Online Nonparametric Anomaly Detection based on Geometric Entropy Minimization

We consider the online and nonparametric detection of abrupt and persistent anomalies, such as a change in the regular system dynamics at a time instance due to an anomalous event (e.g., a failure, a malicious activity). Combining the simplicity of the nonparametric Geometric Entropy Minimization (GEM) method with the timely detection capability of the Cumulative Sum (CUSUM) algorithm we propose a computationally efficient online anomaly detection method that is applicable to high-dimensional datasets, and at the same time achieve a near-optimum average detection delay performance for a given false alarm constraint. We provide new insights to both GEM and CUSUM, including new asymptotic analysis for GEM, which enables soft decisions for outlier detection, and a novel interpretation of CUSUM in terms of the discrepancy theory, which helps us generalize it to the nonparametric GEM statistic. We numerically show, using both simulated and real datasets, that the proposed nonparametric algorithm attains a close performance to the clairvoyant parametric CUSUM test.Comment: to appear in IEEE International Symposium on Information Theory (ISIT) 201

On the Reification of Global Constraints

We introduce a simple idea for deriving reified global constraints in a systematic way. It is based on the observation that most global constraints can be reformulated as a conjunction of pure functional dependency constraints together with a constraint that can be easily reified. We first show how the core constraints of the Global Constraint Catalogue can be reified and we then identify several reification categories that apply to at least 82% of the constraints in the Global Constraint Catalogue

General theory of the modified Gutenberg-Richter law for large seismic moments

The Gutenberg-Richter power law distribution of earthquake sizes is one of the most famous example illustrating self-similarity. It is well-known that the Gutenberg-Richter distribution has to be modified for large seismic moments, due to energy conservation and geometrical reasons. Several models have been proposed, either in terms of a second power law with a larger b-value beyond a cross-over magnitude, or based on a ``hard'' magnitude cut-off or a ``soft'' magnitude cut-off using an exponential taper. Since the large scale tectonic deformation is dominated by the very largest earthquakes and since their impact on loss of life and properties is huge, it is of great importance to constrain as much as possible the shape of their distribution. We present a simple and powerful probabilistic theoretical approach that shows that the Gamma distribution is the best model, under the two hypothesis that the Gutenberg-Richter power law distribution holds in absence of any condition (condition of criticality) and that one or several constraints are imposed, either based on conservation laws or on the nature of the observations themselves. The selection of the Gamma distribution does not depend on the specific nature of the constraint. We illustrate the approach with two constraints, the existence of a finite moment release rate and the observation of the size of a maximum earthquake in a finite catalog. Our predicted ``soft'' maximum magnitudes compare favorably with those obtained by Kagan [1997] for the Flinn-Engdahl regionalization of subduction zones, collision zones and mid-ocean ridges.Comment: 24 pages, including 3 tables, in press in Bull. Seism. Soc. A

Bayesian emulation for optimization in multi-step portfolio decisions

We discuss the Bayesian emulation approach to computational solution of multi-step portfolio studies in financial time series. "Bayesian emulation for decisions" involves mapping the technical structure of a decision analysis problem to that of Bayesian inference in a purely synthetic "emulating" statistical model. This provides access to standard posterior analytic, simulation and optimization methods that yield indirect solutions of the decision problem. We develop this in time series portfolio analysis using classes of economically and psychologically relevant multi-step ahead portfolio utility functions. Studies with multivariate currency, commodity and stock index time series illustrate the approach and show some of the practical utility and benefits of the Bayesian emulation methodology.Comment: 24 pages, 7 figures, 2 table

