VictorJuiz/thesis huggingface dataset:
Convex optimization for neural networks

Due to the non-convex nature of training Deep Neural Network (DNN) models, their effectiveness relies on the use of non-convex optimization heuristics. Traditional methods for training DNNs often require costly empirical methods to produce successful models and do not have a clear theoretical foundation. In this thesis, we examine the use of convex optimization theory to improve the training of neural networks and provide a better interpretation of their optimal weights. In this thesis, we focus on two-layer neural networks with piecewise linear activations and show that they can be formulated as finite-dimensional convex programs with a regularization term that promotes sparsity, which is a variant of group Lasso. We first utilize semi-infinite programming theory to prove strong duality for finite-width neural networks and then describe these architectures equivalently as high dimensional convex models. Remarkably, the worst-case complexity to solve the convex program is polynomial in the number of samples and number of neurons when the rank of the data matrix is bounded, which is the case in convolutional networks. To extend our method to training data of arbitrary rank, we develop a novel polynomial-time approximation scheme based on zonotope subsampling that comes with a guaranteed approximation ratio. Our convex models can be trained using standard convex solvers without resorting to heuristics or extensive hyper-parameter tuning unlike non-convex methods. Due to the convexity, optimizer hyperparameters such as initialization, batch sizes, and step size schedules have no effect on the final model. Through extensive numerical experiments, we show that convex models can outperform traditional non-convex methods and are not sensitive to optimizer hyperparameters. In the remaining parts of the thesis, we first extend the analysis to certain standard two and three-layer Convolutional Neural Networks (CNNs) can be globally optimized in fully polynomial time. Unlike the fully connected networks studied in the first part, we prove that these equivalent characterizations of CNNs have fully polynomial complexity in all input dimensions without resorting to any approximation techniques and therefore enjoy significant computational complexity improvements. We then discuss extensions of our convex analysis to various neural network architectures including vector output networks, batch normalization, Generative Adversarial Networks (GANs), deeper architectures, and threshold networks

Keywords: Engineering.
Electrical Engineering.
Advisor: Pilanci Mert
Boyd Stephen P.
Weissman Tsachy
Coordination of distributed energy resources for distribution grid reliability

Climate change concerns and economics are driving higher electrification and the adoption of distributed energy resources, such as rooftop solar photovoltaic, small scale battery storage, and new electricity consuming devices such as EV chargers, electric heat pumps, and water heaters, as part of an effort to reduce dependency on fossil fuels. Additionally, advances in information technology have enabled the grid to be increasingly observable and controllable with the widespread installation of new sensors and smart devices. While these changes have profound effects on all aspects of the power grid, we focus on the impacts of electrification and distributed renewable generation on the consumer side, leading to the rapid adoption of DERs. In particular, we look at how the increase in electrification including EV chargers, will cause significant increase in load which can lead to transformer overloading and how excess energy generated by rooftop solar and other DERs can be fed back into the grid, which can cause voltage and transformer problems. It has been projected that combating these challenges of increasing electrification and DERs would require costly infrastructure upgrades and / or the development of novel DER coordination schemes that jointly control DERs across a distribution grid, and electricity tariff structures and incentives. The controllability and flexibility of DERs, create an opportunity to coordinate their operation to reduce energy and grid upgrade costs while protecting local grid infrastructure assets such as transformers and maintaining grid reliability. However, effective integration and coordination is difficult because it requires the culmination of many consumer preferences, cyber-physical constraints, scalability, and various communication protocols and control access constraints. We use a power flow driven simulation and optimization methodology to quantify the adverse impacts of projected increases in DER penetration and electrification on distribution grids under different DER control schemes and electricity tariff structures. We describe a methodology for simulation of the grid and its devices including a quantification of the performance limits on DER coordination with two bookend controllers. A local only controller that represents the lower end of grid reliability performance for DER coordination and a perfect foresight oracle controller that represents the upper end of grid reliability performance. Then, we discuss the challenges of an implementable scheme and present a DER coordination scheme via day-ahead demand and supply power bounds that satisfies all the criteria for an implementable scheme.

