VictorJuiz/thesis huggingface dataset:
Leveraging prior knowledge and structure for data-efficient machine learning
Keywords: Electrical Engineering.

Building high-performing end-to-end machine learning systems primarily consists of developing the machine learning model and gathering high-quality training data for the application of interest, assuming one has access to the right hardware. Although machine learning models are getting increasingly commoditized in the last few years with the rise of open-sourced platforms, curating high-quality labeled training datasets is still either costly or not feasible for many real-world applications. Hence, we mainly focus on data in this thesis, specifically how to (1) reduce dependence on labeled data with data-efficient machine learning methods through either injecting domain-specific prior knowledge or leveraging existing software systems and datasets that have initially been created for different tasks, (2) effectively manage training data and build associated tooling in order to maximize the utility of the data, and (3) improve the quality of the data representations achieved by embeddings by matching the structure of the data to the geometry of the embedding space. We start by describing our works on building data-efficient machine learning methods for accelerated magnetic resonance imaging (MRI) reconstruction through physics-driven augmentations for consistency training, scale-equivariant unrolled neural networks, and weak supervision using untrained neural networks. Then, we describe our works on building data-efficient machine learning methods for natural language understanding. In particular, we discuss a supervised contrastive learning approach for pre-trained language model fine-tuning and a large-scale data augmentation method to retrieve in-domain data. Related to effectively managing training data, we discuss our proposed information extraction system for form-like documents Glean and focus on the often overlooked aspects of training data management and associated tooling. We highlight the importance of effectively managing training data by showing that it is at least as critical as the machine learning model advances in terms of downstream extraction performance on a real-world dataset. Finally, to improve embedding representations for a variety of types of data, we investigate spaces with heterogeneous curvature. We demonstrate mixed-curvature representations provide higher quality representations both for graphs and for word embeddings. Also, we investigate integrating entity embeddings from Wikidata knowledge graph to an abstractive text summarization model to enhance factuality
Life in the Margins: Minor Characters in Katherine Mansfield’s Short Stories
Keywords: English
minor character
Character
Women in literature
queer women in literature
Marginality, Social, in literature
Short story
Short stories, English
Queer theory
British colonies
New Zealand
Mansfield, Katherine, 1888-1923
Short stories (Mansfield, Katherine)
Text
Thesis

Many of Mansfield’s stories are lauded for their layered depictions of major characters’ interiority. As central as these are to her work and her exploration of character, this focus only on perspective characters can minimize the importance of minor characters in her more crowded stories like “At the Bay,” “Bliss,” and “The Garden Party.” These characters, despite their places in the margins of their stories, fill a large part of these stories’ character-systems and play off of one another and off of the major characters to create a complex web of meaning that enhances and adds to the many interpretations that the stories offer. They are also a ground for modernist experimentation as much as plot or structure are, and Mansfield uses them to explore and discover new roles for minorness in fiction. The women Mansfield wrote about resembled her in many ways, and she drew on her own experience as a marginalized writer to depict them. This marginalization also contributed to the long-standing perception of her as a minor writer, pushed aside in the narrative of the development of literary modernism just as the (often marginalized) minor characters are in her stories. Yet Mansfield’s minor characters are not solely defined by their minorness, instead presenting avenues for exploration of sexuality, class, colonialism, and gender.
Lighthouse: Combatting Disinformation On Encrypted Messaging Services
Keywords: Computer Science
Disinformation
Encrypted Messaging Services
Text
Thesis

With the advent of social media as a crucial news source for the average smartphone owner, the spread of disinformation, and curated fake news, as a tool for political propaganda on encrypted messaging services is becoming an expanding threat to the public’s perception of news and journalis- tic accuracy. While several systems are in place to detect fake news on public networking platforms, the availability of encrypted messaging has made disinformation notoriously easy to disseminate but challenging to detect in the quest to alert users of fallacious information. Based on previous research that found that increasing awareness of fake news can noticeably reduce its spread, we designed Lighthouse, a standalone application that makes use of notifications from WhatsApp to detect links that have been professionally flagged as disinformation, and alerts users to potentially spurious news articles that have been sent to them. Lighthouse uses the NewsGuard disinformation database as a truth source with the intention of increasing accuracy awareness in the context of fake news as a method to fight the further spread of disinformation. The current implementation of the app serves as a starting point for the further study of disinformation dissemination and intervention methods aimed at addressing curated fake news on platforms protected by end-to-end encryption. It was used by 10 university students over one-week periods to test for database relevance and was found to positively influence the ability to identify disinformation and demonstrated the potential to alter sharing habits.
Likelihood ratio testing in critically-spiked wigner models
Keywords: Statistics.

