VictorJuiz/thesis huggingface dataset:
Algebraic Geometry for Computer Vision

This thesis uses tools from algebraic geometry to solve problems about three-dimensional scene reconstruction. 3D reconstruction is a fundamental task in multiview geometry, a field of computer vision. Given images of a world scene, taken by cameras in unknown positions, how can we best build a 3D model for the scene? Novel results are obtained for various challenging minimal problems, which are important algorithmic routines in Random Sampling Consensus pipelines for reconstruction. These routines reduce overfitting when outliers are present in image data./nOur approach throughout is to formulate inverse problems as structured systems of polynomial equations, and then to exploit underlying geometry. We apply numerical algebraic geometry, commutative algebra and tropical geometry, and we derive new mathematical results in these fields. We present simulations on image data as well as an implementation of general-purpose homotopy-continuation software for implicitization in computational algebraic geometry./nChapter 1 introduces some relevant computer vision. Chapters 2 and 3 are devoted to the recovery of camera positions from images. We resolve an open problem concerning two calibrated cameras raised by Sameer Agarwal, a vision expert at Google Research, by using the algebraic theory of Ulrich sheaves. This gives a robust test for identifying outliers in terms of spectral gaps. Next, we quantify the algebraic complexity for notorious poorly understood cases for three calibrated cameras. This is achieved by formulating in terms of structured linear sections of an explicit moduli space and then computing via homotopy-continuation. In Chapter 4, a new framework for modeling image distortion is proposed, based on lifting algebraic varieties in projective space to varieties in other toric varieties. We check that our formulation leads to faster and more stable solvers than the state of the art. Lastly, Chapter 5 concludes by studying possible pictures of simple objects, as varieties inside products of projective planes. In particular, this dissertation exhibits that algebro-geometric methods can actually be useful in practical settings.

Advisor: Sturmfels, Bernd
The development and validation of a new coding system for dementia patient-caregiver dyads: the Dyadic Dementia Coding System

Dementia is a debilitating disease for the individuals who are afflicted, as well as the family members who care for them. Much research has focused on factors that characterize the symptoms and behaviors of the patient, the traits of the caregiver that enable them to be more or less resilient throughout caregiving, and, to a lesser degree, the qualities of the relationship between patients and caregivers. For the latter, research has focused on marital satisfaction, language use when communicating, and mutual gaze within dyads. However, the behaviors that emerge during interactions between dementia patients and caregivers have rarely been explored. Many dyadic behavioral coding systems are available and widely used, but all of these systems were developed with healthy couples and may therefore lack the ability to capture the nuances of behaviors that emerge during interactions between dementia patients and caregivers. The present study sought to develop a new dyadic behavioral coding system that would accurately capture the behaviors and symptoms of dementia patients and the behaviors and responses of caregivers, as demonstrated by acceptable reliability (inter-rater and split-half) and validity (construct, criterion, and incremental). The sample was composed of 35 patients with Alzheimer’s Disease, 35 patients with behavioral variant frontotemporal dementia, 19 control patients, and their spousal caregivers. The final coding system consisted of nine patient and eleven caregiver codes, which captured patient behavioral symptoms (e.g., inappropriate laughter for patients) and caregiver responses (e.g., guiding appraisal). Results indicated that the dyadic behavioral coding system demonstrated acceptable reliability and validity. In addition, the new coding system was able to distinguish between different kinds of dementia as well as identifying caregivers who are at greater risk of developing depression, above and beyond an existing, commonly used dyadic coding system. Implications of these findings for the development of interventions to improve caregivers’ mental health outcomes are discussed.

Advisor: Levenson, Robert W
Nonrelativistic Naturalness in Aristotelian Quantum Field Theories

Some of the most fundamental questions in theoretical physics can be formulated as puzzles of naturalness, such as the cosmological constant problem and the Higgs mass hierarchy problem. In condensed matter physics, the interpretation of the linear scaling of resistivity with temperature in the strange metal phase of high-temperature superconductors also arises as a naturalness puzzle. In this thesis, we explore the landscape of naturalness in nonrelativistic quantum field theories that exhibit anisotropic scaling in space and time. Such theories are referred to as the ``Aristotelian quantum field theories." In the simple case with scalars, we find that the constant shift symmetry is extended to a shift by a polynomial in spatial coordinates, which protects the technical naturalness of modes with a higher order dispersion. This discovery leads to a generalization of the relativistic Coleman-Hohenberg-Mermin-Wagner (CHMW) theorem to multicritical cases in lower critical dimension. By breaking the polynomial shift symmetries in a hierarchy, we find novel cascading phenomena with large natural hierarchies between the scales at which the values of z change, leading to an evasion of the "no-go" consequences of the relativistic CHMW theorem. Based on these formal developments, we propose potential applications both to the Higgs mass hierarchy problem and to the problem of linear resistivity in strange metals. Finally, encouraged by these nonrelativistic surprises that already arise in simple systems with scalars, we move on to more complicated systems with gauge symmetries. We study the quantization of Horava gravity in 2+1 dimensions and compute the anomalous dimension of the cosmological constant at one loop. However, nonrelativistic naturalness in gravity is still largely unexplored. Whether or not such nonrelativsitic twists have any implications for important naturalness puzzles, such as the cosmological constant problem, remains as an intriguing question.

