VictorJuiz/thesis huggingface dataset:
Platforms and algorithms for decision making at scale

The Internet is strengthening democracy by empowering individuals. Social media enables real-time dissemination of information. Online social networks enable people to come together in support of common causes. But despite the prevalence of Internet technologies, there has yet to be an online platform where large-scale democratic decision making occurs regularly as a society. Multiple obstacles remain in the way of building such platforms. For example, places where users can exercise free-form speech often degenerate into vitriol. The unstructured, large-scale nature of the Internet means that it is not obvious what the optimal way to aggregate opinions is and how to act on them. In this dissertation, we discuss our work on building platforms that tackle these issues from theoretical and practical perspectives. Specifically, - Participatory Budgeting (PB): PB is a democratic process where citizens vote on public budgets. We propose Knapsack Voting, a vote aggregation method in PB, and show that it is welfare-maximizing and strategy-proof under certain utility models. We also discuss the Participatory Budgeting Platform (pbstanford.org), our open-source platform for running online PB elections. It has been used throughout the United States, including Chicago, Boston, Seattle, and New York City, and has distributed over 60 million of public budgets. - Sequential Deliberation: Sequential deliberation is a vote aggregation method that uses rounds of small group interaction and can be used in decision spaces that are too complex for ordinal voting. We show that this method converges to the optimal point quickly under certain utility models. We also show how sequential deliberation can be used in PB to handle project interdependencies. - Online Deliberation Platform: We discuss our platform for conducting large-scale Deliberative Polls with an automated moderator that can support over 1,000 simultaneous participants (stanforddeliberate.org). The platform has been successfully deployed in the US, Canada, Chile, Hong Kong, and Japan, where people deliberated on complex issues such as health care, renewable energy, and foreign policy. We discuss the technical challenges and our study on the efficiency of the platform

Keywords: Management Science and Engineering.
Advisor: Goel Ashish
Ashlagi Itai
Fishkin James S.
Policy evaluation and learning in adaptive experiments

Adaptive experiments are becoming increasingly prevalent due to the ability to largely improve sample efficiency to fulfill particular objectives. This results in the growing availability of data collected from these designs such as contextual bandits. A natural query arises: can we reuse the data to answer a variety of questions that may not be originally targeted by the experiments? However, adaptivity also poses great statistical challenges if the post-analysis objective differs significantly from the original, and standard approaches used to analyze independently collected data can be plagued by bias, excessive variance, or both. This thesis aims to serve as a research investigation of one step towards such post hoc analyses around two themes: evaluating other treatment assignment policies to guide future innovation or experiments, and learning optimal policies to facilitate personalization. Our main contributions are as follows: (i) We present a family of generalized augmented inverse propensity weighted (AIPW) estimators to evaluate a given policy with adaptively collected data from multi-armed bandits. Our approach is to adaptively reweight the terms of an AIPW estimator to control the contribution of each term to the estimator's variance. This scheme reduces overall estimation variance and yields an asymptotically normal test statistic. (ii) We extend the adaptive weighting approach to evaluate policies in contextual bandits, where the weights are carefully chosen to accommodate the variances of AIPW terms that may differ not only over time, but also across the context space. The resulting estimator further reduces estimation variance. (iii) Based on a special variant of above estimators, we propose an algorithm to learn optimal policies with contextual bandit data and establish its finite-sample regret bound. We complement this regret upper bound with a lower bound that characterizes the fundamental difficulty of policy learning with adaptive data. Collectively, we hope our results can shed light on the design and implementation of hypothesis testing and efficient policy learning using adaptively collected data

Advisor: Athey Susan
Van Roy Benjamin
Wager Stefan
Political representation in democratic and autocratic regimes

