywords: Psychology.
Advisor: Markus Hazel Rose primary advisor. Thesis advisor
Eberhardt Jennifer L. (Jennifer Lynn) advisor. Thesis advisor
Walton Gregory M. (Gregory Mariotti) advisor. Thesis advisor
Ultrasound induced neurostimulation [electronic resource]

Ultrasound-induced neurostimulation has recently gained increasing attention. Developments in the use of ultrasound to stimulate and modulate neural activity have raised the possibility of using ultrasound as a new investigative and therapeutic tool in brain research. Little is known about the mechanisms by which it affects neural activity or about the range of acoustic parameters and stimulation protocols that elicit responses. In this thesis, conditions are established for transcranial stimulation of the nervous system in vivo, using the mouse somatomotor response. It is reported that (1) continuous-wave stimuli are as effective as or more effective than pulsed stimuli in eliciting responses, and responses are elicited with stimulus onset rather than stimulus offset; (2) stimulation success increases as a function of both acoustic intensity and acoustic duration; (3) interactions of intensity and duration suggest that successful stimulation results from the integration of stimulus amplitude over a time interval of 50 to 150 ms; (4) the motor response elicited appears to be an all-or-nothing phenomenon, meaning stronger stimulus intensities and durations increase the probability of a motor response without affecting the duration or strength of the response; and (5) motor responses, measured by normalized EMG signals in the neck and tail regions, change signifcantly when sonicating rostral and caudal regions of the mouse motor cortex. Taken together our findings present good evidence for being able to target selective parts of the motor cortex with ultrasound neurostimulation in the mouse, steps that should provide encouragement for the development of new applications in larger animal models, including humans.

Keywords: Bioengineering.
Advisor: Pauly Kim Butts (Kim Rosemary Butts)
Newsome William T. advisor. Thesis advisor
Pelc Norbert J. advisor. Thesis advisor
Unbiased estimation with biased samplers [electronic resource]

This thesis discusses how to construct unbiased estimators from biased estimators. Many situations that call for Monte Carlo methods lack known algorithms for exactly generating the random object for which an expectation is to be computed. Frequently, however, one can generate arbitrarily close approximations to the random object. We introduce a simple randomization idea for creating unbiased estimators in such a setting based on a sequence of approximations. We then describe the implications for two important cases: solutions to stochastic differential equations (SDEs), and equilibrium random variables associated with ergodic Markov chains. The first chapter briefly provides the context and motivation for the theory developed in this thesis and present an overview of the results. The second chapter introduces a general approach to the construction of unbiased estimators from a sequence of biased estimators. We provide the conditions under which the new estimators achieve "square root" convergence, and prove central limit theorems with respect to computational budget. The performance of the resulting unbiased estimators depends on the choice of randomization distributions. We identify the optimal choice of the randomization distributions. Applying the general approach, we show that one can build finite-variance unbiased estimators with a square root convergence rate whenever one has available a scheme that produces strong error of an order greater than 1/2 for the path functional under consideration. The new estimators are the first of their kind to both be unbiased and achieve square root convergence for multi-dimensional SDEs. Numerical experiments with various path functionals of continuous-time processes that arise in finance illustrate the effectiveness of our estimators. Our algorithm is competitive with, and often beats, the state-of-the-art multi-level Monte Carlo method. The third chapter applies our general approach to the computation of equilibrium expectations of ergodic Markov chains. Our approach provides an alternative to the class of algorithms known as "perfect sampling" or "exact sampling." Instead of sampling from the exact equilibrium distribution, our approach constructs unbiased estimators for equilibrium expectation. By aiming for a slightly less ambitious goal than exact sampling, our method can address a broader class of processes with much less care and effort. In particular, we provide a recipe for the construction of unbiased estimators (with square root convergence in great generality) for general positive Harris recurrent chains. Moreover, we show how one can construct unbiased estimators for non-Harris chains such as contraction chains.

Advisor: Glynn Peter W. primary advisor. Thesis advisor
Giesecke Kay advisor. Thesis advisor
Papanicolaou George advisor. Thesis advisor
Uncertainty quantification and numerical methods for conservation laws [electronic resource]