Spiked random matrix models are widely used to model data in which a low-rank signal exists alongside high-dimensional noise. When the eigenvalues of this signal, known as spikes, are either above or below a certain critical threshold, the corresponding models have been widely studied and are well understood. However, the behavior of models with spikes at the critical threshold is more difficult to study, and has often remained elusive, despite the existence of data that is not well-explained by either sub- or supercritical models. This thesis contains the results of series of projects that investigate the likelihood ratios for Gaussian models with critical spikes. It includes rigorous results illustrating the transition between the qualitatively different sub- and supercritical regimes, which has applications not only in statistics, but also in the statistical physics of the SSK model for magnetism. It also contains edge universality results, demonstrating how the quantities crucial for understanding the likelihood of critically-spiked Gaussian random matrices can be extended to their Wigner counterparts. The thesis concludes with a presentation of results about phenomena occurring exactly at the critical threshold, determining the contiguous set of alternatives for testing a critical spike and providing the first description of the limiting likelihood ratio for such tests
Linear periodically time-varying circuits for the Internet of Everything
Keywords: Electrical Engineering.

As the Internet of Everything (IoE) ushers in an age with tens of billions of connected devices, there is a persistent demand for radio receivers to join this ever-growing network. In particular, low power consumption is a critical requirement in order to enable remote deployments and battery-powered operation while receiver linearity specifications are only moderate. With this in mind, the passive mixer-first receiver is an attractive option for the IoE because it requires no external components and offers baseband-controlled impedance matching, high-Q filtering, and RF input range over a decade or more; however, it requires high power to achieve low noise figure due to the lack of gain at RF. Recent work has demonstrated that a transformer--mixer cascade can facilitate significant power savings at the cost of increased area and restricted RF input range. In this dissertation, we propose a low-power passive N-path harmonic-rejection transformer-mixer for narrowband IoE applications. Composed of only switches and capacitors, this circuit integrates the behavior of a transformer and harmonic recombination into the passive mixer itself, providing voltage gain, harmonic-rejection, and high-Q filtering before any active components and while supporting a wide RF input range. We also propose a single-transistor amplifier with back-gate feedback for high power efficiency in the receiver baseband while maintaining sufficient linearity at low supply voltages. Prototype amplifier measurements in 22-nm FD-SOI demonstrate that back-gate feedback improves linearity by 6--20 dB and reduces device-to-device gain variation by 5--10× compared to a conventional design. Finally, we present measurements of a prototype receiver with an N-path harmonic-rejection transformer-mixer at its core and with back-gate feedback employed in the baseband amplifiers. The receiver occupies just 0.064 mm² in a 22-nm FD-SOI technology and consumes 0.6-1.8 mW across the operating range of 0.3--3.0 GHz. It achieves 3.4--4.8-dB NF, 14--18-dBm OB-IIP3, -5--0-dBm OB-B1dB, -8/-3-dBm H3/H5-B1dB, and < 1-dB NF degradation with a -15-dBm OB blocker, demonstrating that the proposed techniques enable power and area savings while achieving performance suitable for the IoE
Lingering Effects: An Analysis of the Teacher Incentive Fund
Keywords: Lingering Effects
Teacher Incentive Fund
Standardized Test Outcomes
Texas
Department of Economics
Text
Thesis

The ability to predictably increase student outcomes has clear value to primary and secondary education. The methods by which that is achieved, however, are less clear. Throughout the past few decades, several government programs and plans have been put forth to improve these outcomes. The Teacher Incentive Fund “TIF” is a unique government grant program that specifically targets teacher and administrator professional development. Using data from the Texas Education Agency, I seek to determine the effect of the TIF on 5th grade standardized test scores as well as SAT scores and participation rate. The grants studied last only 5 years, raising the additional question of whether or not such a short-term grant can have longer-term effects at a school. I look for these “lingering” effects as well as effects during the 5-year grant period using a set of difference in differences regressions using both synthetic and non-synthetic control groups. The non-synthetic results yield inconclusive or no evidence for each hypothesis tested. The synthetic-control regressions provide 1) weak evidence for a positive effect on SAT participation rate and negative effect on SAT scores during the active grant period in large cities; 2) weak evidence for positive active-grant and lingering effects on 5th grade standardized math scores in Austin ISD but no evidence of effects on reading or either reading or math in other regions tested (state-wide and Houston ISD).
Linking heat stress resistance and recovery in reef-building corals
Keywords: Biology.

