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Transductive Zero-Shot Learning with Adaptive Structural Embedding
Zero-shot learning (ZSL) endows the computer vision system with the inferential capability to recognize instances of a new category that has never seen before. Two fundamental challenges in it are visual-semantic embedding and domain adaptation in cross-modality learning and unseen class prediction steps, respectivel...
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A geometric attractor mechanism for self-organization of entorhinal grid modules
Grid cells in the medial entorhinal cortex (mEC) respond when an animal occupies a periodic lattice of "grid fields" in the environment. The grids are organized in modules with spatial periods clustered around discrete values separated by constant ratios reported in the range 1.3-1.8. We propose a mechanism for dynam...
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Attacking Strategies and Temporal Analysis Involving Facebook Discussion Groups
Online social network (OSN) discussion groups are exerting significant effects on political dialogue. In the absence of access control mechanisms, any user can contribute to any OSN thread. Individuals can exploit this characteristic to execute targeted attacks, which increases the potential for subsequent malicious ...
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Perception-based energy functions in seam-cutting
Image stitching is challenging in consumer-level photography, due to alignment difficulties in unconstrained shooting environment. Recent studies show that seam-cutting approaches can effectively relieve artifacts generated by local misalignment. Normally, seam-cutting is described in terms of energy minimization, ho...
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Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo
Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space model...
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Deep Projective 3D Semantic Segmentation
Semantic segmentation of 3D point clouds is a challenging problem with numerous real-world applications. While deep learning has revolutionized the field of image semantic segmentation, its impact on point cloud data has been limited so far. Recent attempts, based on 3D deep learning approaches (3D-CNNs), have achiev...
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Dynamic Pricing with Finitely Many Unknown Valuations
Motivated by posted price auctions where buyers are grouped in an unknown number of latent types characterized by their private values for the good on sale, we investigate revenue maximization in stochastic dynamic pricing when the distribution of buyers' private values is supported on an unknown set of points in [0,...
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Haar systems, KMS states on von Neumann algebras and $C^*$-algebras on dynamically defined groupoids and Noncommutative Integration
We analyse certain Haar systems associated to groupoids obtained by certain natural equivalence relations of dynamical nature on sets like $\{1,2,...,d\}^\mathbb{Z}$, $\{1,2,...,d\}^\mathbb{N}$, $S^1\times S^1$, or $(S^1)^\mathbb{N}$, where $S^1$ is the unitary circle. We also describe properties of transverse functi...
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Restoring a smooth function from its noisy integrals
Numerical (and experimental) data analysis often requires the restoration of a smooth function from a set of sampled integrals over finite bins. We present the bin hierarchy method that efficiently computes the maximally smooth function from the sampled integrals using essentially all the information contained in the...
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Adversarial Active Learning for Deep Networks: a Margin Based Approach
We propose a new active learning strategy designed for deep neural networks. The goal is to minimize the number of data annotation queried from an oracle during training. Previous active learning strategies scalable for deep networks were mostly based on uncertain sample selection. In this work, we focus on examples ...
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Improving SIEM capabilities through an enhanced probe for encrypted Skype traffic detection
Nowadays, the Security Information and Event Management (SIEM) systems take on great relevance in handling security issues for critical infrastructures as Internet Service Providers. Basically, a SIEM has two main functions: i) the collection and the aggregation of log data and security information from disparate net...
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Escaping Saddle Points with Adaptive Gradient Methods
Adaptive methods such as Adam and RMSProp are widely used in deep learning but are not well understood. In this paper, we seek a crisp, clean and precise characterization of their behavior in nonconvex settings. To this end, we first provide a novel view of adaptive methods as preconditioned SGD, where the preconditi...
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The Effect of Temperature on Cu-K-In-Se Thin Films
Films of Cu-K-In-Se were co-evaporated at varied K/(K+Cu) compositions and substrate temperatures (with constant (K+Cu)/In ~ 0.85). Increased Na composition on the substrate's surface and decreased growth temperature were both found to favor Cu1-xKxInSe2 (CKIS) alloy formation, relative to mixed-phase CuInSe2 + KInSe...
