430 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
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Taking shape: The data science of elastic shape analysis with practical applications
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.A mathematical curve can represent many different objects, both physical and abstract,
from the outline curve of an artefact in an image to the weight of growing animal to
the set of frequencies used in a sound. Regardless of these variations, the curves can
almost always vary non-linearly. One way to study shapes and their potential variations
is elastic shape analysis, a rich theory of which has developed over the past twenty years.
However, methods of elastic shape analysis are seldom utilized in practical applications
on real-world data, especially outside of the mathematical shape analysis community.
Our aim in this thesis is to explore some practical applications of elastic shape analysis.
To do this, we work with various types of shape data, the majority of which are based on
image datasets. As our focus is on two-dimensional curves, it is important to be able to
robustly extract contours from images, before we can apply elastic shape analysis tools.
In order to analyse the shapes in a dataset, we turn to methods of machine learning, to
investigate the applications of elastic shape analysis in classification.
In this thesis, we introduce an anthology of projects, in order to emphasise and under-
stand the potential of elastic shape analysis in practical applications. There are four main
projects in this thesis: (i) Classification of objects using outlines and the comparisons
between methods of elastic shape analysis, geometric morphometrics, and human experts,
with a focus on ancient Greek vases, (ii) Mussel species identification and a demonstra-
tion that shape may not be enough in some applications, (iii) A novel tool to monitor
the development of k Ì„ak Ì„ap Ì„o chicks, and (iv) Classifying individual kiwi based on acoustic
data from their calls.
By combining tools from computer vision and machine learning with methods of elastic
shape analysis, we introduce a practical framework for the application of elastic shape
analysis, through a data science lens
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
A Strong Composition Theorem for Junta Complexity and the Boosting of Property Testers
We prove a strong composition theorem for junta complexity and show how such
theorems can be used to generically boost the performance of property testers.
The -approximate junta complexity of a function is the
smallest integer such that is -close to a function that
depends only on variables. A strong composition theorem states that if
has large -approximate junta complexity, then has even
larger -approximate junta complexity, even for . We develop a fairly complete understanding of this behavior,
proving that the junta complexity of is characterized by that of
along with the multivariate noise sensitivity of . For the important
case of symmetric functions , we relate their multivariate noise sensitivity
to the simpler and well-studied case of univariate noise sensitivity.
We then show how strong composition theorems yield boosting algorithms for
property testers: with a strong composition theorem for any class of functions,
a large-distance tester for that class is immediately upgraded into one for
small distances. Combining our contributions yields a booster for junta
testers, and with it new implications for junta testing. This is the first
boosting-type result in property testing, and we hope that the connection to
composition theorems adds compelling motivation to the study of both topics.Comment: 44 pages, 1 figure, FOCS 202
Malleable zero-knowledge proofs and applications
In recent years, the field of privacy-preserving technologies has experienced considerable expansion, with zero-knowledge proofs (ZKPs) playing one of the most prominent roles.
Although ZKPs have been a well-established theoretical construct for three decades, recent efficiency improvements and novel privacy applications within decentralized finance have become the main drivers behind the surge of interest and investment in this area.
This momentum has subsequently sparked unprecedented technical advances.
Non-interactive ZKPs (NIZKs) are now regularly implemented across a variety of domains, encompassing, but not limited to, privacy-enabling cryptocurrencies, credential systems, voting, mixing, secure multi-party computation, and other cryptographic protocols.
This thesis, although covering several areas of ZKP technologies and their application, focuses on one important aspect of NIZKs, namely their malleability.
Malleability is a quality of a proof system that describes the potential for altering an already generated proof.
Different properties may be desired in different application contexts.
On the one end of the spectrum, non-malleability ensures proof immutability, an important requirement in scenarios such as prevention of replay attacks in anonymous cryptocurrencies.
At the other end, some NIZKs enable proof updatability, recursively and directly, a feature that is integral for a variety of contexts, such as private smart contracts, compact blockchains, ZK rollups, ZK virtual machines, and MPC protocols generally.
This work starts with a detailed analysis of the malleability and overarching security of a popular NIZK, known as Groth16.
Here we adopt a more definitional approach, studying certain properties of the proof system, and its setup ceremony, that are crucial for its precise modelling within bigger systems.
Subsequently, the work explores the malleability of transactions within a private cryptocurrency variant, where we show that relaxing non-malleability assumptions enables a functionality, specifically an atomic asset swap, that is useful for cryptocurrency applications.
