Related papers: Informative Bayesian model selection for RR Lyrae …
In strategic classification, agents modify their features, at a cost, to ideally obtain a positive classification from the learner's classifier. The typical response of the learner is to carefully modify their classifier to be robust to…
We present a Bayesian method for the identification and classification of objects from sets of astronomical catalogs, given a predefined classification scheme. Identification refers here to the association of entries in different catalogs…
Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. In many situations, such as when human decisions need to be combined, the base decisions can…
We have investigated and applied machine-learning algorithms for Infrared Colour Selection of Galactic Wolf-Rayet (WR) candidates. Objects taken from the GLIMPSE catalogue of the infrared objects in the Galactic plane can be classified into…
We present a search and analysis of variable stars in the recently discovered Crater~II dwarf galaxy. Based on $B$, $V$, $I$ data collected with the Isaac Newton Telescope (FoV$\sim$0.44 square degrees) we detected 37 variable stars, of…
We provide a flexible framework for selecting among a class of additive partial linear models that allows both linear and nonlinear additive components. In practice, it is challenging to determine which additive components should be…
We propose an iterative variable selection scheme for high-dimensional data with binary outcomes. The scheme adopts a structured screen-and-select framework and uses non-local prior-based Bayesian model selection within the same. The…
Automated decision making is used routinely throughout our everyday life. Recommender systems decide which jobs, movies, or other user profiles might be interesting to us. Spell checkers help us to make good use of language. Fraud detection…
Although conceptually related, variable selection and relative importance (RI) analysis have been treated quite differently in the literature. While RI is typically used for post-hoc model explanation, this paper explores its potential for…
We develop a Bayesian approach for selecting the model which is the most supported by the data within a class of marginal models for categorical variables formulated through equality and/or inequality constraints on generalised logits…
A systematic study of RR Lyrae stars is performed based on a selected sample of 655 objects in the Large Magellanic Cloud with observation of long span and numerous measurements by the Optical Gravitational Lensing Experiment III project.…
Bayesian methods for graphical log-linear marginal models have not been developed in the same extent as traditional frequentist approaches. In this work, we introduce a novel Bayesian approach for quantitative learning for such models.…
RR Lyrae (RRL) variable stars are cornerstone distance indicators. In particular, double-mode RR Lyrae (RRd) stars enable period--luminosity relations (PLRs) that are less sensitive to metallicity, reducing systematic biases in distance…
We present a method for selecting RR Lyrae (RRL) stars (or other type of variable stars) in the absence of a large number of multi-epoch data and light curve analyses. Our method uses color and variability selection cuts that are defined by…
The Bayesian learning rule is a natural-gradient variational inference method, which not only contains many existing learning algorithms as special cases but also enables the design of new algorithms. Unfortunately, when variational…
The cross-identification of sources in separate catalogs is one of the most basic tasks in observational astronomy. It is, however, surprisingly difficult and generally ill-defined. Recently Budav\'ari & Szalay (2008) formulated the problem…
Bayesian analysis of LISA data sets based on Markov chain Monte Carlo methods has been shown to be a challenging problem, in part due to the complicated structure of the likelihood function consisting of several isolated local maxima that…
Bayesian analysis is increasingly popular for use in social science and other application areas where the data are observations from an informative sample. An informative sampling design leads to inclusion probabilities that are correlated…
RR Lyrae stars play a central role in tracing phase-space structures within the Milky Way because they are easy to identify, are relatively luminous, and are found in large numbers in the Galactic bulge, disk, and halo. In this work, we…
Binary classification is a task that involves the classification of data into one of two distinct classes. It is widely utilized in various fields. However, conventional classifiers tend to make overconfident predictions for data that…