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 13 of 13 for “"Coresets"”.
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Bayesian coresets: Revisiting the nonconvex optimization perspective
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms
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GPSZip : semantic representation and compression system for GPS using coresets
… improve efficiency and scalability, we utilize 2 coresets: we formalize the coreset for 1-segment and apply our system on a small k-segment coreset of the data rather than the original data. The compressed trajectory compresses the original sensor stream and approximates its likelihood up to a …
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Efficient semantic retrieval on K-segment coresets of user videos
… compression method, which uses k-segment mean coresets to represent the video data using fewer frames while preserving the information content in the original data set. The system then uses a state-of-the-art object detector to analyze and detect objects in the reduced data. The objects and …
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Machine learning and coresets for automated real-time data segmentation and summarization
… science, robotics, and medicine, and show how coresets can help to overcome these challenges and enable us to build several practical systems that meet these specifications. We propose a theoretical framework for constructing several coreset algorithms that efficiently compress the data while …
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Algorithms and Analysis for Multi-Category Classification
… for learning maximum margin classifiers using coresets to find provably approximate solution to maximum margin linear separating hyperplane. Then, using the constraint classification framework, this algorithm applies directly to all of the previously mentioned complex-output domains. In …
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Small and Stable Descriptors of Distributions for Geometric Statistical Problems
… by a parameter ε. Two examples of coresets are ε-samples and ε-kernels. An ε-sample can estimate the density of a point set in any range from a geometric family of ranges (e.g., disks, axis-aligned rectangles). An ε-kernel approximates the width of a …
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Learning with high dimensional data and preprocessing in non-stationary environments
… representations can also be obtained by creating coresets. Thus, the final Chapter provides techniques which use coresets to maintain a Minimum Enclos- ing Ball in stream settings. These methods have the advantage to also work on non-linear data by choosing a suitable kernel. Specifically, a …
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Scalable Methodologies for Optimizing Over Probability Distributions
… of mean-zero kernels—to generate high-quality coresets from millions of biased samples, obtaining better-than-i.i.d. unbiased coresets. The second part transitions to optimizing over continuous distributions through neural network parameterization, enabling the generation of endless streams of …
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Combinatorial Methods in Statistics
… the fundamental statistical limits of coresets, a popular framework for obtaining algorithmic speedups by replacing a large dataset with a representative subset. In the following chapter, motivated by the problem of fast evaluation of kernel density estimators, we demonstrate how a …
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A generalized (k, m)-segment mean algorithm for long term modeling of traversable environments
… speed is greatly improved by the use of lossless coresets during the iterative update step, as they can be calculated in constant amortized time to perform operations with otherwise linear runtimes. We evaluate the algorithm for two types of data, GPS points and video feature vectors, on several …
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Private k-means clustering : algorithms and applications
… This thesis describes the construction of small coresets for computing k-means clustering of a set of points while preserving differential privacy. As a result, it gives the first 𝑘-means clustering algorithm that is both differentially private, and has an approximation error that depends …
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Sublinear algorithms for massive data problems
… problems. We introduce the notion of Composable Coresets, defined as small summaries of multiple data sets that can be aggregated together to summarize the whole data. We show how to compute such summaries for several clustering problems, and at the same time, demonstrate that no such summaries …
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Data Summarizations for Scalable, Robust and Privacy-Aware Learning in High Dimensions
… via learnable weighted pseudodata, termed pseudocoresets. We show that the use of pseudodata enables overcoming the constraints on minimum summary size for given approximation quality, that are imposed on all existing Bayesian coreset constructions due to data dimensionality. Moreover, it allows …