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Simulations of the Solar System's Early Dynamical Evolution with a Self-Gravitating Planetesimal Disk
Over the course of last decade, the Nice model has dramatically changed our view of the solar system's formation and early evolution. Within the context of this model, a transient period of planet-planet scattering is triggered by gravitational interactions between the giant planets and a massive primordial planetesi...
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On weak Fraisse limits
Using the natural action of $S_\infty$ we show that a countable hereditary class $\cC$ of finitely generated structures has the joint embedding property (JEP) and the weak amalgamation property (WAP) if and only if there is a structure $M$ whose isomorphism type is comeager in the space of all countable, infinitely g...
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Promoting Saving for College Through Data Science
The cost of attending college has been steadily rising and in 10 years is estimated to reach $140,000 for a 4-year public university. Recent surveys estimate just over half of US families are saving for college. State-operated 529 college savings plans are an effective way for families to plan and save for future col...
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Rotation Blurring: Use of Artificial Blurring to Reduce Cybersickness in Virtual Reality First Person Shooters
Users of Virtual Reality (VR) systems often experience vection, the perception of self-motion in the absence of any physical movement. While vection helps to improve presence in VR, it often leads to a form of motion sickness called cybersickness. Cybersickness is a major deterrent to large scale adoption of VR. Prio...
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Comparative Benchmarking of Causal Discovery Techniques
In this paper we present a comprehensive view of prominent causal discovery algorithms, categorized into two main categories (1) assuming acyclic and no latent variables, and (2) allowing both cycles and latent variables, along with experimental results comparing them from three perspectives: (a) structural accuracy,...
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Sensitivity of Love and quasi-Rayleigh waves to model parameters
We examine the sensitivity of the Love and the quasi-Rayleigh waves to model parameters. Both waves are guided waves that propagate in the same model of an elastic layer above an elastic halfspace. We study their dispersion curves without any simplifying assumptions, beyond the standard approach of elasticity theory ...
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The image size of iterated rational maps over finite fields
Let $\varphi:\mathbb{F}_q\to\mathbb{F}_q$ be a rational map on a fixed finite field. We give explicit asymptotic formulas for the size of image sets $\varphi^n(\mathbb{F}_q)$ as a function of $n$. This is done by using properties of the Galois groups of iterated maps, whose connection to the question of the size of i...
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Noncommutative modular symbols and Eisenstein series
We form real-analytic Eisenstein series twisted by Manin's noncommutative modular symbols. After developing their basic properties, these series are shown to have meromorphic continuations to the entire complex plane and satisfy functional equations in some cases. This theory neatly contains and generalizes earlier w...
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Some rigidity characterizations on critical metrics for quadratic curvature functionals
We study closed $n$-dimensional manifolds of which the metrics are critical for quadratic curvature functionals involving the Ricci curvature, the scalar curvature and the Riemannian curvature tensor on the space of Riemannian metrics with unit volume. Under some additional integral conditions, we classify such manif...
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Profinite completions of Burnside-type quotients of surface groups
Using quantum representations of mapping class groups we prove that profinite completions of Burnside-type surface group quotients are not virtually prosolvable, in general. Further, we construct infinitely many finite simple characteristic quotients of surface groups.
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Learning Infinite RBMs with Frank-Wolfe
In this work, we propose an infinite restricted Boltzmann machine~(RBM), whose maximum likelihood estimation~(MLE) corresponds to a constrained convex optimization. We consider the Frank-Wolfe algorithm to solve the program, which provides a sparse solution that can be interpreted as inserting a hidden unit at each i...
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New low-mass eclipsing binary systems in Praesepe discovered by K2
We present the discovery of four low-mass ($M<0.6$ $M_\odot$) eclipsing binary (EB) systems in the sub-Gyr old Praesepe open cluster using Kepler/K2 time-series photometry and Keck/HIRES spectroscopy. We present a new Gaussian process eclipsing binary model, GP-EBOP, as well as a method of simultaneously determining ...