The work culminates with a study of a less general, algebraic NIZK, and particularly its updatability properties, whose applicability we present within the context of ensuring privacy for regulatory compliance purposes
LIPIcs, Volume 274, ESA 2023, Complete Volume
LIPIcs, Volume 274, ESA 2023, Complete Volum
Tennyson's Figures of Repetition
This thesis argues that Tennyson’s uses of repetition can be seen not merely as a manifestation of his sometimes alleged ‘stupidity’ but as an embodiment of his continual self-questioning and self-criticism. To do this, I focus on five figures of repetition: memory/Memory (Chapter 1), mirror-images (Chapter 2), simile (Chapter 3), antithesis (Chapter 4), fama/Fama (Chapter 5). My first chapter begins by considering the way in which Tennyson’s act of recollection is accompanied by the idealisation of the past and the denigration of the present. It then sees the reverse of a recollection within Tennyson’s representation of Memory, and in his use of memory. My second chapter examines Tennyson’s descriptions of mirror-image, showing how this shadowy existence is not simply presented as an inferior reproduction of the original, but comes to assume its own substantiality. My third chapter shows how In Memoriam’s conflicting processes of unity and division are encapsulated in the relationship between the words in the rhetorical figure of the simile. It shows how the poem’s use of simile reveals the tension between the unitive and disjunctive tendencies of language itself, presenting the poem as a critique of the Romantic, metaphorical view of language. My fourth chapter shows how in Maud the speaker’s doubts about his control over the action are communicated through the antithetical repetition of the same verb in the two grammatical voices. My fifth chapter examines how in Idylls of the King Arthur’s authority, which is connected to Tennyson’s authority, is dependent upon repetitive and diffusive speech. It argues that such a derivation of authority from the diffusion of speech is registered in the semantic duplexities of the Latin word fama/Fama. My conclusion considers Tennyson’s posthumous fame as a kind of repetition in itself, examining the way T. S. Eliot remodels Tennyson’s homes in ‘East Coker’
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Computational Methods in Multi-Messenger Astrophysics using Gravitational Waves and High Energy Neutrinos
This dissertation seeks to describe advancements made in computational methods for multi-messenger astrophysics (MMA) using gravitational waves GW and neutrinos during Advanced LIGO (aLIGO)’s first through third observing runs (O1-O3) and, looking forward, to describe novel computational techniques suited to the challenges of both the burgeoning MMA field and high-performance computing as a whole.
The first two chapters provide an overview of MMA as it pertains to gravitational wave/high energy neutrino (GWHEN) searches, including a summary of expected astrophysical sources as well as GW, neutrino, and gamma-ray detectors used in their detection. These are followed in the third chapter by an in-depth discussion of LIGO’s timing system, particularly the diagnostic subsystem, describing both its role in MMA searches and the author’s contributions to the system itself.
The fourth chapter provides a detailed description of the Low-Latency Algorithm for Multi-messenger Astrophysics (LLAMA), the GWHEN pipeline developed by the author and used in O2 and O3. Relevant past multi-messenger searches are described first, followed by the O2 and O3 analysis methods, the pipeline’s performance, scientific results, and finally, an in-depth account of the library’s structure and functionality. In particular, the author’s high-performance multi-order coordinates (MOC) HEALPix image analysis library, HPMOC, is described. HPMOC increases performance of HEALPix image manipulations by several orders of magnitude vs. naive single-resolution approaches while presenting a simple high-level interface and should prove useful for diverse future MMA searches. The performance improvements it provides for LLAMA are also covered.
The final chapter of this dissertation builds on the approaches taken in developing HPMOC, presenting several novel methods for efficiently storing and analyzing large data sets, with applications to MMA and other data-intensive fields. A family of depth-first multi-resolution ordering of HEALPix images — DEPTH9, DEPTH19, and DEPTH40 — is defined, along with algorithms and use cases where it can improve on current approaches, including high-speed streaming calculations suitable for serverless compute or FPGAs.
For performance-constrained analyses on HEALPix data (e.g. image analysis in multi-messenger search pipelines) using SIMD processors, breadth-first data structures can provide short-circuiting calculations in a data-parallel way on compressed data; a simple compression method is described with application to further improving LLAMA performance.
A new storage scheme and associated algorithms for efficiently compressing and contracting tensors of varying sparsity is presented; these demuxed tensors (D-Tensors) have equivalent asymptotic time and space complexity to optimal representations of both dense and sparse matrices, and could be used as a universal drop-in replacement to reduce code complexity and developer effort while improving performance of existing non-optimized numerical code. Finally, the big bucket hash table (B-Table), a novel type of hash table making guarantees on data layout (vs. load factor), is described, along with optimizations it allows for (like hardware acceleration, online rebuilds, and hard realtime applications) that are not possible with existing hash table approaches. These innovations are presented in the hope that some will prove useful for improving future MMA searches and other data-intensive applications
Translating the poetry of Cécile Sauvage: love and creativity in practice
This project is composed of a critical discussion about translating the French writer Cécile Sauvage (1883-1927) and a creative translation of selected Sauvage poems into English. Informed by creative critical theories, this project examines the personal stakes residing within this academic framework. Chapter 1 takes up the concept of fannishness as a method of participating in a cultural product. I define fannishness as love for a text, imagine the translator as a fan, and analyze metaphors of spatial distance used to describe creation and criticism. In Chapter 2, I examine the reception of Sauvage’s poetry, arguing that the historical treatment of Sauvage as a ‘woman poet’ has implications for translation. In Chapter 3, I examine how feminist theorists have dealt with Sauvage; drawing upon feminist and queer theories of translation, I connect translation to violence and love. In Chapter 4, I describe my approach to translating Sauvage on the formal level, drawing upon Jean Boase-Beier and Clive Scott to argue that a successful translation is one that embraces the translator’s positioning and extends the source text’s existence in a new way. In Chapter 5, I suggest that anthologizing or editing Sauvage means rewriting her. As I recount my trip to Sauvage’s archives, I bridge translation and editing, arguing that a translation is an extension of a text’s genesis. Chapter 6 discusses the reasoning behind the form, content and presentation of my translated collection, A Sauvage Reader. The Reader follows, interspersed with poetic commentary and quoted intertexts. The six themes that organize the Reader connect to creative critical vocabulary and to metaphors of translation. I conclude that my translation has given Sauvage’s work a new narrative, chronicled a translator’s experience, and brought to Translation Studies a novel articulation of how translators, like scholars, acknowledge relations of partiality, or what I call love
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