Organisms are facing more intense and frequent stress events in their environments due to climate change impacts, and resilience capacity plays a vital role in survival and persistence through generations. Two important components of stress resilience are the ability to resist and recover from stress. Yet, there is limited understanding of how mechanisms of an individual's resistance and recovery ability contribute to overall resilience, how resistance and recovery may be linked, and whether there are other physiological tradeoffs associated with resistance and recovery. Reef-building corals are the foundational taxa of highly diverse and productive marine ecosystems, and ocean warming represents one of the biggest threats facing corals currently and under future climate change scenarios. Yet, experiments on coral resilience research focuses primarily on identifying and bottling those corals that are predicted to excel at bleaching resistance. However, as our oceans continue to warm, even the most bleaching resistant corals will be at a high risk of bleaching. Therefore, it is valuable to shift focus toward comprehensively evaluating the interconnectedness of other stress resilience factors, like heat stress resistance and recovery. In this dissertation, I characterize patterns of individual heat stress resistance and recovery ability in the tabletop coral Acropora hyacinthus. I show that mortality after short-term heat stress occurs rapidly and is positively correlated with bleaching severity, bleaching state is stable after heat stress, and there is a high likelihood of longer-term recovery if corals survive the first week post-stress. I also show that moderately resistant corals exhibit higher skeletal growth than low and high resistant corals by four months post-heat stress, and that there is significant differential gene expression between low, moderate, and high resistant corals at pre- and post-heat stress timepoints that may illuminate underlying mechanisms of individual resistance and recovery. These results provide insight into putative links between coral heat stress resistance and recovery, and fitness tradeoffs associated with resilience capacity
Long-distance compensatory lengthening
Keywords: Linguistics.

Compensatory lengthening (henceforth, CL) is the phenomenon wherein one segment in a word is deleted or shortened, and another is lengthened to make up for it. Traditionally, the two segments involved have always been adjacent to one another, or in adjacent syllables and separated by only a single consonant. As such, previous accounts of CL have assumed (either tacitly or explicitly) that these were the only possibilities. In this thesis, I present evidence from Slovak and Estonian that the two sounds can in fact be separated by any distance. In Slovak, the deletion or shortening of one vowel can cause another vowel two syllables away to lengthen. In Estonian, the deletion of a vowel anywhere in the word can cause the first syllable to lengthen. The existence of such patterns warrants a new theoretical account of CL, which is exactly what this thesis will provide. I will argue that CL amounts to the movement of a mora from one segment to another, and that moras are required to move as little as possible in this way. This is enforced via the proposed constraint M(ULTI)T(IER)-LIN(EARITY), which is an expanded version of LIN that punishes the inversion of precedence relations between any two nodes in the prosodic hierarchy---including moras and segments. It is violated more the further a mora moves from its original position, and therefore assigns a greater number of violations to long-distance CL than local CL. If this constraint is highly-ranked, CL will be purely local. If it is dominated by other markedness constraints, CL can be forced into being long-distance if such is necessary in order to avoid violations of those markedness constraints
Long-term intertidal community change following mass mortality of Pisaster ochraceus, a keystone marine predator
Keywords:  Department of Biology
Biology
Keystone species
Pisaster ochraceus
Mytilus californianus
Mussels
Sea Star Wasting Disease
Marine ecology
Predation
Recruitment
Text
Thesis

