Essays about: "Stochastic"
Showing result 1 - 5 of 717 essays containing the word Stochastic.
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1. Feature Selection for Microarray Data via Stochastic Approximation
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : This thesis explores the challenge of feature selection (FS) in machine learning, which involves reducing the dimensionality of data. The selection of a relevant subset of features from a larger pool has demonstrated its effectiveness in enhancing the performance of various machine learning algorithms. READ MORE
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2. A temporal Hawkes process model for shooting occurrences in Sweden
University essay from Lunds universitet/Statistiska institutionenAbstract : The Hawkes process, also referred to as a self-exciting point process, is a class of point processes where the intensity is conditioned on previous events. More specifically, an event occurrence excites the process, temporarily increasing the probability of more events occurring. READ MORE
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3. Geometry of high dimensional Gaussian data
University essay from Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakultetenAbstract : Collected data may simultaneously be of low sample size and high dimension. Such data exhibit some geometric regularities consisting of a single observation being a rotation on a sphere, and a pair of observations being orthogonal. This thesis investigates these geometric properties in some detail. READ MORE
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4. Variational AutoEncoders and Differential Privacy : balancing data synthesis and privacy constraints
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis investigates the effectiveness of Tabular Variational Auto Encoders (TVAEs) in generating high-quality synthetic tabular data and assesses their compliance with differential privacy principles. The study shows that while TVAEs are better than VAEs at generating synthetic data that faithfully reproduces the distribution of real data as measured by the Synthetic Data Vault (SDV) metrics, the latter does not guarantee that the synthetic data is up to the task in practical industrial applications. READ MORE
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5. Predicting Electricity Consumption with ARIMA and Recurrent Neural Networks
University essay from Uppsala universitet/Statistiska institutionenAbstract : Due to the growing share of renewable energy in countries' power systems, the need for precise forecasting of electricity consumption will increase. This paper considers two different approaches to time series forecasting, autoregressive moving average (ARMA) models and recurrent neural networks (RNNs). READ MORE