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University of Louisville

Faculty Scholarship

2019

Articles 1 - 16 of 16

Full-Text Articles in Physical Sciences and Mathematics

Seer: An Explainable Deep Learning Midi-Based Hybrid Song Recommender System, Khalil Damak, Olfa Nasraoui Dec 2019

Seer: An Explainable Deep Learning Midi-Based Hybrid Song Recommender System, Khalil Damak, Olfa Nasraoui

Faculty Scholarship

State of the art music recommender systems mainly rely on either matrix factorization-based collaborative filtering approaches or deep learning architectures. Deep learning models usually use metadata for content-based filtering or predict the next user interaction by learning from temporal sequences of user actions. Despite advances in deep learning for song recommendation, none has taken advantage of the sequential nature of songs by learning sequence models that are based on content. Aside from the importance of prediction accuracy, other significant aspects are important, such as explainability and solving the cold start problem. In this work, we propose a hybrid deep learning …

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Default Parallels: The Science Potential Of Jwst Parallel Observations During Tso Primary Observations, Benne W. Holwerda, Jonathan Fraine, Nelly Mouawad, Joanna S. Bridge Nov 2019

Default Parallels: The Science Potential Of Jwst Parallel Observations During Tso Primary Observations, Benne W. Holwerda, Jonathan Fraine, Nelly Mouawad, Joanna S. Bridge

Faculty Scholarship

The James Webb Space Telescope (JWST) will observe several stars for long cumulative durations while pursuing exoplanets as primary science targets for both Guaranteed Time Observations (GTO) and very likely General Observer (GO) programs. Here we argue in favor of an automatic default parallel program to observe, e.g., using the F200W/F277W filters or grism of NIRCAM/NIRISS in order to find high redshift (z (Formula Presented) 10) galaxies, cool red/brown dwarf substellar objects, solar system objects, and observations of serendipitous planetary transits. We argue here the need for automated exploratory astrophysical observations with unused JWST instruments during these long-duration exoplanet observations. …

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Effect Of Galaxy Mergers On Star-Formation Rates, W. J. Pearson, L. Wang, M. Alpaslan, I. Baldry, M. Bilicki, M. J.I. Brown, M. W. Grootes, Benne W. Holwerda, T. D. Kitching, S. Kruk, F. F.S. Van Der Tak Nov 2019

Effect Of Galaxy Mergers On Star-Formation Rates, W. J. Pearson, L. Wang, M. Alpaslan, I. Baldry, M. Bilicki, M. J.I. Brown, M. W. Grootes, Benne W. Holwerda, T. D. Kitching, S. Kruk, F. F.S. Van Der Tak

Faculty Scholarship

Context. Galaxy mergers and interactions are an integral part of our basic understanding of how galaxies grow and evolve over time. However, the effect that galaxy mergers have on star-formation rates (SFRs) is contested, with observations of galaxy mergers showing reduced, enhanced, and highly enhanced star formation. Aims. We aim to determine the effect of galaxy mergers on the SFR of galaxies using statistically large samples of galaxies, totalling over 200 000, which is over a large redshift range from 0.0 to 4.0. Methods. We trained and used convolutional neural networks to create binary merger identifications (merger or non-merger) in …

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Star-Forming, Rotating Spheroidal Galaxies In The Gama And Sami Surveys, Amanda J. Moffett, Steven Phillipps, Aaron S.G. Robotham, Simon P. Driver, Malcolm N. Bremer, Luca Cortese, O. Ivy Wong, Sarah Brough, Michael J.I. Brown, Julia J. Bryant, Christopher J. Conselice, Scott M. Croom, Koshy George, Greg Goldstein, Michael Goodwin, Benne W. Holwerda, Andrew M. Hopkins, Iraklis S. Konstantopoulos, Jon S. Lawrence, Nuria P.F. Lorente, Anne M. Medling, Matt S. Owers, Kevin A. Pimbblet, Samuel N. Richards, Sarah M. Sweet, Jesse Van De Sande Oct 2019

Star-Forming, Rotating Spheroidal Galaxies In The Gama And Sami Surveys, Amanda J. Moffett, Steven Phillipps, Aaron S.G. Robotham, Simon P. Driver, Malcolm N. Bremer, Luca Cortese, O. Ivy Wong, Sarah Brough, Michael J.I. Brown, Julia J. Bryant, Christopher J. Conselice, Scott M. Croom, Koshy George, Greg Goldstein, Michael Goodwin, Benne W. Holwerda, Andrew M. Hopkins, Iraklis S. Konstantopoulos, Jon S. Lawrence, Nuria P.F. Lorente, Anne M. Medling, Matt S. Owers, Kevin A. Pimbblet, Samuel N. Richards, Sarah M. Sweet, Jesse Van De Sande