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The impact of the halide cage on the electronic properties of fully inorganic caesium lead halide perovskites
Perovskite solar cells with record power conversion efficiency are fabricated by alloying both hybrid and fully inorganic compounds. While the basic electronic properties of the hybrid perovskites are now well understood, key electronic parameters for solar cell performance, such as the exciton binding energy of full...
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Discovery of Giant Radio Galaxies from NVSS: Radio & Infrared Properties
Giant radio galaxies (GRGs) are one of the largest astrophysical sources in the Universe with an overall projected linear size of ~0.7 Mpc or more. Last six decades of radio astronomy research has led to the detection of thousands of radio galaxies. But only ~ 300 of them can be classified as GRGs. The reasons behind...
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SGD: General Analysis and Improved Rates
We propose a general yet simple theorem describing the convergence of SGD under the arbitrary sampling paradigm. Our theorem describes the convergence of an infinite array of variants of SGD, each of which is associated with a specific probability law governing the data selection rule used to form mini-batches. This ...
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Nonconvex One-bit Single-label Multi-label Learning
We study an extreme scenario in multi-label learning where each training instance is endowed with a single one-bit label out of multiple labels. We formulate this problem as a non-trivial special case of one-bit rank-one matrix sensing and develop an efficient non-convex algorithm based on alternating power iteration...
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Two Categories of Indoor Interactive Dynamics of a Large-scale Human Population in a WiFi covered university campus
To explore large-scale population indoor interactions, we analyze 18,715 users' WiFi access logs recorded in a Chinese university campus during 3 months, and define two categories of human interactions, the event interaction (EI) and the temporal interaction (TI). The EI helps construct a transmission graph, and the ...
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Robust estimators for generalized linear models with a dispersion parameter
Highly robust and efficient estimators for the generalized linear model with a dispersion parameter are proposed. The estimators are based on three steps. In the first step the maximum rank correlation estimator is used to consistently estimate the slopes up to a scale factor. In the second step, the scale factor, th...
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Abstracting Event-Driven Systems with Lifestate Rules
We present lifestate rules--an approach for abstracting event-driven object protocols. Developing applications against event-driven software frameworks is notoriously difficult. One reason why is that to create functioning applications, developers must know about and understand the complex protocols that abstract the...
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Boltzmann Encoded Adversarial Machines
Restricted Boltzmann Machines (RBMs) are a class of generative neural network that are typically trained to maximize a log-likelihood objective function. We argue that likelihood-based training strategies may fail because the objective does not sufficiently penalize models that place a high probability in regions whe...
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A Non-Gaussian, Nonparametric Structure for Gene-Gene and Gene-Environment Interactions in Case-Control Studies Based on Hierarchies of Dirichlet Processes
It is becoming increasingly clear that complex interactions among genes and environmental factors play crucial roles in triggering complex diseases. Thus, understanding such interactions is vital, which is possible only through statistical models that adequately account for such intricate, albeit unknown, dependence ...
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An Efficient Bayesian Robust Principal Component Regression
Principal component regression is a linear regression model with principal components as regressors. This type of modelling is particularly useful for prediction in settings with high-dimensional covariates. Surprisingly, the existing literature treating of Bayesian approaches is relatively sparse. In this paper, we ...
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Bayesian estimation from few samples: community detection and related problems
We propose an efficient meta-algorithm for Bayesian estimation problems that is based on low-degree polynomials, semidefinite programming, and tensor decomposition. The algorithm is inspired by recent lower bound constructions for sum-of-squares and related to the method of moments. Our focus is on sample complexity ...
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X-ray Transform and Boundary Rigidity for Asymptotically Hyperbolic Manifolds
We consider the boundary rigidity problem for asymptotically hyperbolic manifolds. We show injectivity of the X-ray transform in several cases and consider the non-linear inverse problem which consists of recovering a metric from boundary measurements for the geodesic flow.
