VictorJuiz/thesis huggingface dataset:
Exploring semantic changes across early childhood with dynamic word embeddings

Child-directed speech (CDS), commonly known as baby talk, is a major source of linguistic input during early childhood. Caregivers such as parents adapt their language usage for children to facilitate their daily communication. Furthermore, CDS plays a crucial role in shaping their knowledge about the world. To study this input, researchers have begun applying distributional semantic models to large child-directed speech, extracting various patterns of word use/co-occurrence. In this work, we introduce NLP methods that were originally developed to study historical language change to analyze how caregivers change their language use when talking to younger and older children. Some words' usage changed more than others'; this variability could be predicted based on the word's properties at both the individual and category level. We primarily focus on English data in our study. These findings suggest that the patterns of word use may be tuned to children's developmental context, perhaps scaffolding the acquisition of new concepts and skills.

Keywords:  Symbolic Systems Program
Conceptual learning
word embeddings
natural language processing
semantic change
child-directed speech
language and cognition
Thesis
Advisor: Frank Michael C.
Fourtassi Abdellah
Extended Framework for Multifidelity Uncertainty Quantification in Subsurface Flow Systems

Uncertainty quantification is often performed by simulating a large number (O(1000)) of
reservoir models, which can be very computationally expensive when the models are highly resolved.
In this study, a systematic framework is presented to reduce this computational cost by using
models at multiple levels of resolution. Coarsened models are constructed using
an accurate single-phase global transmissibility upscaling approach. The multifidelity framework
proceeds from coarser to finer models and selects subsets of models from the ensemble at
each step. Models are selected such that they approximately span the uncertainty space
for multiple quantities of interest. At the final step of the procedure, only a few (O(10))
simulations are performed at the finest scale. Percentiles are
estimated for these models using either a 'rank-preserving level' or an error model
to approximate cumulative distribution functions (CDFs) for all quantities of interest. Improvements
relative to a previous multifidelity framework, in terms of model selection and percentile assignment, are
introduced and validated. Detailed results are provided for a 2D channelized system, a 2D embedded discrete
fracture model (EDFM) system, and a 3D channelized system. Seven different fidelity levels are
considered, and CDFs for up to 18 quantities of interest are estimated. Results demonstrate that we achieve
generally accurate approximations for all CDFs, with speedups ranging from a factor of 5
to 24 relative to performing all simulations on the fine scale.

Keywords: Energy Resources Engineering
Thesis
Advisor: Durlofsky Louis
Mallison Bradley
Facilitating analog circuit design and debugging with instrumented, programmable hardware

The increasing ubiquity of electronic devices in our world demands effective tools for designing and debugging circuits. Analog circuits in particular interface systems with our physical world, and therefore play a key role in sensing, communication, actuation, and display. As an iterative process, circuit design requires efficiency both in the inspection of circuit behaviors and in the modification of circuit parameters — both of which can be slow, manual, and error-prone when working with analog hardware. This thesis demonstrates how design tools built on instrumented, programmable hardware can address these challenges and accelerate debugging by facilitating inspection and modification of analog circuits. Specifically, instrumentation reveals circuit behaviors passively and in real time, while programmability allows the designer to perform modifications or explore alternatives without reworking the physical circuit. Jointly, these capabilities further afford opportunities for automation to support test-oriented debugging. In this thesis, we describe three novel design tools illustrating the benefits of this approach: The first, Pinpoint, automatically instruments circuit designs and produces customized hardware-software interfaces to programmatically inspect and test PCBs. The second tool, Simpoint, helps designers compare measured and expected behaviors across circuit alternatives by coupling the physical PCB with a simulation. Finally, the third tool, Scanalog, demonstrates how designing circuits on fully programmable analog hardware can further accelerate design by enabling real-time, interactive manipulation of circuit parameters and topology while observing live responses throughout the circuit. Together, these systems and the techniques they enable demonstrate how tools built on instrumented, programmable hardware facilitate fast iteration to support analog design and debugging

Advisor: Agrawala Maneesh
Follmer Sean 
Horowitz Mark (Mark Alan)
Fake news risk : modeling management decisions to combat disinformation