Faculty Scholarship

The Galaxy And Mass Assembly (GAMA) survey has morphologically identified a class of 'Little Blue Spheroid' (LBS) galaxies whose relationship to other classes of galaxies we now examine in detail. Considering a sample of 868 LBSs, we find that such galaxies display similar but not identical colours, specific star formation rates, stellar population ages, massto- light ratios, and metallicities to Sd-Irr galaxies. We also find that LBSs typically occupy environments of even lower density than those of Sd-Irr galaxies, where ∼65 per cent of LBS galaxies live in isolation. Using deep, high-resolution imaging from VST KiDS and the new Bayesian, …

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The Super Eight Galaxies: Properties Of A Sample Of Very Bright Galaxies At 7 < Z < 8, Joanna S. Bridge, Benne W. Holwerda, Mauro Stefanon, Rychard J. Bouwens, Pascal A. Oesch, Michele Trenti, Stephanie R. Bernard, Larry D. Bradley, Garth D. Illingworth, Samir Kusmic, Dan Magee, Takahiro Morishita, Guido W. Roberts-Borsani, Renske Smit, Rebecca L. Steele Sep 2019

The Super Eight Galaxies: Properties Of A Sample Of Very Bright Galaxies At 7 < Z < 8, Joanna S. Bridge, Benne W. Holwerda, Mauro Stefanon, Rychard J. Bouwens, Pascal A. Oesch, Michele Trenti, Stephanie R. Bernard, Larry D. Bradley, Garth D. Illingworth, Samir Kusmic, Dan Magee, Takahiro Morishita, Guido W. Roberts-Borsani, Renske Smit, Rebecca L. Steele

Faculty Scholarship

We present the Super Eight galaxies - a set of very luminous, high-redshift (7.1 < z < 8.0) galaxy candidates found in the Brightest of Reionizing Galaxies (BoRG) Survey fields. The original sample includes eight galaxies that are Y-band dropout objects with H-band magnitudes of m H < 25.5. Four of these objects were originally reported in Calvi et al. Combining new Hubble Space Telescope (HST) WFC3/F814W imaging and Spitzer IRAC data with archival imaging from BoRG and other surveys, we explore the properties of these galaxies. Photometric redshift fitting places six of these galaxies in the redshift range of 7.1 < z < 8.0, resulting in three new high-redshift galaxies and confirming three of the four high-redshift galaxy candidates from Calvi et al. We calculate the half-light radii of the Super Eight galaxies using the HST F160W filter and find that the Super Eight sizes are in line with the typical evolution of size with redshift. The Super Eights have a mean mass of log (M ∗/M o) ∼10, which is typical for sources in this luminosity range. Finally, we place our sample on the UV z ∼ 8 luminosity function and find that the Super Eight number density is consistent with other surveys in this magnitude and redshift range.

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Mining Semantic Knowledge Graphs To Add Explainability To Black Box Recommender Systems, Mohammed Alshammari, Olfa Nasraoui, Scott Sanders Aug 2019

Mining Semantic Knowledge Graphs To Add Explainability To Black Box Recommender Systems, Mohammed Alshammari, Olfa Nasraoui, Scott Sanders

Faculty Scholarship

Recommender systems are being increasingly used to predict the preferences of users on online platforms and recommend relevant options that help them cope with information overload. In particular, modern model-based collaborative filtering algorithms, such as latent factor models, are considered state-of-the-art in recommendation systems. Unfortunately, these black box systems lack transparency, as they provide little information about the reasoning behind their predictions. White box systems, in contrast, can, by nature, easily generate explanations. However, their predictions are less accurate than sophisticated black box models. Recent research has demonstrated that explanations are an essential component in bringing the powerful predictions of …

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Galaxy Classification: A Machine Learning Analysis Of Gama Catalogue Data, Aleke Nolte, Lingyu Wang, Maciej Bilicki, Benne W. Holwerda, Michael Biehl May 2019

Galaxy Classification: A Machine Learning Analysis Of Gama Catalogue Data, Aleke Nolte, Lingyu Wang, Maciej Bilicki, Benne W. Holwerda, Michael Biehl