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Pinning of longitudinal phonons in holographic spontaneous helices
We consider the spontaneous breaking of translational symmetry and identify the associated Goldstone mode -- a longitudinal phonon -- in a holographic model with Bianchi VII helical symmetry. For the first time in holography, we observe the pinning of this mode after introducing a source for explicit breaking compati...
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An Extension of the Method of Brackets. Part 1
The method of brackets is an efficient method for the evaluation of a large class of definite integrals on the half-line. It is based on a small collection of rules, some of which are heuristic. The extension discussed here is based on the concepts of null and divergent series. These are formal representations of fun...
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optimParallel: an R Package Providing Parallel Versions of the Gradient-Based Optimization Methods of optim()
The R package optimParallel provides a parallel version of the gradient-based optimization methods of optim(). The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce optimization times. We introduce the R package and illustra...
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The barocaloric effect: A Spin-off of the Discovery of High-Temperature Superconductivity
Some key results obtained in joint research projects with Alex Müller are summarized, concentrating on the invention of the barocaloric effect and its application for cooling as well as on important findings in the field of high-temperature superconductivity resulting from neutron scattering experiments.
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Spontaneous currents in superconducting systems with strong spin-orbit coupling
We show that Rashba spin-orbit coupling at the interface between a superconductor and a ferromagnet should produce a spontaneous current in the atomic thickness region near the interface. This current is counter-balanced by the superconducting screening current flowing in the region of the width of the London penetra...
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Catching Loosely Synchronized Behavior in Face of Camouflage
Fraud has severely detrimental impacts on the business of social networks and other online applications. A user can become a fake celebrity by purchasing "zombie followers" on Twitter. A merchant can boost his reputation through fake reviews on Amazon. This phenomenon also conspicuously exists on Facebook, Yelp and T...
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Three-dimensional localized-delocalized Anderson transition in the time domain
Systems which can spontaneously reveal periodic evolution are dubbed time crystals. This is in analogy with space crystals that display periodic behavior in configuration space. While space crystals are modelled with the help of space periodic potentials, crystalline phenomena in time can be modelled by periodically ...
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Socio-economic constraints to maximum human lifespan
The analysis of the demographic transition of the past century and a half, using both empirical data and mathematical models, has rendered a wealth of well-established facts, including the dramatic increases in life expectancy. Despite these insights, such analyses have also occasionally triggered debates which spill...
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SD-CPS: Taming the Challenges of Cyber-Physical Systems with a Software-Defined Approach
Cyber-Physical Systems (CPS) revolutionize various application domains with integration and interoperability of networking, computing systems, and mechanical devices. Due to its scale and variety, CPS faces a number of challenges and opens up a few research questions in terms of management, fault-tolerance, and scala...
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Dual Ore's theorem on distributive intervals of finite groups
This paper gives a self-contained group-theoretic proof of a dual version of a theorem of Ore on distributive intervals of finite groups. We deduce a bridge between combinatorics and representations in finite group theory.
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A construction of trivial Beltrami coefficients
A measurable function $\mu$ on the unit disk $\mathbb{D}$ of the complex plane with $\|\mu\|_\infty<1$ is sometimes called a Beltrami coefficient. We say that $\mu$ is trivial if it is the complex dilatation $f_{\bar z}/f_z$ of a quasiconformal automorphism $f$ of $\mathbb{D}$ satisfying the trivial boundary conditio...
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A GNS construction of three-dimensional abelian Dijkgraaf-Witten theories
We give a detailed account of the so-called "universal construction" that aims to extend invariants of closed manifolds, possibly with additional structure, to topological field theories and show that it amounts to a generalization of the GNS construction. We apply this construction to an invariant defined in terms o...
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Long-path formation in a deformed microdisk laser
An asymmetric resonant cavity can be used to form a path that is much longer than the cavity size. We demonstrate this capability for a deformed microdisk equipped with two linear waveguides, by constructing a multiply reflected periodic orbit that is confined by total internal reflection within the deformed microdis...