Advisor: Horava, Petr
Characterizing the Role of Angiopoietin-like 4 in Energy Homeostasis

The lipoprotein lipase inhibitory function of Angiopoietin-like 4 (ANGPTL4) has been extensively characterized. The purpose of this research is to identify the domain of ANGPTL4 responsible for its lipolytic function and to characterize its physiological and metabolic effects. Also given its lipolytic function, I will try to identify a possible therapeutic role for ANGPTL4./nThe introduction outlines the members of the ANGPTL family of proteins. It reviews the physiological functions of ANGPTL4 in metabolism, inflammation, wound healing and angiogenesis. Finally, it examines adipocyte lipolysis and its role in energy expenditure./nThe first chapter addresses the in vivo effects of overexpression of the ANGPTL4 fibrinogen-like domain on adipose tissue lipolysis and energy expenditure. I hypothesize that the N-terminal coiled-coil domain (CCD) of ANGPTL4 was not required for its lipolytic function. Here I show that the FLD of ANGPTL4 alone stimulates adipocyte lipolysis via the cAMP-PKA pathway. Adenoviral overexpression of ANGPTL4 FLD in mice protects mice against high fat diet induced obesity and ectopic steatosis; increases energy expenditure by inducing beiging of white adipose tissue; and improves glucose homeostasis./nThe second chapter addresses the role of ANGPTL4 in glucose homeostasis and seeks to identify the domain responsible for the ANGPTL4-dependent improvement in glucose tolerance in mice. Here I demonstrate that overexpression of ANGTPL4 in mice on high fat diet housed at thermoneutrality and in mice on chow diet improves glucose tolerance by decreasing gluconeogenesis./nThe third chapter addresses the role of ANGPTL4 in the regulation of thermogenesis upon cold exposure. Mice lacking ANGPTL4 have lower body temperature and lower energy expenditure when housed at 4C, room temperature and thermoneutrality. In addition, mice deficient in ANGPTL4 have lower body temperature than wild-type counterparts./nOverall, this study has identified ANGPTL4 as a critical regulator of energy expenditure and as a potential therapeutic target.

Advisor: Wang, Jen-Chywan
Understanding Data Analysis Activity via Log Analysis

The study of user analysis behavior is of interest to the designers of analysis tools. Specific questions studied include: What types of tasks do users perform using this analysis tool? What approaches do users take to gain insights? What interface features help or hinder users in their work? What are the the distinguishing characteristics of different types of users? These questions are often investigated through controlled experiments, observational studies, user interviews, or surveys. An alternative avenue of investigation is to analyze the logs – the records of user activity – generated by analysis tools themselves. In this dissertation we present two case studies using log analysis to understand user behavior. In the first, we analyze records of user queries from Splunk, a system for log analysis, as well as a survey of Splunk users. In the second, we analyze detailed event logs and application state from Tableau, a system for visualizing relational data. We focus in particular on methods of identifying higher-level units of activity, which we refer to as tasks. We include a discussion of the particular challenges associated with collecting and analyzing log data from analysis systems. In addition to this discussion, our contributions include the description of two different approaches for identifying higher-level analysis activity from logs and a summary of the tasks represented in our datasets.

Advisor: Katz, Randy
Hearst, Marti
Phylogeography and population genetics of diving beetles in New Guinea

Predaceous diving beetles (Dytiscidae) are common inhabitants of both lentic and lotic freshwater systems worldwide. They have played a major role in our understanding of the relationship between habitat stability and evolution for dispersal propensity./nNumerous endemic diving beetles can be found in on the island of New Guinea. However, like most micro-fauna on remote islands, their evolutionary history and population ecology is largely unknown. In this series of studies, I use both traditional Sanger sequencing and next- generation sequencing techniques to explore the phylogenetic relationship of beetles in a genus as well as the population genetic patterns within a species.