Keywords: Engineering.
Electrical Engineering.
Advisor: El Gamal Abbas
Rajagopal Ram
Rivas-Davila Juan
Coronavirus emergence and plasmodium parasite prelude : unraveling first infections

This dissertation embarks on a comprehensive journey to explore and contrast the T cell responses to two distinct infectious diseases: COVID-19 and malaria. By delving into the immunological intricacies of these diseases, this research aims to shed light on the critical roles T cells play in the immune response to both a novel pandemic and an ancient endemic disease. The second chapter presents insights into the dynamics of CD4+ T cell responses following SARS-CoV-2 infection, highlighting a shift in cytokine production patterns and underscoring the potential role of TNF$\alpha$-producing CD4+ T cells in sustaining post-infection immunity. The third chapter focuses on malaria's impact on immune responses during pregnancy, particularly among primigravid women, revealing the modulation of immune responses by Type 1 regulatory (Tr1) cells. The fourth chapter explores genetic factors influencing malaria susceptibility through a study on Diversity Outbred mice, identifying specific loci associated with varying disease outcomes. This thesis integrates these findings to enhance our understanding of T cell correlates and genetic factors that shape immune responses during initial infections. By contrasting the historical context of malaria with the contemporary challenge of COVID-19, the research provides a unique perspective on the evolution of immune responses and their implications. This comprehensive study not only advances our knowledge of immunology but also proposes therapeutic insights, aiming to inform future targeted interventions in the fight against infectious diseases.

Keywords: Medicine.
Microbiology and Immunology.
Advisor: Jagannathan Prasanna
Schneider David (David Samuel)
Wang Taia
Correlation clustering at scale

Correlation clustering is a useful method in machine learning and data analysis that aims to partition data into groups based on the notion of pairwise similarity. Given a collection of objects and a labeling of every pair of objects as either "similar" or "dissimilar", the goal is to find a partitioning of the objects such that similar pairs tend to be clustered together while dissimilar pairs tend not to. Correlation clustering has become desirable in many applications ranging from locating boundaries in digital images to detecting communities in social networks. In many of these applications, the order of magnitude of the input significantly exceeds the resources available to the algorithm such as time and space, which has led to increasing demand for designing efficient algorithms at large scale. In this thesis, we study the problem of correlation clustering in models of efficient computation with large-scale data and propose new algorithms with much improved guarantees. We first present a (3+epsilon)-approximate parallel algorithm for minimizing disagreements with labels that runs in O(1/epsilon) rounds. The approximation ratio almost matches a natural target of 3 for combinatorial algorithms. Then, we give a single-pass 5-approximate streaming algorithm and show that the approximation analysis is tight. Both algorithms are simple to implement and have implications in various models including massively parallel computation, streaming, distributed local model, local computation algorithms, and fully dynamic algorithms

Keywords: Engineering.
Advisor: Charikar Moses
Ahmadipouranari Nima
Tan Li-Yang
Cosmic shear, or atmosphere? Modeling the atmosphere for dark energy measurements with the Vera C. Rubin Observatory

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will image tens of billions of galaxies over ten years--a 100 times increase over previous surveys--enabling the most precise measurements of dark energy properties to date. Realizing the full potential of this powerful dataset requires an unprecedented understanding of observational effects that, if uncorrected, can bias the science results. One such source is the blurring of images due to optical turbulence in the atmosphere, which dominates the point-spread function (PSF) for ground-based instruments. This atmospheric effect imprints spatially correlated noise on scales (and with amplitudes) similar to the cosmological signal we will study: the spatial correlation of positions and shapes of galaxies on the plane of the sky due to gravitational lensing of light by the dark matter in the Universe. High-fidelity simulated astronomical images are an important tool in developing and measuring the performance of image-processing algorithms that will be needed to accurately and precisely account for sources of correlated noise such as the atmospheric PSF. This thesis presents a new simulation tool, psf-weather-station, that allows us to study and model the dependence of correlations in the atmospheric PSF on weather conditions at any observatory by leveraging data from weather forecasting models. We use this tool to simulate the atmospheric PSF predicted for the Vera C. Rubin Observatory in Chile and make quantitative predictions of two-point correlation functions in the size and shape of the PSF that are used in analyses of cosmic shear. We also explore the temporal behaviour of the atmospheric PSF using high-resolution speckle images of stars, recorded near Rubin Observatory, and simulate similar observations using pfs-weather-station.

Keywords: Humanities and Sciences.
Applied Physics.
Advisor: Burchat Patricia
Moerner William
Roodman Aaron
Creating Custom Optical Potentials with Spatial Light Modulators

Modern atomic physics experiments use precisely engineered optical intensity profiles to trap and manipulate atoms. These profiles are created by optical systems based on spatial light modulators (SLMs) and acousto-optic deflectors. SLMs can, in theory, produce nearly arbitrary two-dimensional and select three-dimensional intensity profiles though technical challenges have largely limited SLMs to the formation of optical tweezer arrays. In this thesis, I present computational and experimental methods to greatly expand the set of achievable intensity profiles. For 2D profiles, finding an optimal phase distribution for the SLM is the primary challenge; I demonstrate a novel phase-smoothing approach to eliminate optical vortices and allow for better convergence. I also show results from a camera feedback procedure that corrects for aberrations not considered in the computational model. Finally, I present results from two methods of generating arrays of 3D bottle beams: spliced phase gradients and acousto-optics. These results highlight the viability of our methods for future use in neutral atom experiments.