This dissertation studies political representation in democratic and autocratic regimes. It asks two questions: first, how can citizens influence politics in some of the least democratic regimes? Second, how do citizens form their expectations of political representation following authoritarian breakdown? The dissertation answers these questions in the context of the former German Democratic Republic (GDR) and consists of three papers. The first paper challenges a key assumption in models of electoral politics, according to which electoral contestation is a precondition for political decision-makers to respond to the demands of their constituents. Using a unique dataset of petitions to the central government of the former GDR, I show that despite uncontested elections, the GDR engaged in electoral cycles of responsiveness: petitions were answered more quickly and were more likely to be successful before elections. The second paper explores the relationship between emigration and authoritarian stability. Extant work on this topic usually focuses on emigration from open regimes---that is, autocracies that impose few restrictions on citizens' ability to leave---and focus on remittances and norm diffusion. By contrast, I study emigration from a closed autocracy and emphasize alternative mechanisms. Exploiting an involuntary emigration reform in the former GDR in 1983, I argue that emigration can have countervailing effects on the stability of closed autocracies. On the one hand, the exit visa system in such a setting generates information about troublemakers, which improves autocratic stability. But on the other hand, letting some people leave an otherwise closed regime can create more demand for emigration among left-behind citizens, which undermines stability. The third paper asks where public support for democracy comes from after autocratic breakdown. The existing literature usually focuses on the role of autocratic legacies or contemporary economic or political performance. I emphasize instead the importance of the early democratic years: the mode by which countries transition from autocracy to democracy can lastingly shape citizens' expectations of and beliefs about democratic governance. Evidence for this argument comes from an original survey experiment, household panel data, and observational data on historical unemployment and present-day voting for the far-right populist \textit{AfD}. Taken together, the dissertation identifies two new research agendas. I call for a departure from the traditional focus on co-optation and repression in scholarship on authoritarian regimes and for more research on the ways in which ordinary citizens can gain representation and influence politics in non-democratic regimes. Moreover, while research on the legacies of autocratic rule abounds, I emphasize the important consequences that autocratic breakdown can have for political attitudes, behavior, and long-term democratic stability

Keywords: Political Science.
Advisor: Grzymała-Busse Anna Maria
Fouka Vasiliki
Hainmueller Jens
Rodden Jonathan
A polyhedral compiler for image processing hardware

Image processing applications can benefit tremendously from hardware acceleration. However, hardware accelerators for these applications look very different from the programs that image processing algorithm designers are accustomed to writing. As a result, many image processing hardware compilers have been designed to generate hardware accelerators from high-level specifications of image processing algorithms. Unfortunately, all of these compilers either exclude crucial access patterns, do not scale to realistic size applications, or rely on a compilation process in which each stage of the application is an independently scheduled module that sends data to its consumers through FIFOs which adds resource and energy overhead while inhibiting synthesis optimizations. In this thesis we present a new algorithm for compiling image processing applications, Clockwork, that uses a combination of techniques from polyhedral analysis and synchronous dataflow (SDF) to overcome these limitations. Clockwork compiles the entire application into one flat, statically scheduled module. As a result, accelerators produced by Clockwork have fixed latency, cannot deadlock, and have no resource overhead from inter-stage FIFOs. We show that designs generated by Clockwork achieve on average a 55% reduction in LUTs, a 30% reduction in flip-flops, and a 22% reduction in BRAMs compared to a state-of-the-art stencil compiler at the same throughput, while handling a wider range of access patterns. Clockwork scales to applications with more than 100,000 LUTs. For an image processing application with dozens of stages, Clockwork achieves energy efficiency 260x that of an 8 thread Intel CPU, 17x that of an NVIDIA K80 GPU, and 2.4x that of an NVIDIA V100 GPU

Advisor: Hanrahan P. M. (Patrick Matthew)
Fatahalian Kayvon
Kjolstad Fredrik
Polymer sorting of single-walled carbon nanotubes : additives and applications

Single-walled carbon nanotubes (CNTs) are a promising candidate for flexible and wearable electronics, offering robust mechanical properties, solution-processability as well as superlative charge carrier mobilities. However, bulk synthesis of CNTs produces a mixture of metallic and semiconducting species, greatly limiting their technological utility. To address this issue, various post-synthesis purification schemes have been investigated. Polymer sorting in particular has emerged as a scalable and accessible solution to this problem, offering fast processing times of 1-2 hours, yields over 20% and semiconducting purities as high as 99.99%. Despite these encouraging developments, there is still much to be desired from this strategy, including greater mechanistic insight, higher yields and purities, chiral selectivity, and reducing the polymer's effect on CNT device performance, among others. This thesis discusses the role of additives on polymer sorting of CNTs. First, I will describe the importance of polymer recyclability to the scalability of the sorting process, and introduce a recyclable, 2-ureido-4-pyrimidinone-based supramolecular polymer. I will then show that the molecular weight and conformation of this polymer can be tuned by the addition of monofunctional chain stoppers, enabling improvements in sorting yields without compromising the purity or properties of sorted CNTs. Next, I will recount the mechanistic principles underlying polymer sorting, and examine the effects of polar cosolvents in the context of the polarizability hypothesis of CNT sorting. Finally, I will present a cosolvent-based flocculation technique for reducing the amount of excess sorting polymer in polymer-sorted CNT dispersions. This method can be used to improve the mobility and on-off ratio of CNT thin-film transistors regardless of the choice of sorting polymer, and also leads to enhanced process compatibility and versatility, facilitating the fabrication of stretchable, all-inkjet-printed CNT transistor arrays. Taken together, these forays demonstrate the importance of additives to the polymer sorting process, both in terms of sorting efficacy as well as the performance of resulting CNT devices