Advisor: Roderick, George K
Skipping-oriented Data Design for Large-Scale Analytics

As data volumes continue to expand, analytics approaches that require exhaustively scanning data sets become untenable. For this reason, modern analytics systems employ data skipping techniques to avoid looking at large volumes of irrelevant data. By maintaining some metadata for each block of data, a query may skip a data block if the metadata indicates that the block does not contain relevant data. The effectiveness of data skipping, however, depends on how the underlying data are organized into blocks./nIn this dissertation, we propose a fine-grained data layout framework, called ``Generalized Skipping-Oriented Partitioning and Replication'' (GSOP-R), which aims to maximize query performance through aggressive data skipping. Based on observations of real-world analytics workloads, we find that the workload patterns can be summarized as a succinct set of features. The GSOP-R framework uses these features to transform the incoming data into a small set of feature vectors, and then performs clustering algorithms using the feature vectors instead of the actual data. A resulting GSOP-R layout scheme is highly flexible. For instance, it allows different columns to be horizontally partitioned in different ways and supports replication of only parts of rows or columns./nWe developed several designs for GSOP-R on Apache Spark and Apache Parquet and then evaluated their performance using two public benchmarks and several real-world workloads. Our results show that GSOP-R can reduce the amount of data scanned and improve end-to-end query response times over the state-of-the-art techniques by a factor of 2 to 9.

Advisor: Franklin, Michael J
Kierkegaard and the Funny

Abstract/nKierkegaard and the Funny/nby/nEric Linus Kaplan/nDoctor of Philosophy in Philosophy/nUniversity of California, Berkeley/nProfessor Alva Noë/nThis dissertation begins by addressing a puzzle that arises in academic analytic interpretations of Kierkegaard’s Concluding Unscientific Postscript. The puzzle arises when commentators try to paraphrase the book’s philosophical thesis “truth is subjectivity.” I resolve this puzzle by arguing that the motto “truth is subjectivity” is like a joke, and resists and invites paraphrase just as a joke does./nThe connection between joking and Kierkegaard’s philosophical practice is then deepened by giving a philosophical reconstruction of Kierkegaard's definition of joking as a way of responding to contradiction that is painless precisely because it sees the way out in mind. Kierkegaard’s account of joking and his account of his own philosophical project are used to mutually illuminate each other. The dissertation develops a phenomenology of retroactive temporality that explains how joking and subjective thinking work. I put forward an argument for why “existential humorism” is a valuable approach to life for Kierkegaard, but why it ultimately fails, and explain the relationship between comedy as a way of life and faith as a way of life, particularly as they both relate to risk./nIn the final chapter three peculiar features of Kierkegaard’s writing practice are addressed: his use of indirect communication, pseudonyms, and revocation. I explain the function of these methods to his philosophical project as I have described it in the previous chapters and conclude with a close reading of the graveyard scene in the Postscript and an analysis of how it serves to implicate the reader in existential thinking. Finally, I offer some reflections about the implications of Kierkegaard’s account of humor and subjective thinking for human self-understanding. I argue that an implication of Kierkegaard’s account is that philosophy is a risky, vulnerable, interpersonal activity, just as joking is.

Advisor: Noe, Alva
Dreyfus, Hubert L.
Cardiolipin in Barth Syndrome

Barth Syndrome (BTHS) is a rare genetic disorder caused by mutations in the gene that encodes tafazzin, a protein whose sole function is to remodel the mitochondrial phospholipid cardiolipin (CL). Despite comprising a small proportion of the body’s total phospholipid pool, the critical role CL plays in the structure and function of the mitochondrial inner membrane means that defects in CL composition lead to profound mitochondrial impairment. These mitochondrial defects, in turn, lead to the failure of high energy-demand systems, resulting in neutropenia, skeletal muscle weakness, and cardiomyopathy. While some researchers have suggested gene therapy or protein replacement as potential future treatments, it is conceivable that, if CL could be delivered to the defective mitochondria, the need for a functional tafazzin could be bypassed entirely. In the current study, we use the amphipathic plasma protein apolipoprotein A-I to solubilize CL into discoidal nanoparticles resembling HDL. These CL nanodisks (CLND) were incubated with a cell culture model of the neutropenia seen in BTHS. CL-ND treatment increased cellular CL levels and ameliorated the BTHS phenotype. To extend these findings to whole animals, a 10 week study was carried out using a mouse model of BTHS. However, at the end of the study, while the BTHS mice developed significant differences in CL composition characteristic of the disease, CL-ND treatment had no effect on CL content or composition. Thus, while CL-ND may eventually prove to be a useful therapy for BTHS, the current study highlights the difficulty of translating cell culture results to intact animals.