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Spitzer Observations of Large Amplitude Variables in the LMC and IC 1613
The 3.6 and 4.5 micron characteristics of AGB variables in the LMC and IC1613 are discussed. For C-rich Mira variables there is a very clear period-luminosity-colour relation, where the [3.6]-[4.5] colour is associated with the amount of circumstellar material and correlated with the pulsation amplitude. The [4.5] pe...
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Synergistic Team Composition
Effective teams are crucial for organisations, especially in environments that require teams to be constantly created and dismantled, such as software development, scientific experiments, crowd-sourcing, or the classroom. Key factors influencing team performance are competences and personality of team members. Hence,...
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The inverse hull of 0-left cancellative semigroups
Given a semigroup S with zero, which is left-cancellative in the sense that st=sr \neq 0 implies that t=r, we construct an inverse semigroup called the inverse hull of S, denoted H(S). When S admits least common multiples, in a precise sense defined below, we study the idempotent semilattice of H(S), with a focus on ...
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The Hadamard Determinant Inequality - Extensions to Operators on a Hilbert Space
A generalization of classical determinant inequalities like Hadamard's inequality and Fischer's inequality is studied. For a version of the inequalities originally proved by Arveson for positive operators in von Neumann algebras with a tracial state, we give a different proof. We also improve and generalize to the se...
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Experimental results : Reinforcement Learning of POMDPs using Spectral Methods
We propose a new reinforcement learning algorithm for partially observable Markov decision processes (POMDP) based on spectral decomposition methods. While spectral methods have been previously employed for consistent learning of (passive) latent variable models such as hidden Markov models, POMDPs are more challengi...
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Discreteness of silting objects and t-structures in triangulated categories
We introduce the notion of ST-pairs of triangulated subcategories, a prototypical example of which is the pair of the bound homotopy category and the bound derived category of a finite-dimensional algebra. For an ST-pair $(\C,\D)$, we construct an order-preserving map from silting objects in $\C$ to bounded $t$-struc...
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Sketching the order of events
We introduce features for massive data streams. These stream features can be thought of as "ordered moments" and generalize stream sketches from "moments of order one" to "ordered moments of arbitrary order". In analogy to classic moments, they have theoretical guarantees such as universality that are important for l...
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Deep Multi-view Learning to Rank
We study the problem of learning to rank from multiple sources. Though multi-view learning and learning to rank have been studied extensively leading to a wide range of applications, multi-view learning to rank as a synergy of both topics has received little attention. The aim of the paper is to propose a composite r...
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One-Shot Visual Imitation Learning via Meta-Learning
In order for a robot to be a generalist that can perform a wide range of jobs, it must be able to acquire a wide variety of skills quickly and efficiently in complex unstructured environments. High-capacity models such as deep neural networks can enable a robot to represent complex skills, but learning each skill fro...
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Second variation of Selberg zeta functions and curvature asymptotics
We give an explicit formula for the second variation of the logarithm of the Selberg zeta function, $Z(s)$, on Teichmüller space. We then use this formula to determine the asymptotic behavior as $s \to \infty$ of the second variation. As a consequence, we determine the signature of the Hessian of $\log Z(s)$ for suff...
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Magnetic Fields Threading Black Holes: restrictions from general relativity and implications for astrophysical black holes
The idea that black hole spin is instrumental in the generation of powerful jets in active galactic nuclei and X-ray binaries is arguably the most contentious claim in black hole astrophysics. Because jets are thought to originate in the context of electromagnetism, and the modeling of Maxwell fields in curved spacet...
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Distance covariance for stochastic processes
The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analogs of the distance covariance for two stochastic processes defined on some inter...
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On Nonparametric Regression using Data Depth
We investigate nonparametric regression methods based on statistical depth functions. These nonparametric regression procedures can be used in situations, where the response is multivariate and the covariate is a random element in a metric space. This includes regression with functional covariate as a special case. O...
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A Backward Simulation Method for Stochastic Optimal Control Problems
A number of optimal decision problems with uncertainty can be formulated into a stochastic optimal control framework. The Least-Squares Monte Carlo (LSMC) algorithm is a popular numerical method to approach solutions of such stochastic control problems as analytical solutions are not tractable in general. This paper ...