Faculty Scholarship

We present a machine learning analysis of five labelled galaxy catalogues from the Galaxy And Mass Assembly (GAMA): The SersicCatVIKING and SersicCatUKIDSS catalogues containing morphological features, the GaussFitSimplecatalogue containing spectroscopic features, the MagPhys catalogue including physical parameters for galaxies, and the Lambdar catalogue, which contains photometric measurements. Extending work previously presented at the ESANN 2018 conference – in an analysis based on Generalized Relevance Matrix Learning Vector Quantization and Random Forests – we find that neither the data from the individual catalogues nor a combined dataset based on all 5 catalogues fully supports the visual-inspection-based galaxy classification scheme employed to …

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Debiasing The Human-Recommender System Feedback Loop In Collaborative Filtering, Wenlong Sun, Sami Khenissi, Olfa Nasraoui, Patrick Shafto May 2019

Debiasing The Human-Recommender System Feedback Loop In Collaborative Filtering, Wenlong Sun, Sami Khenissi, Olfa Nasraoui, Patrick Shafto

Faculty Scholarship

Recommender Systems (RSs) are widely used to help online users discover products, books, news, music, movies, courses, restaurants,etc. Because a traditional recommendation strategy always shows the most relevant items (thus with highest predicted rating), traditional RS’s are expected to make popular items become even more popular and non-popular items become even less popular which in turn further divides the haves (popular) from the have-nots (un-popular). Therefore, a major problem with RSs is that they may introduce biases affecting the exposure of items, thus creating a popularity divide of items during the feedback loop that occurs with users, and this may …

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Galaxy And Mass Assembly (Gama): Time-Scales For Galaxies Crossing The Green Valley, S. Phillipps, M. N. Bremer, A. M. Hopkins, R. De Propris, E. N. Taylor, P. A. James, L. J.M. Davies, M. E. Cluver, S. P. Driver, S. A. Eales, Benne W. Holwerda, L. S. Kelvin, A. E. Sansom Mar 2019

Galaxy And Mass Assembly (Gama): Time-Scales For Galaxies Crossing The Green Valley, S. Phillipps, M. N. Bremer, A. M. Hopkins, R. De Propris, E. N. Taylor, P. A. James, L. J.M. Davies, M. E. Cluver, S. P. Driver, S. A. Eales, Benne W. Holwerda, L. S. Kelvin, A. E. Sansom

Faculty Scholarship

We explore the constraints that can be placed on the evolutionary time-scales for typical low-redshift galaxies evolving from the blue cloud through the green valley and on to the red sequence. We utilize galaxies from the GAMA survey with 0.1 < z < 0.2 and classify them according to the intrinsic (u∗ - r∗) colours of their stellar populations, as determined by fits to their multiwavelength spectral energy distributions. Using these fits to also determine stellar population ages and star formation time-scales, we argue that our results are consistent with a green valley population dominated by galaxies that are simply decreasing their star formation (running out of gas) over a time-scale of 2-4 Gyr which are seen at a specific epoch in their evolution (approximately 1.6 e-folding times after their peak in star formation). If their fitted star formation histories are extrapolated forward, the green galaxies will further redden over time, until they attain the colours of a passive population. In this picture, no specific quenching event which cuts-off their star formation is required, though it remains possible that the decline in star formation in green galaxies may be expedited by internal or external forces. However, there is no evidence that green galaxies have recently changed their star formation time-scales relative to their previous longer term star formation histories.

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Galaxy And Mass Assembly (Gama): Environmental Quenching Of Centrals And Satellites In Groups, L. J.M. Davies, A. S.G. Robotham, C. Del P. Lagos, S. P. Driver, A. R.H. Stevens, Y. M. Bahé, M. Alpaslan, M. N. Bremer, M. J.I. Brown, S. Brough, J. Bland-Hawthorn, L. Cortese, P. Elahi, M. W. Grootes, Benne W. Holwerda, A. D. Ludlow, S. Mcgee, M. Owers, S. Phillipps Mar 2019

Galaxy And Mass Assembly (Gama): Environmental Quenching Of Centrals And Satellites In Groups, L. J.M. Davies, A. S.G. Robotham, C. Del P. Lagos, S. P. Driver, A. R.H. Stevens, Y. M. Bahé, M. Alpaslan, M. N. Bremer, M. J.I. Brown, S. Brough, J. Bland-Hawthorn, L. Cortese, P. Elahi, M. W. Grootes, Benne W. Holwerda, A. D. Ludlow, S. Mcgee, M. Owers, S. Phillipps

