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Cyclicity in weighted $\ell^p$ spaces
We study the cyclicity in weighted $\ell^p(\mathbb{Z})$ spaces. For $p \geq 1$ and $\beta \geq 0$, let $\ell^p\_\beta(\mathbb{Z})$ be the space of sequences $u=(u\_n)\_{n\in \mathbb{Z}}$ such that $(u\_n |n|^{\beta})\in \ell^p(\mathbb{Z}) $. We obtain both necessary conditions and sufficient conditions for $u$ to be ...
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State-Space Identification of Unmanned Helicopter Dynamics using Invasive Weed Optimization Algorithm on Flight Data
In order to achieve a good level of autonomy in unmanned helicopters, an accurate replication of vehicle dynamics is required, which is achievable through precise mathematical modeling. This paper aims to identify a parametric state-space system for an unmanned helicopter to a good level of accuracy using Invasive We...
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Latent Molecular Optimization for Targeted Therapeutic Design
We devise an approach for targeted molecular design, a problem of interest in computational drug discovery: given a target protein site, we wish to generate a chemical with both high binding affinity to the target and satisfactory pharmacological properties. This problem is made difficult by the enormity and discrete...
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SlimNets: An Exploration of Deep Model Compression and Acceleration
Deep neural networks have achieved increasingly accurate results on a wide variety of complex tasks. However, much of this improvement is due to the growing use and availability of computational resources (e.g use of GPUs, more layers, more parameters, etc). Most state-of-the-art deep networks, despite performing wel...
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An alternative axiomization of $N$-pseudospaces
We give a new axiomatization of the N-pseudospace, studied in [2] (Tent(2014)) and [1] (Baudisch,Martin-Pizarro,Ziegler(2014)) based on the zigzags introduced in [2]. We also present a more detailed account of the characterization of forking given in [2].
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Symmetry breaking in linear multipole traps
Radiofrequency multipole traps have been used for some decades in cold collision experiments, and are gaining interest for precision spectroscopy due to their low mi-cromotion contribution, and the predicted unusual cold-ion structures. However, the experimental realisation is not yet fully controlled, and open quest...
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Deep Spatio-temporal Manifold Network for Action Recognition
Visual data such as videos are often sampled from complex manifold. We propose leveraging the manifold structure to constrain the deep action feature learning, thereby minimizing the intra-class variations in the feature space and alleviating the over-fitting problem. Considering that manifold can be transferred, lay...
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Gas dynamics in strong centrifugal fields
Dynamics of waves generated by scopes in gas centrifuges (GC) for isotope separation is considered. The centrifugal acceleration in the GC reaches values of the order of $10^6$g. The centrifugal and Coriolis forces modify essentially the conventional sound waves. Three families of the waves with different polarisatio...
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Robust Stackelberg controllability for the Navier--Stokes equations
In this paper we deal with a robust Stackelberg strategy for the Navier--Stokes system. The scheme is based in considering a robust control problem for the "follower control" and its associated disturbance function. Afterwards, we consider the notion of Stackelberg optimization (which is associated to the "leader con...
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Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications
In this paper, five different approaches for reduced-order modeling of brittle fracture in geomaterials, specifically concrete, are presented and compared. Four of the five methods rely on machine learning (ML) algorithms to approximate important aspects of the brittle fracture problem. In addition to the ML algorith...
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A ferroelectric quantum phase transition inside the superconducting dome of Sr$_{1-x}$Ca$_{x}$TiO$_{3-δ}$
SrTiO$_{3}$, a quantum paraelectric, becomes a metal with a superconducting instability after removal of an extremely small number of oxygen atoms. It turns into a ferroelectric upon substitution of a tiny fraction of strontium atoms with calcium. The two orders may be accidental neighbors or intimately connected, as...
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First Detection of Equatorial Dark Dust Lane in a Protostellar Disk at Submillimeter Wavelength
In the earliest (so-called "Class 0") phase of sunlike (low-mass) star formation, circumstellar disks are expected to form, feeding the protostars. However, such disks are difficult to resolve spatially because of their small sizes. Moreover, there are theoretical difficulties in producing such disks in the earliest ...
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General dynamical properties of cosmological models with nonminimal kinetic coupling
We consider cosmological dynamics in the theory of gravity with the scalar field possessing the nonminimal kinetic coupling to curvature given as $\eta G^{\mu\nu}\phi_{,\mu}\phi_{,\nu}$, where $\eta$ is an arbitrary coupling parameter, and the scalar potential $V(\phi)$ which assumed to be as general as possible. Wit...
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Extensions of interpolation between the arithmetic-geometric mean inequality for matrices
In this paper, we present some extensions of interpolation between the arithmetic-geometric means inequality. Among other inequalities, it is shown that if $A, B, X$ are $n\times n$ matrices, then \begin{align*} \|AXB^*\|^2\leq\|f_1(A^*A)Xg_1(B^*B)\|\,\|f_2(A^*A)Xg_2(B^*B)\|, \end{align*} where $f_1,f_2,g_1,g_2$ are ...
