11 research outputs found

    Data Representation for Learning and Information Fusion in Bioinformatics

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    This thesis deals with the rigorous application of nonlinear dimension reduction and data organization techniques to biomedical data analysis. The Laplacian Eigenmaps algorithm is representative of these methods and has been widely applied in manifold learning and related areas. While their asymptotic manifold recovery behavior has been well-characterized, the clustering properties of Laplacian embeddings with finite data are largely motivated by heuristic arguments. We develop a precise bound, characterizing cluster structure preservation under Laplacian embeddings. From this foundation, we introduce flexible and mathematically well-founded approaches for information fusion and feature representation. These methods are applied to three substantial case studies in bioinformatics, illustrating their capacity to extract scientifically valuable information from complex data

    Non-acyclicity of coset lattices and generation of finite groups

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    Publications of the Jet Propulsion Laboratory, 1978

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    This bibliography cites 958 externally distributed technical papers released during calendar year 1978, that resulted from scientific and engineering work performed, or managed, by the Jet Propulsion Laboratory. The publications are indexed by author, subject, publication type and number. A descriptive entry appears under the name of each author of each publication; an abstract is included with the entry for the primary (first-listed) author

    Cumulative index to NASA Tech Briefs, 1986-1990, volumes 10-14

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    Tech Briefs are short announcements of new technology derived from the R&D activities of the National Aeronautics and Space Administration. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This cumulative index of Tech Briefs contains abstracts and four indexes (subject, personal author, originating center, and Tech Brief number) and covers the period 1986 to 1990. The abstract section is organized by the following subject categories: electronic components and circuits, electronic systems, physical sciences, materials, computer programs, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

    Convex reconstruction from structured measurements

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    Convex signal reconstruction is the art of solving ill-posed inverse problems via convex optimization. It is applicable to a great number of problems from engineering, signal analysis, quantum mechanics and many more. The most prominent example is compressed sensing, where one aims at reconstructing sparse vectors from an under-determined set of linear measurements. In many cases, one can prove rigorous performance guarantees for these convex algorithms. The combination of practical importance and theoretical tractability has directed a significant amount of attention to this young field of applied mathematics. However, rigorous proofs are usually only available for certain "generic cases"---for instance situations, where all measurements are represented by random Gaussian vectors. The focus of this thesis is to overcome this drawback by devising mathematical proof techniques can be applied to more "structured" measurements. Here, structure can have various meanings. E.g. it could refer to the type of measurements that occur in a given concrete application. Or, more abstractly, structure in the sense that a measurement ensemble is small and exhibits rich geometric features. The main focus of this thesis is phase retrieval: The problem of inferring phase information from amplitude measurements. This task is ubiquitous in, for instance, in crystallography, astronomy and diffraction imaging. Throughout this project, a series of increasingly better convex reconstruction guarantees have been established. On the one hand, we improved results for certain measurement models that mimic typical experimental setups in diffraction imaging. On the other hand, we identified spherical t-designs as a general purpose tool for the derandomization of data recovery schemes. Loosely speaking, a t-design is a finite configuration of vectors that is "evenly distributed" in the sense that it reproduces the first 2t moments of the uniform measure. Such configurations have been studied, for instance, in algebraic combinatorics, coding theory, and quantum information. We have shown that already spherical 4-designs allow for proving close-to-optimal convex reconstruction guarantees for phase retrieval. The success of this program depends on explicit constructions of spherical t-designs. In this regard, we have studied the design properties of stabilizer states. These are configurations of vectors that feature prominently in quantum information theory. Mathematically, they can be related to objects in discrete symplectic vector spaces---a structure we use heavily. We have shown that these vectors form a spherical 3-design and are, in some sense, close to a spherical 4-design. Putting these efforts together, we establish tight bounds on phase retrieval from stabilizer measurements. While working on the derandomization of phase retrieval, I obtained a number of results on other convex signal reconstruction problems. These include compressed sensing from anisotropic measurements, non-negative compressed sensing in the presence of noise and identifying improved convex regularizers for low rank matrix reconstruction. Going even further, the mathematical methods I used to tackle ill-posed inverse problems can be applied to a plethora of problems from quantum information theory. In particular, the causal structure behind Bell inequalities, new ways to compare experiments to fault-tolerance thresholds in quantum error correction, a novel benchmark for quantum state tomography via Bayesian estimation, and the task of distinguishing quantum states

    Emergent Design

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    Explorations in Systems Phenomenology in Relation to Ontology, Hermeneutics and the Meta-dialectics of Design SYNOPSIS A Phenomenological Analysis of Emergent Design is performed based on the foundations of General Schemas Theory. The concept of Sign Engineering is explored in terms of Hermeneutics, Dialectics, and Ontology in order to define Emergent Systems and Metasystems Engineering based on the concept of Meta-dialectics. ABSTRACT Phenomenology, Ontology, Hermeneutics, and Dialectics will dominate our inquiry into the nature of the Emergent Design of the System and its inverse dual, the Meta-system. This is an speculative dissertation that attempts to produce a philosophical, mathematical, and theoretical view of the nature of Systems Engineering Design. Emergent System Design, i.e., the design of yet unheard of and/or hitherto non-existent Systems and Metasystems is the focus. This study is a frontal assault on the hard problem of explaining how Engineering produces new things, rather than a repetition or reordering of concepts that already exist. In this work the philosophies of E. Husserl, A. Gurwitsch, M. Heidegger, J. Derrida, G. Deleuze, A. Badiou, G. Hegel, I. Kant and other Continental Philosophers are brought to bear on different aspects of how new technological systems come into existence through the midwifery of Systems Engineering. Sign Engineering is singled out as the most important aspect of Systems Engineering. We will build on the work of Pieter Wisse and extend his theory of Sign Engineering to define Meta-dialectics in the form of Quadralectics and then Pentalectics. Along the way the various ontological levels of Being are explored in conjunction with the discovery that the Quadralectic is related to the possibility of design primarily at the Third Meta-level of Being, called Hyper Being. Design Process is dependent upon the emergent possibilities that appear in Hyper Being. Hyper Being, termed by Heidegger as Being (Being crossed-out) and termed by Derrida as Differance, also appears as the widest space within the Design Field at the third meta-level of Being and therefore provides the most leverage that is needed to produce emergent effects. Hyper Being is where possibilities appear within our worldview. Possibility is necessary for emergent events to occur. Hyper Being possibilities are extended by Wild Being propensities to allow the embodiment of new things. We discuss how this philosophical background relates to meta-methods such as the Gurevich Abstract State Machine and the Wisse Metapattern methods, as well as real-time architectural design methods as described in the Integral Software Engineering Methodology. One aim of this research is to find the foundation for extending the ISEM methodology to become a general purpose Systems Design Methodology. Our purpose is also to bring these philosophical considerations into the practical realm by examining P. Bourdieu’s ideas on the relationship between theoretical and practical reason and M. de Certeau’s ideas on practice. The relationship between design and implementation is seen in terms of the Set/Mass conceptual opposition. General Schemas Theory is used as a way of critiquing the dependence of Set based mathematics as a basis for Design. The dissertation delineates a new foundation for Systems Engineering as Emergent Engineering based on General Schemas Theory, and provides an advanced theory of Design based on the understanding of the meta-levels of Being, particularly focusing upon the relationship between Hyper Being and Wild Being in the context of Pure and Process Being
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