Keywords: Physics
Physics
Spatial Light Modulators
SLM
Bottle Beams
Optical Vortices
Text
Thesis
Advisor: Schleier-Smith Monika
Hogan Jason
Crossing the empires : travel poetry in Southern Song China (1127-1210)

This first study in any language on the emissary poetry of the Southern Song explores the relationship between politics and travel poetry by Song officials from the standpoint of Song-Jin relations. It challenges the existing scholarship which claims that there was nationalism in the Southern Song. More specifically, through close reading, the present study shows that there was no shared consciousness among the Southern Song emissaries as it varied from mission to mission, person to person. Furthermore, this study reveals that irredentism or revanchism -- often viewed as a central feature of nationalism -- is but a particular version of the policy of huifu. Huifu meant different things to the emperorship and the officials at different points of Song-Jin relations. And the dream travels of Lu You in the last chapter highlight that irredentism was also changing and shifting at an individual level. To such an extent that this most famous irredentist of the Southern Song gave up his irredentism towards the end of his life. This study does show, however, the loyalty of the Song officials. But with a distinction between loyalty to whom and loyalty to what. While some showed allegiance to the emperorship, some showed allegiance to the Song dynasty. The entity that commanded their loyalty was not an imagined community but the Song empire, which was seriously challenged by the Jurchen Jin, its more powerful neighbor in the north. Finally, this study demonstrates that travel poetry informed by foreign relations and domestic politics -- like ancestor's instructions and Confucian thought -- is also an integral part of the Song political culture

Keywords: Humanities and Sciences.
East Asian Languages and Cultures.
Advisor: Egan Ronald
Kieschnick John
Vinograd Richard Ellis
Zhou Yiqun
Cryogenic single-molecule active control microscopy with fluorescent proteins

Superresolution microscopy is a powerful optical technique for studying molecules and structures within biological cells at size scales below the optical diffraction limit of ~200-300 nm. Performing superresolution imaging on samples maintained at cryogenic temperatures provides several advantages: reduced photobleaching resulting in improved localization precisions, the use of plunge-freezing as a chemical-free fixation technique, and the potential of correlative imaging with cryogenic electron tomography (cryoET). However, single-molecule superresolution methods such as PALM and STORM are difficult to implement in frozen samples due to the limited availability of fluorophores with access to efficient active control mechanisms at low temperatures. The work presented in this dissertation establishes a workflow for cryogenic fluorescence imaging compatible with subsequent cryoET and details our search for control over the emissive states of two fluorescent proteins, PAmKate and mApple, under cryogenic conditions

Keywords: Humanities and Sciences.
Chemistry.
Advisor: Moerner W. E. (William Esco)
Cui Bianxiao
Fayer Michael D.
Cultural Centers on College Campuses: Understanding Marginalized Students' Perceptions of Community Centers

Cultural centers are spaces at colleges and universities that provide resources, programming, community, and more for marginalized students. While some universities have a multicultural center aimed to serve students of many identities, many universities have centers that cater to a specific identity of students, including racial/ethnic backgrounds, gender, sexuality, and more. Cultural centers play a crucial role in fostering a sense of belonging and support for marginalized student populations in higher education, however, there is still little research that understands the diverse range of feelings and experiences that students have about these spaces. This thesis aims to bridge this knowledge gap by using a survey-based approach to explore the perceptions and emotions of marginalized students towards cultural centers.
A mixed-methods research design was utilized to collect and analyze data from marginalized students at Stanford University. The survey consisted of both quantitative Likert-scale questions and qualitative open-ended prompts, allowing for the analysis based on marginalized identities, cultural centers, frequency with the centers, and other specific methods. The survey focused on understanding frequency and reasoning behind students’ participation within cultural centers, how students view the cultural centers in terms of the main goals of the centers, and how these cultural centers affect students in terms of their perceptions of their identities, as well as their sense of belonging and sense of self.
Results from this survey indicated a wide range of experiences, with a substantial number of students holding positive opinions. Many students expressed a strong sense of belonging, community, and cultural pride, and prioritized interacting with cultural centers within their regular schedules. However, others felt there was a need for more programming surrounding intersectionality, more diverse representation within identities, more opportunities for first-time students to interact, and routine assessment of these spaces. Overall, this study showed more about how different communities on campus view and value cultural centers, as well as how having these spaces within a prestigious and elite university such as Stanford extremely influence student life.