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Machine Translation in Indian Languages: Challenges and Resolution
English to Indian language machine translation poses the challenge of structural and morphological divergence. This paper describes English to Indian language statistical machine translation using pre-ordering and suffix separation. The pre-ordering uses rules to transfer the structure of the source sentences prior t...
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Retrieving the quantitative chemical information at nanoscale from SEM EDX measurements by Machine Learning
The quantitative composition of metal alloy nanowires on InSb(001) semiconductor surface and gold nanostructures on germanium surface is determined by blind source separation (BSS) machine learning (ML) method using non negative matrix factorization (NMF) from energy dispersive X-ray spectroscopy (EDX) spectrum image...
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Decomposition Strategies for Constructive Preference Elicitation
We tackle the problem of constructive preference elicitation, that is the problem of learning user preferences over very large decision problems, involving a combinatorial space of possible outcomes. In this setting, the suggested configuration is synthesized on-the-fly by solving a constrained optimization problem, ...
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Vibrational surface EELS probes confined Fuchs-Kliewer modes
Recently, two reports have demonstrated the amazing possibility to probe vibrational excitations from nanoparticles with a spatial resolution much smaller than the corresponding free-space phonon wavelength using electron energy loss spectroscopy (EELS). While Lagos et al. evidenced a strong spatial and spectral modu...
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The Dependence of the Mass-Metallicity Relation on Large Scale Environment
We examine the relation between gas-phase oxygen abundance and stellar mass---the MZ relation---as a function of the large scale galaxy environment parameterized by the local density. The dependence of the MZ relation on the environment is small. The metallicity where the MZ relation saturates and the slope of the MZ...
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Proof of Riemann hypothesis, Generalized Riemann hypothesis and Ramanujan $τ$-Dirichlet series hypothesis
We prove Riemann hypothesis, Generalized Riemann hypothesis, and Ramanujan $\tau$-Dirichlet series hypothesis. Method is to show the convexity of function which has zeros critical strip the same as zeta function.
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A second order primal-dual method for nonsmooth convex composite optimization
We develop a second order primal-dual method for optimization problems in which the objective function is given by the sum of a strongly convex twice differentiable term and a possibly nondifferentiable convex regularizer. After introducing an auxiliary variable, we utilize the proximal operator of the nonsmooth regu...
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PDD Graph: Bridging Electronic Medical Records and Biomedical Knowledge Graphs via Entity Linking
Electronic medical records contain multi-format electronic medical data that consist of an abundance of medical knowledge. Facing with patient's symptoms, experienced caregivers make right medical decisions based on their professional knowledge that accurately grasps relationships between symptoms, diagnosis and corr...
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A new algorithm for fast generalized DFTs
We give an new arithmetic algorithm to compute the generalized Discrete Fourier Transform (DFT) over finite groups $G$. The new algorithm uses $O(|G|^{\omega/2 + o(1)})$ operations to compute the generalized DFT over finite groups of Lie type, including the linear, orthogonal, and symplectic families and their varian...
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Critical magnetic fields in a superconductor coupled to a superfluid
We study a superconductor that is coupled to a superfluid via density and derivative couplings. Starting from a Lagrangian for two complex scalar fields, we derive a temperature-dependent Ginzburg-Landau potential, which is then used to compute the phase diagram at nonzero temperature and external magnetic field. Thi...
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The bubble algebras at roots of unity
We introduce multi-colour partition algebras $P_{n,m}(\delta_0, ..., \delta_{m-1})$, which are generalization of both bubble algebras and partition algebras, then define the bubble algebra $T_{n,m}(\delta_0, ..., \delta_{m-1})$ as a sub-algebra of the algebra $P_{n,m}(\delta_0, ..., \delta_{m-1})$. We present general...
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Self-Repairing Energy Materials: Sine Qua Non for a Sustainable Future
Materials are central to our way of life and future. Energy and materials as resources are connected and the obvious connections between them are the energy cost of materials and the materials cost of energy. For both of these resilience of the materials is critical; thus a major goal of future chemistry should be to...
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Design and performance of dual-polarization lumped-element kinetic inductance detectors for millimeter-wave polarimetry
Lumped-element kinetic inductance detectors (LEKIDs) are an attractive technology for millimeter-wave observations that require large arrays of extremely low-noise detectors. We designed, fabricated and characterized 64-element (128 LEKID) arrays of horn-coupled, dual-polarization LEKIDs optimized for ground-based CM...
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An overview of knot Floer homology
Knot Floer homology is an invariant for knots discovered by the authors and, independently, Jacob Rasmussen. The discovery of this invariant grew naturally out of studying how a certain three-manifold invariant, Heegaard Floer homology, changes as the three-manifold undergoes Dehn surgery along a knot. Since its orig...
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Mathematical model of immune response to hepatitis B
A new detailed mathematical model for dynamics of immune response to hepatitis B is proposed, which takes into account contributions from innate and adaptive immune responses, as well as cytokines. Stability analysis of different steady states is performed to identify parameter regions where the model exhibits cleara...
