Essays about: "dimensionality reduction"

Showing result 1 - 5 of 83 essays containing the words dimensionality reduction.

1. 1. Towards topology-aware Variational Auto-Encoders : from InvMap-VAE to Witness Simplicial VAE

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Aniss Aiman Medbouhi; [2022]
   Keywords : Variational Auto-Encoder; Nonlinear dimensionality reduction; Generative model; Inverse projection; Computational topology; Algorithmic topology; Topological Data Analysis; Data visualisation; Unsupervised representation learning; Topological machine learning; Betti number; Simplicial complex; Witness complex; Simplicial map; Simplicial regularization.; Variations autokodare; Ickelinjär dimensionalitetsreducering; Generativ modell; Invers projektion; Beräkningstopologi; Algoritmisk topologi; Topologisk Data Analys; Datavisualisering; Oövervakat representationsinlärning; Topologisk maskininlärning; Betti-nummer; Simplicielt komplex; Vittneskomplex; Simpliciel avbildning; Simpliciel regularisering.;

   Abstract : Variational Auto-Encoders (VAEs) are one of the most famous deep generative models. After showing that standard VAEs may not preserve the topology, that is the shape of the data, between the input and the latent space, we tried to modify them so that the topology is preserved. READ MORE

3. 2. Organization of Electronic Dance Music by Dimensionality Reduction

   University essay from Umeå universitet/Institutionen för datavetenskap

   Author : Victor Tideman; [2022]
   Keywords : Dimensionality Reduction; Digital Signal Processing; Similarity; Music;

   Abstract : This thesis aims to produce a similarity metric for tracks of the genre: Electronic Dance Music, by taking a high-dimensional data representation of each track and then project it to a low-dimensional embedded space (2D and 3D) by applying two Dimensionality Reduction (DR) techniques called t-distributed stochastic neighbor embedding (t-SNE) and Pairwise Controlled Manifold Approximation (PaCMAP). A content-based approach is taken to identify similarity, which is defined as the distances between points in the embedded space. READ MORE

4. 3. Accelerating MCR-ALS decomposition of hyperspectral images using k-means clustering

   University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik

   Author : Eric Kull; [2022]
   Keywords : k-means; clustering; MCR-ALS; hyperspectral image; Physics and Astronomy;

   Abstract : A hyperspectral image may be decomposed into component spectra and their distri- bution in the image to simplify analysis by revealing underlying patterns and reducing the dimensionality of the image; this may be achieved by the algorithm MCR-ALS. However, the algorithm is time consuming, but could be accelerated by a data re- duction. READ MORE

5. 4. Autoencoder Compression in High Energy Physics

   University essay from Lunds universitet/Partikelfysik; Lunds universitet/Fysiska institutionen; Lunds universitet/Lunds Tekniska Högskola

   Author : Sten Åstrand; [2022]
   Keywords : High energy physics; LHC; ATLAS; hadron jet; machine learning; autoencoder; dimensionality reduction; artificial intelligence; data compression; Physics and Astronomy;

   Abstract : Situated in Geneva, Switzerland, the Large Hadron Collider is largest particle accelerator in the world, and as such, its operation carries with it some of the greatest technical challenges ever faced. Among them are the huge demands put on data storage capacity by experiments in particle physics, both in terms of rate and volume of data. READ MORE

6. 5. ML-Aided Cross-Band Channel Prediction in MIMO Systems

   University essay from Linköpings universitet/Statistik och maskininlärning

   Author : Alejo Pérez Gómez; [2022]
   Keywords : MIMO; Deep Learning; Machine Learning; Probabilistic Principal Component Analysis; Variational Autoencoder;

   Abstract : Wireless communications technologies have experienced an exponential development during the last decades. 5G is a prominent exponent whose one of its crucial component is the Massive MIMO technology. READ MORE