Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 26 for “"Nearest-Neighbor Search"”.
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Nearest neighbor search for cyro-electron microscopy images
… microscopy (EM) technology enables researchers to determine the structure of a molecule at a much higher resolution than ever before. The single particle reconstruction (SPR) is one of the most widespread techniques used to reconstruct the 3D model of a molecule from its large set of …
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Large Scale Nearest Neighbor Search - Theories, Algorithms, and Applications
… and so on. On these large scale data sets, nearest neighbor search is fundamental for lots of applications including content based search/retrieval, recommendation, clustering, graph and social network research, as well as many other machine learning and data mining problems. Exhaustive …
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Efficient nearest-neighbor search algorithms for sub-Riemannian geometries
… been at the core of a significant amount of research in the past decades and it has recently gained traction outside academia with the rise of commercial interest in self-driving cars and autonomous aerial vehicles. Among the leading algorithms to tackle the problem are sampling-based planners, …
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Nearest neighbor search : the old, the new, and the impossible
… for dealing with massive dataset is the Nearest Neighbor (NN) problem. In the NN problem, the goal is to preprocess a set of objects, so that later, given a query object, one can find efficiently the data object most similar to the query. This problem has a broad set of applications in …
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Understanding Indexing Efficiency for Approximate Nearest Neighbor Search in High-dimensional Vector Databases
… for many important online services, including search, eCommerce, and recommendation systems. In a vector database, the major operation is to search the 𝑘 closest vectors to a given query vector, known as 𝑘-Nearest-Neighbor (𝑘-NN) search. Due to massive data scale in practice, Approximate …
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Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations
Graph-based approaches to nearest neighbor search are popular and powerful tools for handling large datasets in practice, but they have limited theoretical guarantees. We study the worst-case performance of recent graph-based approximate nearest neighbor search algorithms, such as HNSW, NSG and …
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Private Similarity Search with Sublinear Communication
Nearest neighbor search is a fundamental building-block for a wide range of applications. A privacy-preserving protocol for nearest neighbor search involves a set of clients who send queries to a remote database. Each client retrieves the nearest neighbor(s) to its query in the database without …
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Parallel Algorithms, Optimizations, and Benchmarks for Metric and Graph Clustering
… expected to perform numerous similarity searches, as clustering entails grouping similar objects together. Although many algorithms have been designed for nearest neighbor search, many clustering algorithms require customized nearest neighbor search with special constraints, so we cannot …
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Algorithms above the noise floor
… methods like stochastic gradient descent. And in nearest neighbor search, a variety of approximation algorithms works remarkably well despite the "curse of dimensionality". In this thesis, we study this phenomenon in the context of three fundamental algorithmic problems arising in the data …
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On the use of locality aware distributed hash tables for homology searches over voluminous biological sequence data
… routines such as DNA and protein homology searches; these must also preferably be done in real-time. This thesis proposes a scalable and similarity-aware distributed storage framework, Mendel, that enables retrieval of biologically significant DNA and protein alignments against a voluminous …
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High-dimensional indexing methods utilizing clustering and dimensionality reduction
… the prevalence of a new paradigm for similarity search. These applications include multimedia databases, medical imaging databases, time series databases, DNA and protein sequence databases, and many others. Features of data objects are extracted and transformed into high-dimensional data points. …
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Large-Scale Machine Learning for Classification and Search
… for the purpose of making classification and nearest neighbor search practical on gigantic databases. Our first approach is to explore data graphs to aid classification and nearest neighbor search. A graph offers an attractive way of representing data and discovering the essential information …
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Multi-Satellite Remote Sensing of Land-Atmosphere Interactions: Advanced Data-Driven Methodologies for Passive Microwave Retrievals of Flood and Precipitation
… responses. The proposed approach relies on a nearest-neighbor search based on a weighted distance metric and a modern sparsity-promoting inversion method using observations from optical, short-infrared, and microwave bands, thereby allowing the detection under all-sky (clear and cloudy) …
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Supplementing Localization Algorithms for Indoor Footsteps
… learning approach is also explored using a nearest neighbor search. Additionally, a novel instrumentation method is designed based on a multi-point coupling approach that provides directional inference from a single point of measurement. This work contributes to solving the indoor footstep …
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Predicting prescription patterns
… a new nonlinear local algorithm based on nearest neighbor search. In analyzing the database the drug patterns were found to be diverse and over 30% of the patients were unique, in the sense that no other patient had been prescribed the same set of active ingredients. In spite of this …
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WACO: Learning workload-aware co-optimization of the format and schedule of a sparse tensor program
… template. In addition, within the enormous search space of co-optimization, our novel search strategy, an approximate nearest neighbor search, efficiently and accurately retrieves the best format and schedule for a given sparsity pattern. We evaluate WACO for four different algorithms (SpMV, …
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Graph-based Vector Search Algorithms for Retrieval-Augmented AI Systems
… vector embeddings and leveraging approximate nearest neighbor search (ANNS) have thus become an important data processing primitive in AI systems following the introduction of retrievel-augmented generation (RAG). However, the complexity of tasks these AI systems aim to solve introduces …
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Modeling Shape, Appearance and Motion for Human Movement Analysis
… combine them with appearance-based distances for nearest neighbor classification. We evaluated the approach on videos of 61 individuals under significant illumination and viewpoint changes. Fourth, we describe a prototype-based approach to action recognition. During training, a set of action …
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Geometric Algorithms and Data Structures for Simulating Diffusion Limited Reactions
… up step (3). The main contribution of this research is the development of an efficient and effective kinetic Monte Carlo (KMC) algorithm for simulating diffusion-limited chemical reactions in the context of radiation therapy. The central problem studied is - given n particles distributed among …
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