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Damped Posterior Linearization Filter
The iterated posterior linearization filter (IPLF) is an algorithm for Bayesian state estimation that performs the measurement update using iterative statistical regression. The main result behind IPLF is that the posterior approximation is more accurate when the statistical regression of measurement function is done...
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Status updates through M/G/1/1 queues with HARQ
We consider a system where randomly generated updates are to be transmitted to a monitor, but only a single update can be in the transmission service at a time. Therefore, the source has to prioritize between the two possible transmission policies: preempting the current update or discarding the new one. We consider ...
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A mean score method for sensitivity analysis to departures from the missing at random assumption in randomised trials
Most analyses of randomised trials with incomplete outcomes make untestable assumptions and should therefore be subjected to sensitivity analyses. However, methods for sensitivity analyses are not widely used. We propose a mean score approach for exploring global sensitivity to departures from missing at random or ot...
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On the union complexity of families of axis-parallel rectangles with a low packing number
Let R be a family of n axis-parallel rectangles with packing number p-1, meaning that among any p of the rectangles, there are two with a non-empty intersection. We show that the union complexity of R is at most O(n+p^2), and that the (<=k)-level complexity of R is at most O(kn+k^2p^2). Both upper bounds are tight.
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Using photo-ionisation models to derive carbon and oxygen gas-phase abundances in the rest UV
We present a new method to derive oxygen and carbon abundances using the ultraviolet (UV) lines emitted by the gas-phase ionised by massive stars. The method is based on the comparison of the nebular emission-line ratios with those predicted by a large grid of photo-ionisation models. Given the large dispersion in th...
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A Probabilistic Framework for Location Inference from Social Media
We study the extent to which we can infer users' geographical locations from social media. Location inference from social media can benefit many applications, such as disaster management, targeted advertising, and news content tailoring. In recent years, a number of algorithms have been proposed for identifying user ...
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The Novel ABALONE Photosensor Technology: 4-Year Long Tests of Vacuum Integrity, Internal Pumping and Afterpulsing
The ABALONE Photosensor Technology (U.S. Patent 9064678 2015) has the capability of supplanting the expensive 80 year old Photomultiplier Tube (PMT) manufacture by providing a modern and cost effective alternative product. An ABALONE Photosensor comprises only three monolithic glass components, sealed together by our...
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Multi-robot Dubins Coverage with Autonomous Surface Vehicles
In large scale coverage operations, such as marine exploration or aerial monitoring, single robot approaches are not ideal, as they may take too long to cover a large area. In such scenarios, multi-robot approaches are preferable. Furthermore, several real world vehicles are non-holonomic, but can be modeled using Du...
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New Fairness Metrics for Recommendation that Embrace Differences
We study fairness in collaborative-filtering recommender systems, which are sensitive to discrimination that exists in historical data. Biased data can lead collaborative filtering methods to make unfair predictions against minority groups of users. We identify the insufficiency of existing fairness metrics and propo...
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Graph heat mixture model learning
Graph inference methods have recently attracted a great interest from the scientific community, due to the large value they bring in data interpretation and analysis. However, most of the available state-of-the-art methods focus on scenarios where all available data can be explained through the same graph, or groups ...
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Technical Report: Reactive Navigation in Partially Known Non-Convex Environments
This paper presents a provably correct method for robot navigation in 2D environments cluttered with familiar but unexpected non-convex, star-shaped obstacles as well as completely unknown, convex obstacles. We presuppose a limited range onboard sensor, capable of recognizing, localizing and (leveraging ideas from co...
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Automatic smoothness detection of the resolvent Krylov subspace method for the approximation of $C_0$-semigroups
The resolvent Krylov subspace method builds approximations to operator functions $f(A)$ times a vector $v$. For the semigroup and related operator functions, this method is proved to possess the favorable property that the convergence is automatically faster when the vector $v$ is smoother. The user of the method doe...