Faculty Scholarship

Recently a number of studies have found a similarity between the passive fraction of central and satellite galaxies when controlled for both stellar and halo mass. These results suggest that the quenching processes that affect galaxies are largely agnostic to central/satellite status, which contradicts the traditional picture of increased satellite quenching via environmental processes such as stripping, strangulation, and starvation. Here we explore this further using the Galaxy And Mass Assembly (GAMA) survey, which extends to ~2 dex lower in stellar mass than SDSS, is more complete for closely separated galaxies (≳395 per cent compared to ≳370 per cent), and …

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The Dependence Of Intrinsic Alignment Of Galaxies On Wavelength Using Kids And Gama, Christos Georgiou, Harry Johnston, Henk Hoekstra, Massimo Viola, Konrad Kuijken, Benjamin Joachimi, Nora Elisa Chisari, Daniel J. Farrow, Hendrik Hildebrandt, Benne W. Holwerda, Arun Kannawadi Feb 2019

The Dependence Of Intrinsic Alignment Of Galaxies On Wavelength Using Kids And Gama, Christos Georgiou, Harry Johnston, Henk Hoekstra, Massimo Viola, Konrad Kuijken, Benjamin Joachimi, Nora Elisa Chisari, Daniel J. Farrow, Hendrik Hildebrandt, Benne W. Holwerda, Arun Kannawadi

Faculty Scholarship

The outer regions of galaxies are more susceptible to the tidal interactions that lead to intrinsic alignments of galaxies. The resulting alignment signal may therefore depend on the passband if the colours of galaxies vary spatially. To quantify this, we measured the shapes of galaxies with spectroscopic redshifts from the GAMA survey using deep gri imaging data from the KiloDegree Survey. The performance of the moment-based shape measurement algorithm DEIMOS was assessed using dedicated image simulations, which showed that the ellipticities could be determined with an accuracy better than 1% in all bands. Additional tests for potential systematic errors did …

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The Frequency Of Dust Lanes In Edge-On Spiral Galaxies Identified By Galaxy Zoo In Kids Imaging Of Gama Targets, Benne W. Holwerda, Lee Kelvin, Ivan Baldry, Chris Lintott, Mehmet Alpaslan, Kevin A. Pimbblet, Jochen Liske, Thomas Kitching, Steven Bamford, Jelte De Jong, Maciej Bilicki, Andrew Hopkins, Joanna Bridge, R. Steele, A. Jacques, S. Goswami, S. Kusmic, W. Roemer, S. Kruk, C. C. Popescu, K. Kuijken, L. Wang, A. Wright Jan 2019

The Frequency Of Dust Lanes In Edge-On Spiral Galaxies Identified By Galaxy Zoo In Kids Imaging Of Gama Targets, Benne W. Holwerda, Lee Kelvin, Ivan Baldry, Chris Lintott, Mehmet Alpaslan, Kevin A. Pimbblet, Jochen Liske, Thomas Kitching, Steven Bamford, Jelte De Jong, Maciej Bilicki, Andrew Hopkins, Joanna Bridge, R. Steele, A. Jacques, S. Goswami, S. Kusmic, W. Roemer, S. Kruk, C. C. Popescu, K. Kuijken, L. Wang, A. Wright

Faculty Scholarship

Dust lanes bisect the plane of a typical edge-on spiral galaxy as a dark optical absorption feature. Their appearance is linked to the gravitational stability of spiral disks; the fraction of edge-on galaxies that displays a dust lane is a direct indicator of the typical vertical balance between gravity and turbulence: a balance struck between the energy input from star formation and the gravitational pull into the plane of the disk. Based on morphological classifications by the Galaxy Zoo project on the Kilo Degree Survey (KiDS) imaging data in the Galaxy and Mass Assembly (GAMA) fields, we explore the relation …

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Personal Universes: A Solution To The Multi-Agent Value Alignment Problem, Roman V. Yampolskiy Jan 2019

Personal Universes: A Solution To The Multi-Agent Value Alignment Problem, Roman V. Yampolskiy

Faculty Scholarship

AI Safety researchers attempting to align values of highly capable intelligent systems with those of humanity face a number of challenges including personal value extraction, multi-agent value merger and finally in-silico encoding. State-of-the-art research in value alignment shows difficulties in every stage in this process, but merger of incompatible preferences is a particularly difficult challenge to overcome. In this paper we assume that the value extraction problem will be solved and propose a possible way to implement an AI solution which optimally aligns with individual preferences of each user. We conclude by analyzing benefits and limitations of the proposed approach.