Conservation laws with uncertain initial and boundary conditions are approximated using a generalized polynomial chaos expansion approach where the solution is represented as a generalized Fourier series of stochastic basis functions, e.g. orthogonal polynomials or wavelets. The stochastic Galerkin method is used to project the governing partial differential equation onto the stochastic basis functions to obtain an extended deterministic system. The stochastic Galerkin and collocation methods are used to solve an advection-diffusion equation with uncertain viscosity. We investigate well-posedness, monotonicity and stability for the stochastic Galerkin system. High-order summation-by-parts operators and weak imposition of boundary conditions are used to prove stability. We investigate the impact of the total spatial operator on the convergence to steady-state. Next we apply the stochastic Galerkin method to Burgers' equation with uncertain boundary conditions. An analysis of the truncated polynomial chaos system presents a qualitative description of the development of the solution over time. An analytical solution is derived and the true polynomial chaos coefficients are shown to be smooth, while the corresponding coefficients of the truncated stochastic Galerkin formulation are shown to be discontinuous. We discuss the problematic implications of the lack of known boundary data and possible ways of imposing stable and accurate boundary conditions. We present a new fully intrusive method for the Euler equations subject to uncertainty based on a Roe variable transformation. The Roe formulation saves computational cost compared to the formulation based on expansion of conservative variables. Moreover, it is more robust and can handle cases of supersonic flow, for which the conservative variable formulation fails to produce a bounded solution. A multiwavelet basis that can handle discontinuities in a robust way is used. Finally, we investigate a two-phase flow problem. Based on regularity analysis of the generalized polynomial chaos coefficients, we present a hybrid method where solution regions of varying smoothness are coupled weakly through interfaces. In this way, we couple smooth solutions solved with high-order finite difference methods with non-smooth solutions solved for with shock-capturing methods.

Advisor: Iaccarino Gianluca primary advisor. Thesis advisor
Nordström Jan
Gerritsen Margot (Margot G.) advisor. Thesis advisor
Jameson Antony
Under the Microscope: Why US Intelligence Underestimated the Soviet Biological Weapons Program

Through trend and detail analysis of declassified U.S. intelligence documents, this paper shows that ambiguity in dual-use biological research was the main underlying cause of the US Intelligence underestimation of the Soviet Bioweapons program. Although lack of prioritization of biowarfare issues and complacency due to mirror imaging also existed, such intelligence failures were a result of the uncertainty caused by the dual-use nature of biological research. General statements, lack of absolute certainty about the presence of a Soviet bioweapons program, and wavering attention given to intelligence collection on bioweapons in the Soviet Union were common trends amongst the documents. The nature of biological research and public health events do not lend themselves easily for differentiation between defensive, natural, and illicit. The inability to distinguish between legitimate research and biological research for offensive military purposes was a primary reason for the lack of certainty about the Soviet Union’s pursuits in biology. This unfortunately continues to be an issue as biological technology advances. But due to the clear ambiguity in purpose and potential of dual-use biological research, as well as to avoid infringement upon scientific research, intelligence communities must create stronger relationships with the scientific community, which in turn must develop strong community-responsibility and incentives to detract scientists from pursuing bioweapons under any capacity.

Keywords: CISAC
Center for International Security and Cooperation
Stanford University
declassified documents
intelligence
security
United States
Soviet Union
bioweapons
Thesis
Advisor: Holloway David
Understanding and tuning organic semiconductor packing during solution processing [electronic resource]

Circuits based on organic semiconductors (OSCs) are being currently explored for flexible, transparent and low-cost electronic applications. However, to realize such applications, the charge transport performance of OSCs in thin film transistors (TFTs) must be improved. Using a solution processing method called solution shearing, we were able to create metastable polymorphs of various OSCs and improve the electronic performance. This is the first time industrially friendly coating processes have been utilized to change the molecular packing of OSCs. Changing the molecular packing to form metastable polymorphs through solution processing allows researchers to complement traditional synthetic methods to generate high performance OSCs. The first part of my research work details the use of solution shearing to increase the mobility of small molecular OSCs. The model OSC 6,13-bis(triisopropylsilylethynyl) pentacene (TPn) is used as the model compound for our study, and various metastable polymorph are created through solution processing. The highest mobility obtained for the metastable TFTs (4.6 cm2 V-1 s-1 ) is three times higher than the previous highest mobility found in literature. The lattice strain method to modify OSC charge transport was shown to be general to certain classes of small molecule and polymeric OSCs as well. In order to study crystallization of OSCs during solution shearing, my research extended to constructing a miniaturized solution shearing machine to be used in-situ at synchrotron facilities. We obtained high speed (100 frames/s), in-situ images of metastable crystal growth using a microbeam (20 [micrometer]) grazing incidence X-ray diffraction (GIXD) method. Using knowledge from these experiments, we were able to obtain design rules for creating lattice strain and polymorphism using other solution processing techniques. Finally, our research has brought the use of lattice strain closer industrial use through the use of selective deposition of OSCs. Industrial applications of lattice strained OFETs requires that the OFETS are patterned. We have developed a surface functionalization procedure that utilizes hydrophobic/hydrophilic interactions to isolate lattice strained OSCs. We show that charge carrier mobilities over 2 cm2/Vs are possible in the patterned OFETs of TIPS-pentacene, and that strained OFETs can exist at patterning sizes of 100 microns and lower. We show that the pattern size can have an effect on the lattice strain possible in the OSCs, and investigate methods that enable sub 10 micron scale patterning using solution shearing. In summary, we have shown that high performance, metastable polymorphs of various organic semiconductors can be fabricated through solution processing methods, and the underlying reasons for polymorphism is explained through the use of in-situ X-ray diffraction techniques.