Probing the circumgalactic baryons through cross-correlations

We study the cross-correlation of distribution of galaxies, the Sunyaev-Zel'dovich (SZ) and X-ray power spectra of galaxies from current and upcoming surveys and show these to be excellent probes of the nature, i.e. extent, evolution and energetics, of the circumgalactic medium (CGM). The SZ-galaxy cross-power spectrum, especially at large multipoles, depends on the steepness of the pressure profile of the CGM. This property of the SZ signal can, thus, be used to constrain the pressure profile of the CGM. The X-ray cross power spectrum also has a similar shape. However, it is much more sensitive to the underlying density profile. We forecast the detectability of the cross-correlated galaxy distribution, SZ and X-ray signals by combining South Pole Telescope-Dark Energy Survey (SPT-DES) and eROSITA-DES/eROSITA-LSST (extended ROentgen Survey with an Imaging Telescope Array-Large Synoptic Survey Telescope) surveys, respectively. We find that, for the SPT-DES survey, the signal-to-noise ratio (SNR) peaks at high mass and redshift with SNR $\sim 9$ around $M_h\sim 10^{13} h^{-1} M_{\odot}$ and $z\sim 1.5\hbox{--} 2$ for flat density and temperature profiles. The SNR peaks at $\sim 6 (12 )$ for the eROSITA-DES (eROSITA-LSST) surveys. We also perform a Fisher matrix analysis to find the constraint on the gas fraction in the CGM in the presence or absence of an unknown redshift evolution of the gas fraction. Finally, we demonstrate that the cross-correlated SZ-galaxy and X-ray-galaxy power spectrum can be used as powerful probes of the CGM energetics and potentially discriminate between different feedback models recently proposed in the literature; for example, one can distinguish a `no active galactic nuclei feedback' scenario from a CGM energized by `fixed-velocity hot winds' at greater than $3\sigma$.Comment: 14 pages, 10 figures, 4 tables, accepted for publication in MNRA

Resummed Photon Spectra for WIMP Annihilation

We construct an effective field theory (EFT) description of the hard photon spectrum for heavy WIMP annihilation. This facilitates precision predictions relevant for line searches, and allows the incorporation of non-trivial energy resolution effects. Our framework combines techniques from non-relativistic EFTs and soft-collinear effective theory (SCET), as well as its multi-scale extensions that have been recently introduced for studying jet substructure. We find a number of interesting features, including the simultaneous presence of SCET$_{\text{I}}$ and SCET$_{\text{II}}$ modes, as well as collinear-soft modes at the electroweak scale. We derive a factorization formula that enables both the resummation of the leading large Sudakov double logarithms that appear in the perturbative spectrum, and the inclusion of Sommerfeld enhancement effects. Consistency of this factorization is demonstrated to leading logarithmic order through explicit calculation. Our final result contains both the exclusive and the inclusive limits, thereby providing a unifying description of these two previously-considered approximations. We estimate the impact on experimental sensitivity, focusing for concreteness on an SU(2)$_{W}$ triplet fermion dark matter - the pure wino - where the strongest constraints are due to a search for gamma-ray lines from the Galactic Center. We find numerically significant corrections compared to previous results, thereby highlighting the importance of accounting for the photon spectrum when interpreting data from current and future indirect detection experiments.Comment: 55+25 pages, 11+2 figures; v3, updated an expression in the appendix to make it applicable at higher order - no impact on the results in this wor

An Analysis of the Value of Information when Exploring Stochastic, Discrete Multi-Armed Bandits

In this paper, we propose an information-theoretic exploration strategy for stochastic, discrete multi-armed bandits that achieves optimal regret. Our strategy is based on the value of information criterion. This criterion measures the trade-off between policy information and obtainable rewards. High amounts of policy information are associated with exploration-dominant searches of the space and yield high rewards. Low amounts of policy information favor the exploitation of existing knowledge. Information, in this criterion, is quantified by a parameter that can be varied during search. We demonstrate that a simulated-annealing-like update of this parameter, with a sufficiently fast cooling schedule, leads to an optimal regret that is logarithmic with respect to the number of episodes.Comment: Entrop

Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling

Tight performance specifications in combination with operational constraints make model predictive control (MPC) the method of choice in various industries. As the performance of an MPC controller depends on a sufficiently accurate objective and prediction model of the process, a significant effort in the MPC design procedure is dedicated to modeling and identification. Driven by the increasing amount of available system data and advances in the field of machine learning, data-driven MPC techniques have been developed to facilitate the MPC controller design. While these methods are able to leverage available data, they typically do not provide principled mechanisms to automatically trade off exploitation of available data and exploration to improve and update the objective and prediction model. To this end, we present a learning-based MPC formulation using posterior sampling techniques, which provides finite-time regret bounds on the learning performance while being simple to implement using off-the-shelf MPC software and algorithms. The performance analysis of the method is based on posterior sampling theory and its practical efficiency is illustrated using a numerical example of a highly nonlinear dynamical car-trailer system