Strategically using information to affect the views of a population is not a new phenomenon and dates all the way back to the earliest development of political systems. Some of the earliest examples still in existence today were produced by a Greek writer Herodotus who penned an inaccurate account of historical events in the Persian empire approximately 500 years after the birth of Jesus Christ. Political propaganda is nearly as old as politics. Similarly, fake news, as a specific tactic of propaganda, is not relegated only to the information age. Older examples are easy to find that pre-date the digital revolution. However, the speed of distribution and the number of people that can be reached by leveraging the modern information infrastructure is unprecedented. These factors combine to result in increased risk from fake news that must be addressed. The internet has enabled the distribution of vast amounts of information to an incredibly large population virtually instantaneously and for comparatively low cost. While the development of this capability has resulted in enormous economic development and provided great benefit to the world, it has also exposed the same population to increased risk. The rapid distribution of fake news can cause contagion, manipulate markets, spark conflict, or fracture strategic relationships. The scourge of fake news is even more problematic with the current limitations on fact-checking methodologies which are unable to keep pace with the increased volume of fake news production. In the search for methods to combat fake news, both public and private organizations are struggling. Probabilistic Risk Analysis (PRA) can be leveraged to quantitatively describe the risk associated with fake news. This thesis presents a method for modeling management decisions designed to combat fake news in an online network. It leverages established infectious disease modeling to describe online virality and implements countermeasure regimes to inform opposition decision making. The model was informed by two online surveys of a representative sample of the U.S. voting population that endeavored to measure the impact of limited but targeted fake news. The results point to both the potential effectiveness and limitations of fake news that is leveraged as part of a targeted influence campaign. The online survey results also point to the dangers of the use of modified video and audio, known as "deep fakes, " in fake news of the future. Technological improvements including expertly crafted deep fakes, online microtargeting, smart trolls, and the potential use of artificial intelligence for content production suggests fake news will continue to persist as a scourge in the future and could present a viable threat to democratic self-governance

Keywords: Management Science and Engineering.
Advisor: Paté-Cornell M. Elisabeth (Marie Elisabeth) 
Persily Nathaniel 
Shachter Ross D.
Fast approximate inference : shifting the Pareto frontier via adaptation

Computing high dimensional discrete integrals is a fundamental problem that underlies probabilistic inference and appears in fields ranging from machine learning to statistical mechanics. This problem has no efficient exact solution, which has led to the development of many approximation strategies that can generally be categorized as sampling, variational, or randomized hashing based inference algorithms. There exists a general trade-off between the approximation accuracy and computational efficiency of these algorithms. This thesis focuses on improving this trade-off. The Pareto frontier of algorithms for a particular inference query captures this trade-off. It consists of state of the art algorithms that cannot be improved upon by any known algorithms in terms of both accuracy and efficiency for the query. In this thesis we present techniques for improving the Pareto frontier, resulting in more accurate approximations for a fixed runtime budget or faster runtime for a fixed level of accuracy compared with prior work. The techniques are generally based on identifying handcrafted algorithmic components that perform a single, static computation on every input problem instance. We then design alternative dynamic components that adapt to specific input instances. First, we hand design an adaptive sampling algorithm for estimating the permanent of a matrix. Second, we design an adaptive randomized hashing algorithm for estimating the number of solutions to a Boolean formula. Next, we show that adaptive strategies can be parameterized and learned directly from data using a novel graph neural network architecture that subsumes belief propagation, a popular and general algorithm that performs variational inference on factor graphs. Finally, we develop a novel inference algorithm that leverages randomized optimization to perform fast inference. In experiments we consider multi-object target tracking, community detection, estimating the partition function of an Ising model, and approximate model counting. Our proposed techniques frequently result in orders of magnitude improvements in terms of approximation accuracy or computational efficiency

Advisor: Ermon Stefano
Ahmadipouranari Nima 
Sabharwal Ashish
Female Presidents: Gender and Political Campaigns

Female heads of state remain a rare phenomenon in the world; the Northeast Asian region has seen two female presidents – Park Geun-hye and Tsai Ing-wen. A study of these two presidents addresses questions about gender bias in political campaigns. While Tsai and Park differ in many aspects, my thesis will explore similarities in their campaigns. This thesis compares campaign materials from four presidential campaigns in 2007, 2011, 2012, and 2015. Both candidates ran an unsuccessful first campaign followed by a successful second campaign. This thesis contrasts the first campaigns with the second campaigns for each candidate then compares the changes made between the campaigns. Changes in campaign messaging are assumed to be intentional and are contextualized. For both candidates, their gender was an unavoidable consideration in their campaign strategy. Consistent with previous literature on gender-based campaign strategy, all four campaigns contained gender-abiding and gender-bending aspects. Outside of these strategies, this thesis focuses on genderless campaign strategies. Genderless strategies downplay a female candidate’s gender without adopting ‘male’ characteristics. It is important to note that both gender-abiding and gender-bending strategies emphasize a candidate’s gender while genderless strategies do not. This thesis analyzes cartoon caricatures and logos that independently represented the candidates. These representations were neither gender-abiding nor gender-bending; rather, they were an attempt to create genderless or androgynous versions of the candidates. They presented an easily identifiable but ungendered visual signature. Although there is no correlation between having a female head of state and improving women’s participation in politics, studying the political campaigns of these female politicians reveals articulated gender bias. How a candidate navigates gendered expectations shows as much about the candidate as it does about a country’s electorate. Electorates accustomed to high proportions of female politicians may be less likely to negatively judge genderless strategies. In turn, female leaders of those governments are able to campaign more frequently as genderless politicians rather than as female politicians.

