Category
Dimensionality reduction
Related publications (777)
Environment rather than breed or body site shapes the skin bacterial community of healthy sheep as revealed by metabarcoding
Christof Holliger, Alexander Mathis, Emmanuelle Rohrbach, Laetitia Janine Andrée Cardona
Background: The skin is inhabited by a variety of micro-organisms, with bacteria representing the predominant taxon of the skin microbiome. In sheep, the skin bacterial community of healthy animals has been addressed in few studies, only with culture-based ...
2023End-to-end kernel learning via generative random Fourier features
Random Fourier features (RFFs) provide a promising way for kernel learning in a spectral case. Current RFFs-based kernel learning methods usually work in a two-stage way. In the first-stage process, learn-ing an optimal feature map is often formulated as a ...
ELSEVIER SCI LTD2023Dimensionality reduction of time-series data, and systems and devices that use the resultant embeddings
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for dimensionality reduction of time-series using contrastive learning. A method can include receiving multidimensional input time series data that includes ...
2023Improving K-means Clustering Using Speculation
Anastasia Ailamaki, Viktor Sanca, Eleni Zapridou, Stefan Igescu
K-means is one of the fundamental unsupervised data clustering and machine learning methods. It has been well studied over the years: parallelized, approximated, and optimized for different cases and applications. With increasingly higher parallelism leadi ...
2023The Cerebellum and Cognitive Function: Anatomical Evidence from a Transdiagnostic Sample
Farnaz Delavari, Charles Laidi
Multiple lines of evidence across human functional, lesion, and animal data point to a cerebellar role, in particular of crus I, crus II, and lobule VIIB, in cognitive function. However, a mapping of distinct facets of cognitive function to cerebellar stru ...
New York2023The two-point correlation function covariance with fewer mocks
We present FITCOV an approach for accurate estimation of the covariance of two-point correlation functions that requires fewer mocks than the standard mock-based covariance. This can be achieved by dividing a set of mocks into jackknife regions and fitting ...
Oxford2023Stay close, but not too close: aerial image analysis reveals patterns of social distancing in seal colonies
Devis Tuia, Benjamin Alexander Kellenberger
Many species aggregate in dense colonies. Species-specific spatial patterns provide clues about how colonies are shaped by various (a)biotic factors, including predation, temperature regulation or disease transmission. Using aerial imagery, we examined the ...
2023Fairness and Explainability in Clustering Problems
In this thesis we present and analyze approximation algorithms for three different clustering problems. The formulations of these problems are motivated by fairness and explainability considerations, two issues that have recently received attention in the ...
EPFL2023Manifold Learning-Based Polynomial Chaos Expansions For High-Dimensional Surrogate Models
In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantitie ...
2022Sketches, metrics and fast algorithms
As it has become easier and cheaper to collect big datasets in the last few decades, designing efficient and low-cost algorithms for these datasets has attracted unprecedented attention. However, in most applications, even storing datasets as acquired has ...
EPFL2022