Keywords: Chemical Engineering.
Advisor: Bao Zhenan primary advisor. Thesis advisor
Fuller Gerald G.
Salleo Alberto
Understanding human actions in still images [electronic resource]

Many human actions, such as "playing violin'' and "taking a photo'', can be well described by still images, because of the specific spatial relationship between humans and objects, as well as the specific human and object poses involved in these actions. Recognizing human actions in still images will potentially provide useful information in image indexing and visual search, since a large proportion of available images contain people. Progress on action recognition is also beneficial to object and scene understanding, given the frequent human-object and human-scene interactions. Further, as video processing algorithms often rely on some form of initialization from individual video frames, understanding human actions in still images will help recognize human actions in videos. However, understanding human actions in still images is a challenging task, because of the large appearance and pose variation in both humans and objects even for the same action. In the first part of this thesis, we treat action understanding as an image classification task, where the goal is to correctly assign a class label such as "playing violin'' or "reading book'' to each human. Compared with traditional vision tasks such as object recognition, we show that it is critical to utilize detailed and structured visual information for action classification. To this end, we extract dense and structured visual descriptors for image representation, and propose to combine randomization and discrimination for image classification. The performance of our classification system can be further improved by integrating with other high-level features such as action attributes and objects. The second part of this thesis aims at having a deeper understanding of human actions. Considering the specific types of human-object interactions for each action, we first propose a conditional random field model which allows objects and human poses to serve as context of each other, and hence mutually improve each other's recognition results. Then, we move on to discover object functionality in a weakly supervised setting. For example, given a set of images containing human-violin interactions, where a human is either playing violin or holding a violin but not playing, our method builds a model of "playing violin'' that corresponds to the functionality of the object, and clusters the input images accordingly. Finally, we summarize our work and show our vision and preliminary results of how our work can benefit some new vision tasks, including fine-grained object recognition, video event categorization, and social role understanding.

Advisor: Li Fei Fei
Koller Daphne advisor. Thesis advisor
Liang Percy advisor. Thesis advisor
Savarese Silvio advisor. Thesis advisor
Understanding modulatory computations in neural pathways of the retina [electronic resource]

The retina performs multiple simultaneous processing operations on the visual scene using a network of only five basic cell types, but more than fifty subtypes. Like many higher order sensory neurons, retinal ganglion cells integrate input through multiple parallel pathways that are influenced by diverse populations of inhibitory interneurons, nearly all of which have unknown function. Understanding the specific contributions of interneuron pathways is difficult because it requires a quantitative model that includes both the interneuron's input, its output, and its effects on other sensory inputs. Here we present an experimental and computational approach to discover all of these relationships together. We studied the visual computations performed by amacrine cells, a class of inhibitory interneuron. Like inhibitory interneurons in other neural circuits, amacrine cells are highly diverse in their physiology and occupy distinct anatomical layers. To measure how the signals transmitted through individual sustained amacrine cells contribute to retinal output, we presented white noise visual stimuli to the intact, isolated salamander retina. We recorded intracellularly from and injected current into single amacrine cells while recording spiking activity from the ganglion cell population of the salamander retina using a multielectrode array. In this way, many simultaneous paired recordings were performed. To characterize the contribution of the amacrine cell, we first characterized the amacrine cell preferred stimulus feature. Then using the method of Spike-Triggered Covariance (STC), we measured the response of ganglion cells to the subspace of stimuli that was different from the amacrine preferred feature. Using this method, we were able to characterize both modulatory and additive effects of the amacrine pathway on other features encoded by the ganglion cell. We found great diversity in functional effects of amacrine cells, consisting of the linear effect in which amacrine pathway contributes in building the receptive field of the ganglion cell, and nonlinear effects in which amacrine pathway modulates the ganglion cell's response function for other visual features. Our analysis indicates that the amacrine cell population defines a context that modulates the multiple features conveyed by the ganglion cell. Because modulation occurs throughout the nervous system, our approach provides a general strategy to understand the functional contributions of specific neurons to computations in a complex circuit.

Keywords: Electrical Engineering.
Advisor: Baccus Stephen A. primary advisor. Thesis advisor
Boahen Kwabena (Kwabena Adu) advisor. Thesis advisor
Ganguli Surya
Shenoy Krishna V. (Krishna Vaughn) advisor. Thesis advisor