Keywords: Materials Science and Engineering.
Advisor: Bao Zhenan
Hong Guosong
Mannix Andrew J.
Posterior sampling for efficient reinforcement learning

Reinforcement learning has shown tremendous success over the past few years. Much of this recent success can be attributed to agents learning from an inordinate amount of data in simulated environments. In order to achieve similar success in real environments, it is crucial to address data efficiency. Uncertainty quantification plays a prominent role in designing an intelligent agent which exhibits data efficiency. An agent which has a notion of uncertainty can trade-off between exploration and exploitation and explore in an intelligent manner. Such an agent should not only consider immediate information gain from an action but also its consequences on future learning prospects. An agent which has this capability is said to exhibit deep exploration. Algorithms that tackle deep exploration, so far, have relied on epistemic uncertainty representation through ensembles or other hypermodels, exploration bonuses, or visitation count distributions. An open question is whether deep exploration can be achieved by an incremental reinforcement learning algorithm that tracks a single point estimate, without additional complexity required to account for epistemic uncertainty. We answer this question in the affirmative. In this dissertation, we develop Langevin DQN, a variation of DQN that differs only in perturbing parameter updates with Gaussian noise, and demonstrate through a computational study that Langevin DQN achieves deep exploration. This is the first algorithm that demonstratively achieves deep exploration using a single-point estimate. We also present index sampling, a novel method for efficiently generating approximate samples from a posterior over complex models such as neural networks, induced by a prior distribution over the model family and a set of input-output data pairs. In addition, we develop posterior sampling networks, a new approach to model this distribution over models. We are particularly motivated by the application of our method to tackle reinforcement learning problems, but it could be of independent interest to the Bayesian deep learning community. Our method is especially useful in RL when we use complex exploration schemes, which make use of more than a single sample from the posterior, such as information directed sampling. Finally, we present some preliminary results demonstrating that the Langevin DQN update rule could be used to train posterior sampling networks, as an alternative to index sampling, and further improve data efficiency

Keywords: Electrical Engineering.
Advisor: Van Roy Benjamin
Brunskill Emma
Pilanci Mert
Post-Paleozoic Trends in the Abundance of Benthic Marine Organisms: Increasing Skeletal Abundance in Shallow-Marine Environments over the past 250 million years

Variations in skeletal abundance through geological history, when combined with organismal body size, can provide a much-improved quantification of
animal abundance in marine environments, an important control on energy and nutrient flow through such systems. Increases in abundance have long been hypothesized to explain the increase in taxonomic diversity and mean animal body size in marine communities during the post-Paleozoic (252 Mya - Present) but total biomass has remained more poorly constrained than taxonomic diversity and body size due to the challenge of collecting relevant data. For this study, the abundance of skeletal fossils in marine limestones from the earliest Triassic through the Neogene (252 - 0 Mya) was evaluated in order to more directly quantify the absolute abundance of skeletal animals, algae, and foraminifera in marine carbonate environments. Absolute abundance data were collected from thirteen previously published papers reporting point count data for 1596 rock samples totaling to around 400,000 individual points. These data were recorded along with the geologic age, depositional environment, and standardized at the phylum and class level. An increase in the abundance of calcifying organisms across the post-Paleozoic was found, with the exception of a short-term decline following a major mass extinction event at the end of the Triassic period (201 Mya). These findings support the hypothesis that the abundance of marine biota has increased since the start of the Mesozoic, suggesting that increased trophic resources were at least one factor enabling the increases in taxonomic diversity. These and similar findings also have implications for modern conservation efforts. Conservationists can use these data as a deep-time baseline against which to compare changes in abundances within modern marine environments to identify ecosystems most in need of protection.