Advisor: Ryan, Robert O
Communication Avoidance for Algorithms with Sparse All-to-all Interactions

In parallel computing environments from multicore systems to cloud computers and supercomputers, data movement is the dominant cost in both running time and energy usage. Even worse, hardware trends suggest that the gap between computing and data movement, both in memory systems and interconnect networks, will continue to grow. Minimizing communication is therefore necessary in devising scalable parallel algorithms. This work discusses parallelizing kernels in applications ranging from chemistry and cosmology to machine learning./nWe have developed new communication-avoiding algorithms for problems with all-to-all interactions such as many-body and matrix computations, taking into account their sparsity patterns, either from cutoff distance, symmetry, or data sparsity. Our algorithms are communication-efficient (some are provably optimal) and scalable to tens of thousands of processors, exhibiting orders of magnitude speedup over more commonly used algorithms./nThese all-to-all computational patterns arise in scientific simulations and machine learning. The last part of the thesis will present a case study of communication-avoiding sparse-dense matrix multiplication as used in graphical model structure learning. The resulting high-performance sparse inverse covariance matrix estimation algorithm enables processing high-dimensional data with arbitrary underlying structures at a scale that was previously intractable, e.g., 1.28 million dimensions (over 800 billion parameters) in under 21 minutes on 24,576 cores of a Cray XC30. Our method is used to automatically estimate the underlying functional connectivity of the human brain from resting-state fMRI data. The results show good agreement with a state-of-the-art clustering, which used manual intervention, from the neuroscience literature.

Advisor: Yelick, Katherine A
Artificial Aliens: Reproductive Imaginations in German Culture

This dissertation, titled “Artificial Aliens: Reproductive Imaginations in German Culture,” studies how reproductive processes in biology and the arts evoke similar cultural anxieties, and how they, in turn, are shaped by these same fears. I view and investigate reproduction in biology and the arts as related processes, specifically those conducted via artificial means. My dissertation examines this relationship by tracing artificial aliens as a point of connection across disciplines, media, and periods. The figure of the artificial alien appears as artificial human, othered stranger, alien lifeform, and cinematic image. I develop my argument via several case studies, ranging from Weimar silent films such as Otto Rippert’s Homunculus (1916/1920) and Henrik Galeen’s Alraune (1927/1928) to Frank Schätzing’s science fiction bestseller Der Schwarm (2004) to Netflix’s original series Sense8 (2015-). I argue that there exists a complex dynamic between reproductive processes in biology and the arts and discourses on memory, identity, and media and its archaeology. This project thus contributes to existing research on the interplay between science and fiction. I argue that reproductive imaginations play a crucial role in self-conceptions of the human species. The (im)materiality of the cinematic image is key to rethinking the nature/culture divide. My project therefore highlights circulation and cross-fertilization between the sciences and the humanities.

Advisor: Göktürk, Deniz
Algorithmic Mechanism Design in Dynamic Environments

Over the past few decades, a new field has emerged from the interaction between Computer Science and Game Theory: Algorithmic Mechanism Design. The field has seen tremendous growth and has been extremely successful in tackling a wide variety of problems. Despite all this progress, the vast majority of the literature to date focuses on static, one-time decisions. In many situations of interest, however, this simplification is too far from reality. For example, a search engine must choose how to allocate its advertising inventory in the face of changing search queries and advertiser budgets. In a cloud computing center resources need to be dynamically reallocated in response to the arrival of new computational tasks of varying priority. This thesis explores the interplay of incentives and the dynamic nature of decision-making in the design of efficient mechanisms./nIn the first part of this thesis we study Dynamic Auction Design. We introduce a novel class of dynamic auction problems in which a monopolist is selling $m$ items in $m$ consecutive stages to $n$ buyers./nWe study these problem from several different perspectives:/n{\em Computational Complexity}, i.e. how hard is it to compute the optimal auction, {\em Competition Complexity}, i.e. how much additional competition is necessary for a standard Vickrey (second-price) auction at every stage to extract more revenue than the optimal auction, {\em Power of Adaptivity}, i.e. what is the revenue gap between adaptive and non-adaptive auctions,/n{\em Power of Commitment}, i.e. what happens if the seller cannot commit to her future behavior./nIn the second part of this thesis we study Dynamic Fair Division. We introduce a novel class of resource allocation problems in which resources are shared between agents dynamically arriving and departing over time./nFor a single resource, when $n$ agents are present, there is only one truly ``fair'' allocation: each agent receives $1/n$ of the resource. Implementing this static solution over time is notoriously impractical. There are too many disruptions to existing allocations: for a new agent to get her fair share, all other agents must give up a small piece. What if, at every $c$ arrivals we could only reclaim resources from a fixed number of agents $d$? We provide non-wasteful such algorithms that are almost optimal with respect to fairness, even for multiple, heterogeneous resources.

Advisor: Papadimitriou, Christos