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 34 for “"top-k"”.
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Top-k Semantic Caching
… of this thesis is the intelligent caching of top-k queries in an environment with high latency and low throughput. In such an environment, caching can be used to reduce network traffic and improve response time. Slow database connections of mobile devices and to databases, which have been …
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Unstable Modules with Only the Top k Steenrod Operations
… an abelian category of unstable modules with the top k Steenrod operations at the prime 2. We show that this category has homological dimension at most k. We establish forgetful functors, suspension functors, loop functors and Frobenius functors between such modules. The forgetful functors induce …
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Portfolio Optimization Using Financial Chaos Index and Time-Homogeneous Top-K Ranking
… us to tackle the problem of time-dependent top-K ranking. More specifically, given N items, all having positive latent strengths, top-K ranking problem aims to identify the K items receiving the highest ranks based on partially revealed comparisons among the items. This problem has been …
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Efficient computation of advanced skyline queries.
… cube computation and its analysis; and (3) top-k most representative skyline. To tackle the problem of online skyline computation, we develop a novel framework which converts more expensive multiple dimensional skyline computation to stabbing queries in 1-dimensional space. Based on this …
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De Novo Protein Structure Modeling and Energy Function Design
… of the interaction between residues.</p> <p>The top-k search algorithm was optimized to be used for proteins containing both α-helices and β-sheets. Secondary structure elements (SSEs) are visible in cryo-electron microscopy (cryo-EM) density maps. Combined with the SSEs predicted in a protein …
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Efficient Data Modelling, Indexing and Processing in Large Datasets
… we study the problem of continuously updating top-k messages with the highest ranks, each of which contains all the requested keywords when the rank of a message calculates based on freshness and distance to query’s location. Since new incoming messages are arriving all the time and the score …
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In the Shadow of Prompts: Adversarial Attacks and Model Cloning in Large Language Models
… interfaces (APIs) that still expose full or top-k logits and lack mature safeguards, they present a serious, often overlooked attack surface. Earlier work has shown how to rebuild the output projection layer or distill surface behavior, but no attack has produced a deployable clone within a …
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Unveiling Phenotype–Genotype Interplay with Deep Learning Foundation Models for scRNA-seq: A Quantitative Perspective
… relationship. First, we implement a top-k classification and entropy evaluation pipeline to serve as a primary validation framework. Our results demonstrate that the pretrained PolyGene [1] is robust in top-k classification metrics and provides meaningful insights into the entropy …
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Integrating Similarity Based Retrieval and Query Refinement in Databases
… need. The semantics of this domain favor a ""top-k"" retrieval approach where we only seek the best matching results for a query. We therefore developed for each of the two areas (similarity search and query refinement) several techniques to efficiently process queries. For similarity queries …
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IVIS: Search and visualization on heterogeneous information networks
… more intuitive and knowledgeable than the simple top-k blue links from traditional search engines, and bring more meaningful structural results with correlated entities. We also investigate the ranking algorithm, and we show that the personalized PageRank and proposed Hetero-personalized PageRank …
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Efficient Algorithms for Querying Large and Uncertain Data
… summarization of the entire dataset so that Top-$k$ or user preference queries are answered efficiently with high quality guarantees by looking only in the data summary.</p><p>Such a summary can also be used in multi-criteria decision problems.</p><p>Furthermore, near-linear space indexes are …
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Efficient coordinate descent for ranking with domination loss
… when rated by average precision and precision at top k. It does not train as quickly as online algorithms, but offers extensions to multiple layers, and perhaps most importantly, can be used to produce extremely sparse weight vectors. When trained with feature induction, it achieves similarly …
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Outlier detection for information networks
… query, the aim is to allow the user to find top-K ranked matches for the query in the network. Matches are ranked based on the rare and surprising associations (expressed as edges) within them. My work focuses on outlier detection with respect to two main kinds of queries: clique queries and …
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Architectural support for commutativity in hardware speculation
… as counter increments, priority updates, and top-K set insertions. As a result, at 128 cores on full applications, CommTM outperforms a conventional eager-lazy HTM by up to 3.4x and reduces or eliminates aborts.
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Keyword-based object search and exploration in multidimensional text databases
… and materialization strategies for ranking top-k dimensions and cells. Finally, extensive experiments on real datasets demonstrate the efficiency and effectiveness of our approach.
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Data-driven transfer optimizations for big data in the industrial internet of things
… case study, an IIoT application identifies the top-k most relevant objects (e.g., machine failures) across multiple industrial facilities. We introduce a new fixed-phase distributed top-k algorithm. This algorithm uses fewer phases than related work while simultaneously reducing the data …
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Choice modeling and recommendation optimization in presence of context effects
… when the input data is featurized. We study the top-$K$ retrieval problem which focuses on finding $K$ relevant products/documents for a given query. We train a featurized estimator that can measure the context effects among the objects through mapping their features to contextual interaction …
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Query selection in Deep Web Crawling
… rank the matched documents and return only the top k documents. This thesis shows that we need to use queries whose size is commensurate with k, and experiments with several query size estimation methods.
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Motif Mining On Structured And Semi-structured Biological Data
… Despite the considerateeffort put in this topic, it remains a challenging and difficult problem.There are several advances in biology such that the data is structured (graphs)and semi-structured (sequences).A challenge of motif mining in sequences is the existence of variationsincluding …
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Reducing Global Memory Accesses in DNN Training using Structured Weight Masking
… masking based on L2 norm magnitude and top-k selection was developed and evaluated on the CIFAR-10 dataset. The study systematically varied block sizes and sparsity ratios, analyzing the impact on classification accuracy, theoretical computational cost (FLOPs), and theoretical memory …
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