Keywords:  Stanford Global Studies
Stanford Global Studies
East Asian Studies
South Korea
Taiwan
Presidential Campaigns
Female Presidents
Park Geun-hye
Tsai Ing-wen
Genderless
Gender Bias
Gender-abiding
Gender-bending
Thesis
Advisor: Pan Jennifer
‘Fetal Viability’ in Supreme Court Abortion Cases: Probing the Boundary between Medicine and the Law

The landmark case Roe v. Wade legalized abortion in the U.S. However, it only did so up until the point of ‘fetal viability’, after which the State may prohibit abortion in the interest of protecting ‘potential life’. Roe defined ‘fetal viability’, a concept taken from neonatal medicine, as “the potential to live outside the mother’s womb, albeit with artificial aid,” specifying gestational age as the only relevant factor. As I will demonstrate, this egregiously simplified definition fails to represent the nuanced, medical reality of the issue. This thesis investigates the following three research questions: (1) How is the concept of ‘fetal viability’ scientifically and medically constructed? (2) How has the concept of ‘fetal viability’ been understood and deployed in Supreme Court cases from Roe v. Wade onwards? (3) How does ‘fetal viability’ function as a boundary object between medicine and the law, and what conflicts result from the distinct assumptions and requirements of each discipline? To answer these questions, I analyze various medical sources and key Supreme Court abortion cases in order to perform an interdisciplinary STS analysis of ‘viability’ as a boundary object. I find that ‘viability’ depends on numerous factors other than gestational age and is conceptualized in terms of morbidity and mortality statistics. One cannot generalize ‘viability’ to a single gestational age for all fetuses, and it is antithetical to medical practice to do so. The Roe Court understands ‘viability’ to be a medical fact that draws a clear line between ‘viable’ and ‘non-viable’ fetuses. This interpretation breaks down in later cases as the need to actually implement the ‘viability’ standard forces the Court to reckon with the medical reality of the issue. Furthermore, Roe’s use of the ‘viability’ criterion leaves the constitutional right to an abortion vulnerable to the tides of scientific advancement. The Court failed to recognize that the different assumptions and requirements inherent to the fields of law and medicine would result in disparate conceptualizations of ‘viability’, making ‘viability’ a concept underpowered for the legal weight it was intended to bear.

Keywords: Science Technology and Society
fetal viability
viability
abortion
Roe v. Wade
Planned Parenthood v. Danforth
Colautii v. Franklin
Webster v. Reproductive Health Services
boundary object
Thesis
Fiber Broadband Circulation and Competition: Analyzing Cause and Effect of Fiber Entry

High-speed broadband connectivity is expanding to more Americans, but many communities are left behind. This paper models both the entry decisions of the fiber firms within a regional market and the effects of that entry on incumbent competitors. I use FCC Form 477 accessibility data to analyze the regional characteristics of a census block group that correlated with higher likelihood of recent entry of first fiber firm. Next, the effects of new fiber presence on the maximum and mean speeds offered by already present firms are analyzed. The paper finds that fiber firms are likely responding to both demographic and competition-based factors in a census block group. This paper finds minimal effects of fiber firm entry on the average speed offered in the block group, and a negative impact on the speed offered by the fastest incumbent.

Keywords: fiber
broadband
speed
competition
Thesis
Advisor: Rosston Greg
Clerici-Arias Marcelo
Field experiments in firms

This dissertation studies the impact of managerial practices on firm performance. Using three field experiments in multiple firms, I offer a unique perspective on the causal impacts of delegation in hiring, the strategic allocation of managerial attention, and peer performance information provision on employee and firm performance. Chapter 1 uses a 12-month field experiment in a large retail chain to study the value of delegation in hiring to local branches. Chapter 2 draws upon a 6-month field experiment in a leading multinational spa chain to understand the optimal allocation strategy of managerial attention. Chapter 3 develops a 7-month field experiment in the spa chain to study how the provision of experienced workers' performance trajectory and peers' performance information influences employee attrition, productivity, and firm performance

