Essays about: "representation learning"
Showing result 11 - 15 of 389 essays containing the words representation learning.
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11. Domain Knowledge and Representation Learning for Centroid Initialization in Text Clustering with k-Means : An exploratory study
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Text clustering is a problem where texts are partitioned into homogeneous clusters, such as partitioning them based on their sentiment value. Two techniques to address the problem are representation learning, in particular language representation models, and clustering algorithms. READ MORE
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12. Detection of insurance fraud using NLP and ML
University essay from Lunds universitet/Matematisk statistikAbstract : Machine-Learning can sometimes see things we as humans can not. In this thesis we evaluated three different Natural Language Procces-techniques: BERT, word2vec and linguistic analysis (UDPipe), on their performance in detecting insurance fraud based on transcribed audio from phone calls (referred to as audio data) and written text (referred to as text-form data), related to insurance claims. READ MORE
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13. Analysis of speaking time and content of the various debates of the presidential campaign : Automated AI analysis of speech time and content of presidential debates based on the audio using speaker detection and topic detection
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The field of artificial intelligence (AI) has grown rapidly in recent years and its applications are becoming more widespread in various fields, including politics. In particular, presidential debates have become a crucial aspect of election campaigns and it is important to analyze the information exchanged in these debates in an objective way to let voters choose without being influenced by biased data. READ MORE
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14. On Linear Mode Connectivity up to Permutation of Hidden Neurons in Neural Network : When does Weight Averaging work?
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Neural networks trained using gradient-based optimization methods exhibit a surprising phenomenon known as mode connectivity, where two independently trained network weights are not isolated low loss minima in the parameter space. Instead, they can be connected by simple curves along which the loss remains low. READ MORE
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15. Football Trajectory Modeling Using Masked Autoencoders : Using Masked Autoencoder for Anomaly Detection and Correction for Football Trajectories
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Football trajectory modeling is a powerful tool for predicting and evaluating the movement of a football and its dynamics. Masked autoencoders are scalable self-supervised learners used for representation learning of partially observable data. READ MORE