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An Explainable Autoencoder For Collaborative Filtering Recommendation, Pegah Sagheb Haghighi, Olurotimi Seton, Olfa Nasraoui Jan 2019

An Explainable Autoencoder For Collaborative Filtering Recommendation, Pegah Sagheb Haghighi, Olurotimi Seton, Olfa Nasraoui

Faculty Scholarship

Autoencoders are a common building block of Deep Learning architectures, where they are mainly used for representation learning. They have also been successfully used in Collaborative Filtering (CF) recommender systems to predict missing ratings. Unfortunately, like all black box machine learning models, they are unable to explain their outputs. Hence, while predictions from an Autoencoderbased recommender system might be accurate, it might not be clear to the user why a recommendation was generated. In this work, we design an explainable recommendation system using an Autoencoder model whose predictions can be explained using the neighborhood based explanation style. Our preliminary work …

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Reproducible K-Means Clustering In Galaxy Feature Data From The Gama Survey, Sebastian Turner, Lee S. Kelvin, Ivan K. Baldry, Paulo J. Lisboa, Steven N. Longmore, Chris A. Collins, Benne W. Holwerda, Andrew M. Hopkins, Jochen Liske Jan 2019

Reproducible K-Means Clustering In Galaxy Feature Data From The Gama Survey, Sebastian Turner, Lee S. Kelvin, Ivan K. Baldry, Paulo J. Lisboa, Steven N. Longmore, Chris A. Collins, Benne W. Holwerda, Andrew M. Hopkins, Jochen Liske

Faculty Scholarship

A fundamental bimodality of galaxies in the local Universe is apparent in many of the features used to describe them. Multiple sub-populations exist within this framework, each representing galaxies following distinct evolutionary pathways. Accurately identifying and characterizing these sub-populations requires that a large number of galaxy features be analysed simultaneously. Future galaxy surveys such as LSST and Euclid will yield data volumes for which traditional approaches to galaxy classification will become unfeasible. To address this, we apply a robust k-means unsupervized clustering method to feature data derived from a sample of 7338 local-Universe galaxies selected from the Galaxy And Mass …

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Askap Commissioning Observations Of The Gama 23 Field, Denis A. Leahy, A. M. Hopkins, R. P. Norris, J. Marvil, J. D. Collier, E. N. Taylor, J. R. Allison, C. Anderson, M. Bell, M. Bilicki, J. Bland-Hawthorn, S. Brough, M. J.I. Brown, S. Driver, G. Gurkan, L. Harvey-Smith, I. Heywood, Benne W. Holwerda, J. Liske, A. R. Lopez-Sanchez, D. Mcconnell, A. Moffett, M. S. Owers, K. A. Pimbblet, W. Raja, N. Seymour, M. A. Voronkov, L. Wang Jan 2019

Askap Commissioning Observations Of The Gama 23 Field, Denis A. Leahy, A. M. Hopkins, R. P. Norris, J. Marvil, J. D. Collier, E. N. Taylor, J. R. Allison, C. Anderson, M. Bell, M. Bilicki, J. Bland-Hawthorn, S. Brough, M. J.I. Brown, S. Driver, G. Gurkan, L. Harvey-Smith, I. Heywood, Benne W. Holwerda, J. Liske, A. R. Lopez-Sanchez, D. Mcconnell, A. Moffett, M. S. Owers, K. A. Pimbblet, W. Raja, N. Seymour, M. A. Voronkov, L. Wang

Faculty Scholarship

We have observed the G23 field of the Galaxy AnMass Assembly (GAMA) survey using the Australian Square Kilometre Array Pathfinder (ASKAP) in its commissioning phase to validate the performance of the telescope and to characterise the detected galaxy populations. This observation covers ∼48 deg2 with synthesised beam of 32.7 arcsec by 17.8 arcsec at 936MHz, and ∼39 deg2 with synthesised beam of 15.8 arcsec by 12.0 arcsec at 1320MHz. At both frequencies, the root-mean-square (r.m.s.) noise is ∼0.1 mJy/beam. We combine these radio observations with the GAMA galaxy data, which includes spectroscopy of galaxies that are i-band selected with a …

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