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On the observability of Pauli crystals
The best known manifestation of the Fermi-Dirac statistics is the Pauli exclusion principle: no two identical fermions can occupy the same one-particle state. This principle enforces high order correlations in systems of many identical fermions and is responsible for a particular geometric arrangement of trapped part...
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Interpolating Between Choices for the Approximate Intermediate Value Theorem
This paper proves the approximate intermediate value theorem, constructively and from notably weak hypotheses: from pointwise rather than uniform continuity, without assuming that reals are presented with rational approximants, and without using countable choice. The theorem is that if a pointwise continuous function...
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HAZMAT II: Ultraviolet Variability of Low-Mass Stars in the GALEX Archive
The ultraviolet (UV) light from a host star influences a planet's atmospheric photochemistry and will affect interpretations of exoplanetary spectra from future missions like the James Webb Space Telescope. These effects will be particularly critical in the study of planetary atmospheres around M dwarfs, including Ea...
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Exactly solvable Schrödinger equation with double-well potential for hydrogen bond
We construct a double-well potential for which the Schrödinger equation can be exactly solved via reducing to the confluent Heun's one. Thus the wave function is expressed via the confluent Heun's function. The latter is tabulated in {\sl {Maple}} so that the obtained solution is easily treated. The potential is infi...
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The co-evolution of emotional well-being with weak and strong friendship ties
Social ties are strongly related to well-being. But what characterizes this relationship? This study investigates social mechanisms explaining how social ties affect well-being through social integration and social influence, and how well-being affects social ties through social selection. We hypothesize that highly ...
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A magnetic version of the Smilansky-Solomyak model
We analyze spectral properties of two mutually related families of magnetic Schrödinger operators, $H_{\mathrm{Sm}}(A)=(i \nabla +A)^2+\omega^2 y^2+\lambda y \delta(x)$ and $H(A)=(i \nabla +A)^2+\omega^2 y^2+ \lambda y^2 V(x y)$ in $L^2(R^2)$, with the parameters $\omega>0$ and $\lambda<0$, where $A$ is a vector pote...
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John-Nirenberg Radius and Collapse in Conformal Geometry
Given a positive function $u\in W^{1,n}$, we define its John-Nirenberg radius at point $x$ to be the supreme of the radius such that $\int_{B_t}|\nabla\log u|^n<\epsilon_0^n$ when $n>2$, and $\int_{B_t}|\nabla u|^2<\epsilon_0^2$ when $n=2$. We will show that for a collapsing sequence in a fixed conformal class under ...
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Deep Prior
The recent literature on deep learning offers new tools to learn a rich probability distribution over high dimensional data such as images or sounds. In this work we investigate the possibility of learning the prior distribution over neural network parameters using such tools. Our resulting variational Bayes algorith...
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Generalized two-dimensional linear discriminant analysis with regularization
Recent advances show that two-dimensional linear discriminant analysis (2DLDA) is a successful matrix based dimensionality reduction method. However, 2DLDA may encounter the singularity issue theoretically and the sensitivity to outliers. In this paper, a generalized Lp-norm 2DLDA framework with regularization for an...
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Time-Frequency Audio Features for Speech-Music Classification
Distinct striation patterns are observed in the spectrograms of speech and music. This motivated us to propose three novel time-frequency features for speech-music classification. These features are extracted in two stages. First, a preset number of prominent spectral peak locations are identified from the spectra of...
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Kinodynamic Planning on Constraint Manifolds
This paper presents a motion planner for systems subject to kinematic and dynamic constraints. The former appear when kinematic loops are present in the system, such as in parallel manipulators, in robots that cooperate to achieve a given task, or in situations involving contacts with the environment. The latter are ...
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Binary Classification from Positive-Confidence Data
Can we learn a binary classifier from only positive data, without any negative data or unlabeled data? We show that if one can equip positive data with confidence (positive-confidence), one can successfully learn a binary classifier, which we name positive-confidence (Pconf) classification. Our work is related to one...
