- Epoch of reionization window. I. Mathematical formalism
- Liu, Adrian; Parsons, Aaron R.; Trott, Cathryn M.
The 21 cm line provides a powerful probe of astrophysics and cosmology at high redshifts, but unlocking the potential of this probe requires the robust mitigation of foreground contaminants that are typically several orders of magnitude brighter tha …
- Correlating Fourier phase information with real-space higher order statistics in CMB data
- Modest, H. I.; Räth, C.; Banday, A. J.; Górski, K. M.; Morfill, G. E.
We present a heuristic study on the correlations between harmonic space phase information and higher-order statistics. Using the spherical full-sky maps of the cosmic microwave background as an example, we demonstrate that known phase correlations a …
- Reconstructing the sky location of gravitational-wave detected compact binary systems: Methodology for testing and comparison
- Sidery, T.; Aylott, B.; Christensen, N.; Farr, B.; Farr, W.; Feroz, F.; Gair, J.; Grover, K.; Graff, P.; Hanna, C.; Kalogera, V.; Mandel, I.; O’Shaughnessy, R.; Pitkin, M.; Price, L.; Raymond, V.; Röver, C.; Singer, L.; van der Sluys, M.; Smith, R. J. E.; Vecchio, A.; Veitch, J.; Vitale, S.
The problem of reconstructing the sky position of compact binary coalescences detected via gravitational waves is a central one for future observations with the ground-based network of gravitational-wave laser interferometers, such as Advanced LIGO …
- Flat parameter-space metric for all-sky searches for gravitational-wave pulsars
- Wette, Karl; Prix, Reinhard
All-sky, broadband, coherent searches for gravitational-wave pulsars are computationally limited. It is therefore important to make efficient use of available computational resources, notably by minimizing the number of templates used to cover the s …
- Interpolation in waveform space: Enhancing the accuracy of gravitational waveform families using numerical relativity
- Cannon, Kipp; Emberson, J. D.; Hanna, Chad; Keppel, Drew; Pfeiffer, Harald P.
Matched filtering for the identification of compact object mergers in gravitational wave antenna data involves the comparison of the data stream to a bank of template gravitational waveforms. Typically the template bank is constructed from phenomeno …
- A fast method for power spectrum and foreground analysis for 21 cm cosmology
- Dillon, Joshua S.; Liu, Adrian; Tegmark, Max
We develop and demonstrate an acceleration of the Liu and Tegmark quadratic estimator formalism for inverse variance foreground subtraction and power spectrum estimation in 21 cm tomography from O(N3) to O(NlogN), where N is the number of voxels …
- Global 21 cm signal experiments: A designer’s guide
- Liu, Adrian; Pritchard, Jonathan R.; Tegmark, Max; Loeb, Abraham
The global (i.e., spatially averaged) spectrum of the redshifted 21 cm line has generated much experimental interest lately, thanks to its potential to be a direct probe of the epoch of reionization and the dark ages, during which the first luminous …
- ASTROMLSKIT: A New Statistical Machine Learning Toolkit: A Platform for Data Analytics in Astronomy
- Snehanshu Saha, Surbhi Agrawal, Manikandan. R, Kakoli Bora, Swati Routh, Anand Narasimhamurthy
Astroinformatics is a new impact area in the world of astronomy, occasionally called the final frontier, where several astrophysicists, statisticians and computer scientists work together to tackle various data intensive astronomical problems. Expon …
- Computation-Risk Tradeoffs for Covariance-Thresholded Regression
- Diane Shender and John Lafferty
We present a family of linear regression es- timators that provides a fine-grained trade- off between statistical accuracy and computa- tional efficiency. The estimators are based on hard thresholding of the sample covariance matrix entries together …
- Noisy Sparse Subspace Clustering
- Yu-Xiang Wang and Huan Xu
This paper considers the problem of subspace clustering under noise. Specifically, we s- tudy the behavior of Sparse Subspace Clus- tering (SSC) when either adversarial or ran- dom noise is added to the unlabelled input data points, which are assume …
- Principal Component Analysis on non-Gaussian Dependent Data
- Fang Han and Han Liu
n this paper, we analyze the performance of a semiparametric principal component analysis named Copula Component Analysis (COCA) (Han & Liu, 2012) when the data are dependent. The semiparametric model assumes that, after unspecified marginally monot …
- Scalable Optimization of Neighbor Embedding for Visualization
- Zhirong Yang, Jaakko Peltonen, Samuel Kaski
Neighbor embedding (NE) methods have found their use in data visualization but are limited in big data analysis tasks due to their O(n2) complexity for n data sam- ples. We demonstrate that the obvious ap- proach of subsampling produces inferior re- …
- Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning
- Daniel Tarlow, Kevin Swersky, Ilya Sutskever, Richard S. Zemel
Neighborhood Components Analysis (NCA) is a popular method for learning a distance metric to be used within a k-nearest neigh- bors (kNN) classifier. A key assumption built into the model is that each point stochasti- cally selects a single neighbor …
- MAD-Bayes: MAP-based Asymptotic Derivations from Bayes
- Tamara Broderick, Brian Kulis, Michael I. Jordan
The classical mixture of Gaussians model is related to K-means via small-variance asymptotics: as the covariances of the Gaus- sians tend to zero, the negative log-likelihood of the mixture of Gaussians model ap- proaches the K-means objective, and …
- On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance
- Aditya Krishna Menon, Harikrishna Narasimhan, Shivani Agarwal, India Sanjay Chawla
Class imbalance situations, where one class is rare compared to the other, arise frequently in machine learning applications. It is well known that the usual misclassification error is ill-suited for measuring performance in such settings. A wide ra …
- Quantile Regression for Large-scale Applications
- Jiyan Yang, Xiangrui Meng, Michael W. Mahoney
Quantile regression is a method to estimate the quantiles of the conditional distribution of a response variable, and as such it permits a much more accurate portrayal of the rela- tionship between the response variable and observed covariates than …
- Structure Discovery in Nonparametric Regression through Compositional Kernel Search
- David Duvenaud, James Robert Lloyd, Roger Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani
Despite its importance, choosing the struc- tural form of the kernel in nonparametric regression remains a black art. We define a space of kernel structures which are built compositionally by adding and multiplying a small number of base kernels. We …
- On the distances of planetary nebulae
- Smith, Haywood
Past calibrations of statistical distance scales for planetary nebulae have been problematic, especially with regard to `short’ versus `long’ scales. Reconsidering the calibration process naturally involves examining the precision and especially the …
- Detection of periodicity based on serial dependence of phase-folded data
- Zucker, Shay
We introduce and test several novel approaches for periodicity detection in unevenly-spaced sparse data sets. Specifically, we examine five different kinds of periodicity metrics, which are based on non-parametric measures of serial dependence of th …
- Testing the mutual consistency of different supernovae surveys
- Karpenka, N. V.; Feroz, F.; Hobson, M. P.
It is now common practice to constrain cosmological parameters using supernovae (SNe) catalogues constructed from several different surveys. Before performing such a joint analysis, however, one should check that parameter constraints derived from t …