Keywords: Education
Higher Education
Belonging
Community
Cultural Centers
Multicultural Centers
Marginalized Students
Diversity, Equity, and Inclusion
Community Centers
Text
Thesis
Advisor: Martínez Ramón
Kelman Ari
Curating an empire : creating and destroying archives of nature in Spain and Spanish America, 1781-1821

The Enlightenment was an age of institution building. Throughout the 1700s, natural history museums fed by imperial spoils emerged in European capitals. In the case of the Spanish Empire, more studies focus on such institutions in Madrid than those across the Atlantic. Ample textual evidence confirms the creation of two public natural history institutions in Spanish America—one in Mexico City in 1790 and another in Guatemala City in 1797—although the locations of the objects once within them are unknown. I argue that scholars have written about these colonial museums less than about contemporary European museums due to a dearth of extant material specimens from their collections. Throughout my research in Spain, Mexico, and Guatemala, I not only visited traditional textual archives, but also embedded myself within museum collections to study objects. In Spain, I encountered many specimens from the eighteenth century, but I found no such remnants in the Americas. Colonial violence led to the disappearance of objects in the Americas, while they survived on the Iberian Peninsula. On the surface, these findings appear to justify paternalistic rejections of repatriation. Yet, even without their physical collections, the historical impact of long-gone American institutions remains accessible. My dissertation tells the stories of multiple "lost" American collections—natural history museums, botanical gardens, and the spoils of nature collected on expeditions—thus breaking the historian's fixation on objects and "reading" for silences in the modern material archive. I use this decolonial approach to contextualize these American practices and institutions alongside their Spanish analogues.

Keywords: Humanities and Sciences.
History.
Advisor: Findlen Paula
Bleichmar Daniela
Riskin Jessica
Schiebinger Londa L.
A customer journey mapping framework with mobile application

Customer journey mapping (CJM) is a product and service design tool that is widely used by both researchers and practitioners. It tracks the customer and user interactions with products and services during their experiences and maps out significant changes in their experiences. While CJM possesses the advantages of studying customer experiences from their perspectives, it also suffers from limitations such as small sample sizes and biases. This thesis introduces a framework for performing CJM with mobile applications (mobile apps) and analyzing the data collected from the app. The framework was tested on the errand experiences of students and its findings were compared with those of a parallel study using traditional CJM approaches to demonstrate its effectiveness in performing CJM. The results showed that although existing methods are more suitable for small-scale data collection and identifying apparent user interactions, our proposed approach can better target diverse experiences and reveal latent needs. Overall, mobile applications have the potential to improve CJM and provide valuable insights into customer experiences

Keywords: Engineering.
Mechanical Engineering.
Advisor: Okamura Allison
Bernstein Michael S.
Lattin James M.
MacDonald Erin (Erin Faith)
A darker form of discipline : the institutional character of Black literary studies, 1969-1999

What has it meant to produce knowledge and to teach at the intersection of English literature and Black Studies? This dissertation asks after the history and function of Black literary studies as it emerged as an academic discipline in the late 20th century U.S. academy. I propose that Black literary studies' institutional knowledge project is best understood as an endeavor to reflexively theorize the conditions of its own institutionalization. To this end, I illustrate the tremendous promise represented by this endeavor as well as its significant liabilities. This introduction supplies theoretical and contextual exegesis and frames the methodological critique which grounds "A Darker Form of Discipline, " and which animates the broader experiment in interpretive method staged across my four chapters. This experiment attempts to reinvigorate Black literary studies' reflexive sensitivity to institutional knowledge production. Grounded in a disciplinary critique that defamiliarizes the subject/object relation of the critic and the literary text----arguing that Black literary studies' discipline formation relied on the mutualistic, co-creation of criticism and literary tradition----my interpretive method turns to the literary text as a collaborator and an informant on the institutional conditions of Black literary studies' discipline formation. In this way, I work toward a critical practice that can shed light upon its practitioners----helping us to assess the conditions under which we work, and to judge the type of work we actually do

Keywords: Humanities and Sciences.
Advisor: Elam Michele
Rasberry Vaughn
McGurl Mark