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Skewing Methods for Variance-Stabilizing Local Linear Regression Estimation
It is well-known that kernel regression estimators do not produce a constant estimator variance over a domain. To correct this problem, Nishida and Kanazawa (2015) proposed a variance-stabilizing (VS) local variable bandwidth for Local Linear (LL) regression estimator. In contrast, Choi and Hall (1998) proposed the s...
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Proximodistal Exploration in Motor Learning as an Emergent Property of Optimization
To harness the complexity of their high-dimensional bodies during sensorimotor development, infants are guided by patterns of freezing and freeing of degrees of freedom. For instance, when learning to reach, infants free the degrees of freedom in their arm proximodistally, i.e. from joints that are closer to the body...
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Near-optimal Sample Complexity Bounds for Robust Learning of Gaussians Mixtures via Compression Schemes
We prove that $\tilde{\Theta}(k d^2 / \varepsilon^2)$ samples are necessary and sufficient for learning a mixture of $k$ Gaussians in $\mathbb{R}^d$, up to error $\varepsilon$ in total variation distance. This improves both the known upper bounds and lower bounds for this problem. For mixtures of axis-aligned Gaussia...
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Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME
We present a heuristic based algorithm to induce \textit{nonmonotonic} logic programs that will explain the behavior of XGBoost trained classifiers. We use the technique based on the LIME approach to locally select the most important features contributing to the classification decision. Then, in order to explain the ...
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Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation
Manipulation of deformable objects, such as ropes and cloth, is an important but challenging problem in robotics. We present a learning-based system where a robot takes as input a sequence of images of a human manipulating a rope from an initial to goal configuration, and outputs a sequence of actions that can reprod...
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Online learning with graph-structured feedback against adaptive adversaries
We derive upper and lower bounds for the policy regret of $T$-round online learning problems with graph-structured feedback, where the adversary is nonoblivious but assumed to have a bounded memory. We obtain upper bounds of $\widetilde O(T^{2/3})$ and $\widetilde O(T^{3/4})$ for strongly-observable and weakly-observ...
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Dynamical characteristics of electromagnetic field under conditions of total reflection
The dynamical characteristics of electromagnetic fields include energy, momentum, angular momentum (spin) and helicity. We analyze their spatial distributions near the planar interface between two transparent and non-dispersive media, when the incident monochromatic plane wave with arbitrary polarization is totally r...
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Functors induced by Cauchy extension of C*-algebras
In this paper we give three functors $\mathfrak{P}$, $[\cdot]_K$ and $\mathfrak{F}$ on the category of C$^\ast$-algebras. The functor $\mathfrak{P}$ assigns to each C$^\ast$-algebra $\mathcal{A}$ a pre-C$^\ast$-algebra $\mathfrak{P}(\mathcal{A})$ with completion $[\mathcal{A}]_K$. The functor $[\cdot]_K$ assigns to e...
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Hierarchically cocompact classifying spaces for mapping class groups of surfaces
We define the notion of a hierarchically cocompact classifying space for a family of subgroups of a group. Our main application is to show that the mapping class group $\mbox{Mod}(S)$ of any connected oriented compact surface $S$, possibly with punctures and boundary components and with negative Euler characteristic ...
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A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
An explosion of high-throughput DNA sequencing in the past decade has led to a surge of interest in population-scale inference with whole-genome data. Recent work in population genetics has centered on designing inference methods for relatively simple model classes, and few scalable general-purpose inference techniqu...
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Coherent single-atom superradiance
Quantum effects, prevalent in the microscopic scale, generally elusive in macroscopic systems due to dissipation and decoherence. Quantum phenomena in large systems emerge only when particles are strongly correlated as in superconductors and superfluids. Cooperative interaction of correlated atoms with electromagneti...
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Recurrent Deterministic Policy Gradient Method for Bipedal Locomotion on Rough Terrain Challenge
This paper presents a deep learning framework that is capable of solving partially observable locomotion tasks based on our novel interpretation of Recurrent Deterministic Policy Gradient (RDPG). We study on bias of sampled error measure and its variance induced by the partial observability of environment and subtraj...
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