Keywords:  School of Earth
Singh, Pulkit
School of Earth Energy &amp; Environmental Science, Paleoecology, Post-Paleozoic, Marine Abundance
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Thesis
Advisor: Payne Jonathan
Sperling Erik
The power and limits of preprocessing in cryptography

Preprocessing refers to a computation that is executed before one is given the inputs to a certain computation task. Preprocessing can be used to speed up some cryptographic systems but also to speed up cryptanalytic attacks. This thesis explores the power and limits of preprocessing for both of these goals. First, we study algorithms with preprocessing for some of the most central problems that underpin the security of modern-day cryptosystems. We give new lower bounds for generic algorithms with preprocessing for the discrete-logarithm, CDH, and DDH problems. We also present new connections between the task of inverting functions with preprocessing and other areas of theoretical computer science. These connections shed light on the gap between the best known upper and lower bounds for the function-inversion problem and give rise to better algorithms for well-studied problems in complexity theory and data structures. We then turn to using the power of preprocessing to construct new protocols for private information retrieval. Our protocols allow fast (sublinear-time) private database lookups without increasing the server-side storage requirements. Finally, we present Checklist -- a system that uses these protocols for private blocklist lookups. In Checklist, a client can determine whether a particular string appears on a server-held blocklist, without leaking its string to the server. We implement and evaluate Checklist in the context of the "Safe Browsing" blocklist, which all major browsers use to prevent web clients from visiting malware-hosting URLs

Advisor: Boneh Dan
Reingold Omer
Wootters Mary
The practical point of view and constructivism : from transcendental idealism to metanormative constructivism

This project examines a family of views that can be seen as contemporary descendants of a tradition inspired by Immanuel Kant's transcendental idealism—a constructivism about human freedom and responsibility, and about values, reasons and normative truths in practical and moral philosophy. I investigate views that attempt to vindicate practical freedom by appeal to the so-called "practical point of view." Some views are designed to show that constructivism justifies that we are genuinely free and responsible for what we do. Other views concern the constitution of human agency in their accounts and explanations of normative entities. One fundamental issue I will investigate is whether "constitutivist constructivism" can be considered a distinctive general position in practical or moral philosophy about the nature of the normative. While I think they may have distinguished their views from, on one end, dispositionalism and, on the other end, robust realism, it is a challenge to explain just how an appeal to constitutive features of human agency figures into the accounts of normative entities, and in such a way that distinguishes constructivism from already existing general positions in practical or moral philosophy. I examine three constructivist views: compatibilist constructivism defended by Hilary Bok, and the constitutivist constructivism defended by Christine Korsgaard and by Sharon Street. What makes them all count as constructivist is a sort of procedural commitment, although as we will see the procedural dimensions of their views differ. And what makes Korsgaard and Street constructivist views count as constitutivists also differ in interesting ways. I argue that constitutivist versions of constructivism can be seen as a novel and distinctive form of antirealism in metaethics or metanormative studies. To do so, I ultimately return to Kant's works. I reject judgment-dependence as the primary way to understand Kant's own antirealism and as the best way to establish an antirealism for constitutivist constructivism as well, contrary to what the constitutivist constructivists that are the subject of this project argue. I argue that insofar as we accept Alexander Miller's three ways of being antirealist (2019), we can discern a novel fourth way: a non-error-theoretic, non-expressivist, non-idealist, and non-subjectivist style of non-realism that opposes robust realism in practical and moral philosophy by denying a rational will independence of normative truths, contra what Kant calls "heteronomy, " where the nature of normative truth must be understood in relation to the principles constitutive of the activities of the rational will

Keywords: Philosophy.
Advisor: Hills David James
Dannenberg Jorah
Wood Allen W.
Practicing human rights in the Arab world : international law in 20th century advocacy

This dissertation explores how several Arab NGOs in Morocco, Palestine, Egypt and Kuwait practiced human rights from the late 1970s to the early 1990s. Drawing on institutional archives and interviews, it argues that these organizations provide new insights into the history of human rights both regionally and internationally. Located in a region battered by colonialism, foreign exploitation, and domestic autocracy, they are a valuable entry-point for considering the universality of rights and the extent to which Cold War politics shaped grassroots advocacy. The division between political and civil rights, and economic, cultural and social rights—so salient on the international level—was of minimal importance in shaping human rights advocacy on the ground. Instead, NGOs embraced those rights which most directly spoke to their particular political challenges and prioritized the most egregious state practices. Human rights activists found synergy between rights and nationalism, Socialism, democracy, and constitutional monarchy. Rights were not a single paradigm for how to organize political life, but part of several different visions that arose in response to the aftermath of the loss of the 1967 war with Israel. The 1970s and 1980s were period of both continuity, as advocates drew on the existing content of recent international treaties, and innovation, as they transformed the law from a text to a shared practice of resistance

Keywords: History.
Advisor: Beinin Joel
Yaycioglu Ali
Martinez Jenny S.