Keywords: Business.
Advisor: Casey Katherine Elizabeth 
Lazear Edward P. 
Abramitzky Ran
Shaw Kathryn 
Sterling Adina
Financing Farmers in Brazil: Designing a Lending Marketplace to Match Farmers and Lenders

This thesis answers the following question: How can a centralized credit marketplace be used to improve the offer of funding for farmers in Brazil? It presents a study of the credit market for farmers in Brazil, an environment that has a high potential for a centralized credit marketplace. It explores how matching and market design theory and tools can be applied to develop this marketplace to improve farmers’ access to financing. Available literature can also be used to design the governance rules of the platform to deal with the strategy of participants, thickness, congestion, and safety issues. Beyond the core interaction (loans) between lenders and farmers, the marketplace can attract other providers of goods and services that can help the marketplace become thicker by increasing the trustworthiness and reducing information asymmetry3⁄4spinning the network effects of the marketplace. Data, from conventional and non-traditional sources, is critical not only for the designing of an efficient matching algorithm but also for building a robust algorithm of credit risk assessment of farmers. The regulatory conditions for the marketplace were set by the Central Bank of Brazil in 2018 with the introduction of the appropriate regulation. In this regard, a centralized credit marketplace for farmers is a suitable solution at the right time.

Keywords:  Public Policy Program
Stanford University
Humanities and Sciences
Public Policy Program
agriculture
Brazilian agriculture
credit for farmers
farming
financing farmers
food security
data
lending marketplace
online marketplace
rural credit
online lending
Thesis
Advisor: Athey Susan
First principles approaches towards modeling the electrochemical interface

In light of recent global climate trends resulting primarily from anthropogenic carbon emissions, there is a growing need to transition away from our reliance on fossil fuels. Perhaps the most promising approach towards this goal is the incorporation of renewable energy resources, such as wind and solar, more heavily into our energy grid. Unfortunately, these resources are inherently intermittent in time. To eliminate fossil fuels from our energy mix, grid-scale energy storage on both the daily and seasonal time scales will therefore be necessary. Energy storage on such an immense scale can in principle be practically achieved by storing energy in the form of chemical bonds; however, in practice the efficient conversion of low energy to high energy compounds (and vice-versa) is hampered by poor catalysts, despite decades of research efforts. This thesis focuses on developments in utilizing computer simulations to search for catalyst materials that are capable of efficiently electrochemically converting chemicals for energy storage. Density functional theory (DFT) has proven to be a very useful tool in simulating catalytic processes, and has successfully led to design tools for catalyst prediction. However, the application of DFT to electrochemical reactions has long been complicated by the complexity of the electrochemical interface: rather than simulating a gas-solid interface, we must simulate an electrified liquid-solid interface. In the first part of this thesis, we examine a commonly used and criticized approximation in our simulations, namely that electron transfer from a metal surface to an adsorbing molecule occurs on a timescale much faster than the timescale of the molecular adsorption. We then turn our attention to the treatment of the solvent in our simulations of the electrochemical interface, beginning with an explicit treatment where solvent molecules are explicitly included in the simulation. Finally, we explore an implicit treatment of the electrolyte by the incorporation of a polarizable dielectric continuum. We show that while implicit treatments offer a much simpler way to compute reaction energetics, great care must be taken both when considering parameterization of the model (for, among other things, solvation energies), and in understanding the electrostatics involved in the reaction events studied. We conclude by developing a new method for simulating electrochemical reaction events, by considering a hybrid explicit-implicit approach to modeling the interface. In particular, we show the surface charge to be a better descriptor for the driving force, as opposed to the traditionally considered work function of the electrode

Keywords: Chemical Engineering.
Advisor: Jaramillo Thomas Francisco
Noerskov Jens
Qin Jian (Professor of Chemical Engineering)
Focus and ocular parallax cues for virtual and augmented reality displays

Immersive computer graphics systems strive to generate perceptually realistic user experiences. Current-generation near-eye displays, such as virtual or augmented reality (VR/AR) displays, have made significant progress towards this goal with advances in certain technologies: interactive, photorealistic rendering; high-resolution, high-refresh-rate, low-persistence, stereoscopic displays; and low-latency head tracking. Modern VR and AR systems provide all of these capabilities and create experiences that support many, but not all, of the monocular and binocular depth cues of the human visual system, including occlusions, shading, binocular disparity, and motion parallax. However, at least two depth cues--focus and ocular parallax cues--are missing. In this dissertation, I introduce and evaluate practical systems aimed at creating perceptually realistic experiences by supporting these two cues

Keywords: Electrical Engineering.
Advisor: Wetzstein Gordon 
Girod Bernd 
Wandell Brian A.