Beginning in 2013, a Sea Star Wasting Disease epidemic caused a mass mortality event for the ochre sea star (Pisaster ochraceus) and several other sea star species across their entire range of distribution in the California Current region. Because Pisaster ochraceus is a keystone species in rocky intertidal communities and has been shown to control California mussel (Mytilus californianus) populations and prevent their competitive dominance under several settings, thereby maintaining intertidal community diversity, sudden sea star population declines are expected to cause cascading changes on the community. This study tests this prediction and investigates how the natural removal of keystone predation affects the rocky intertidal community in the long term. Previous studies conducted at Hopkins Marine Station, in Monterey Bay, California, in 2014 and 2015 found a limited and spatially heterogeneous expansion of M. californianus following the sea star demise. Field surveys of 18 mussel plots at two sites at Hopkins Marine Station conducted three times a year between 2014 and 2021 show that mussel cover has been increasing since 2014, when there was a peak in mussel recruitment in the area, and that the lower limit of mussel beds has been shifting to lower tidal heights, supporting the hypothesized mussel expansion following predator mass mortality. However, long-term monitoring of the P. ochraceus population at Hopkins Marine Station shows that sea star abundance has been declining since long before 2013. It is therefore likely that changes in M. californianus abundance and distribution are driven by other factors, such as recruitment variability and extreme events in addition to predation pressure. As more mass mortality events are expected under warming conditions in the coming decades, the results of this study, and of future research addressing the impact of multiple stressors on intertidal communities can inform predictions about how the community will change when these events occur.
Look Who’s Talking: Examining the role of racialized beliefs in language processing and speaker judgments
Keywords: language and race
linguistic discrimination
language processing
race and perception
speaker perception
Text
Thesis

We heavily depend on information about who is talking, as well as our prior beliefs about the world, to construct meaning. However, there exists little empirical research on the role of preconceived notions and stereotypes in how we process utterances and judge their speakers. In a series of three experiments, I examine how racialized ideologies affect both language comprehension and listeners’ judgments of different speakers. I first investigate whether racialized stereotypes and beliefs affect comprehension using a series of self-paced reading tasks (Experiments 1 & 2), and then ask whether racial (and gendered) biases affect the degree to which listeners penalize speakers for interrupting (Experiment 3). Experiments 1 and 2 provided no evidence for the activation of racialized stereotypes. The findings from Experiment 3 suggest that race and gender significantly affect how a speaker is judged. When interrupting, female speakers were judged to be less prosocial, more aggressive, and less intelligent than male speakers. And when interrupting, Black speakers were judged to be less prosocial, and more aggressive than White speakers. These results suggest that the perceived race and gender of a speaker — and the implicit biases associated with race and gender — affect how harshly a listener penalizes that speaker for interrupting. This penalization has broader consequences in larger societal systems including the courtroom and classroom.
Low power techniques for wireless MRI receiver arrays
Keywords: Electrical Engineering.

A longtime goal of the MRI community has been the development of conformal wireless receiver arrays as an alternative to their bulky, rigid, and often uncomfortable standard implementations. Current MR receive channels require high power consumption to enable the stringent Noise Figure, Gain, and Dynamic Range necessary for clinically relevant data. Combined with high channel counts (32 to 96), power consumption is a major challenge when translating to the wireless use case. As the pre-amplifier is the receiver element that determines many performance metrics and can consume over 200mW it is a prime candidate for re-evaluation. In this work, I will present an alternative SiGe HBT based MRI pre-amplifier with power con- sumption up to 28x less than current HEMT-based devices. Its potential for integration is first evaluated through behavioral modeling alongside a real image dataset. Following initial simulated results, its impact on imaging performance is evaluated via benchtop evaluation with MR-relevant receiver components. Alongside this pre-amplifier I propose a semi-blind calibration and compensa- tion framework that can be integrated into the existing pre-scan period for dynamic range expansion, as this amplifier features reduced linearity relative to MR standards. The application of this cali- bration method is able to reduce errors stemming from non-linear distortion to levels comparable to industry reference amplifiers. This is followed by preliminary work integrating this amplifier and calibration method into a 1.5T system demonstrating example calibration experiments and phantom images. The presented calibration method is applied to these images recovering image quality and illustrating the potential for the utility of the presented amplifier and calibration method. This concludes in a discussion regarding system level integration considerations for such a method in high-channel count arrays
Machine learning and crowdsourcing for digital behavioral phenotyping
Keywords: Bioengineering.

Early childhood is the most potent opportunity to impact long-term health and learning. However, there are major bottlenecks to care, with a massive shortage of clinicians for diagnosis and treatment, disproportionately affecting underserved populations. This thesis centers around developing a streamlined system for continuously phenotyping children with potential developmental delays by leveraging distributed non-expert crowdworkers in conjunction with machine learning algorithms. This work involves collecting diagnostically rich information from children and their parents in a secure and trustworthy manner, curating a reliable and capable crowd workforce for labeling behavioral features, and training behavioral computer vision classifiers for detection of neurodevelopmental concerns