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Controlling Stray Electric Fields on an Atom Chip for Rydberg Experiments
Experiments handling Rydberg atoms near surfaces must necessarily deal with the high sensitivity of Rydberg atoms to (stray) electric fields that typically emanate from adsorbates on the surface. We demonstrate a method to modify and reduce the stray electric field by changing the adsorbates distribution. We use one ...
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Unseen Progenitors of Luminous High-z Quasars in the R_h=ct Universe
Quasars at high redshift provide direct information on the mass growth of supermassive black holes and, in turn, yield important clues about how the Universe evolved since the first (Pop III) stars started forming. Yet even basic questions regarding the seeds of these objects and their growth mechanism remain unanswe...
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Decoding the spectroscopic features and timescales of aqueous proton defects
Acid solutions exhibit a variety of complex structural and dynamical features arising from the presence of multiple interacting reactive proton defects and counterions. However, disentangling the transient structural motifs of proton defects in the water hydrogen bond network and the mechanisms for their interconvers...
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MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment
Generating music has a few notable differences from generating images and videos. First, music is an art of time, necessitating a temporal model. Second, music is usually composed of multiple instruments/tracks with their own temporal dynamics, but collectively they unfold over time interdependently. Lastly, musical ...
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Geometric Analysis of Synchronization in Neuronal Networks with Global Inhibition and Coupling Delays
We study synaptically coupled neuronal networks to identify the role of coupling delays in network's synchronized behaviors. We consider a network of excitable, relaxation oscillator neurons where two distinct populations, one excitatory and one inhibitory, are coupled and interact with each other. The excitatory pop...
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Model predictive trajectory optimization and tracking for on-road autonomous vehicles
Motion planning for autonomous vehicles requires spatio-temporal motion plans (i.e. state trajectories) to account for dynamic obstacles. This requires a trajectory tracking control process which faithfully tracks planned trajectories. In this paper, a control scheme is presented which first optimizes a planned traje...
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A Toolbox For Property Checking From Simulation Using Incremental SAT (Extended Abstract)
We present a tool that primarily supports the ability to check bounded properties starting from a sequence of states in a run. The target design is compiled into an AIGNET which is then selectively and iteratively translated into an incremental SAT instance in which clauses are added for new terms and simplified by t...
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Machine Learning of Linear Differential Equations using Gaussian Processes
This work leverages recent advances in probabilistic machine learning to discover conservation laws expressed by parametric linear equations. Such equations involve, but are not limited to, ordinary and partial differential, integro-differential, and fractional order operators. Here, Gaussian process priors are modif...
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YouTube-8M Video Understanding Challenge Approach and Applications
This paper introduces the YouTube-8M Video Understanding Challenge hosted as a Kaggle competition and also describes my approach to experimenting with various models. For each of my experiments, I provide the score result as well as possible improvements to be made. Towards the end of the paper, I discuss the various...
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Temporal Pattern Discovery for Accurate Sepsis Diagnosis in ICU Patients
Sepsis is a condition caused by the body's overwhelming and life-threatening response to infection, which can lead to tissue damage, organ failure, and finally death. Common signs and symptoms include fever, increased heart rate, increased breathing rate, and confusion. Sepsis is difficult to predict, diagnose, and t...
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On the use of the energy probability distribution zeros in the study of phase transitions
This contribution is devoted to cover some technical aspects related to the use of the recently proposed energy probability distribution zeros in the study of phase transitions. This method is based on the partial knowledge of the partition function zeros and has been shown to be extremely efficient to precisely loca...
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Visibility-based Power Spectrum Estimation for Low-Frequency Radio Interferometric Observations
We present a visibility based estimator namely, the Tapered Gridded Estimator (TGE) to estimate the power spectrum of the diffuse sky signal. The TGE has three novel features. First, the estimator uses gridded visibilities to estimate the power spectrum which is computationally much faster than individually correlati...
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Archiving Software Surrogates on the Web for Future Reference
Software has long been established as an essential aspect of the scientific process in mathematics and other disciplines. However, reliably referencing software in scientific publications is still challenging for various reasons. A crucial factor is that software dynamics with temporal versions or states are difficul...
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Exact Formulas for the Generalized Sum-of-Divisors Functions
We prove new exact formulas for the generalized sum-of-divisors functions. The formulas for $\sigma_{\alpha}(x)$ when $\alpha \in \mathbb{C}$ is fixed and $x \geq 1$ involves a finite sum over all of the prime factors $n \leq x$ and terms involving the $r$-order harmonic number sequences. The generalized harmonic num...
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On addition theorems related to elliptic integrals
This paper provides some explicit formulas related to addition theorems for elliptic integrals $\int_0^x dt/R(t)$, where $R(t)$ is the square root from a polynomial of degree 4. These integrals are related to complex elliptic genera and are motivated by Euler's addition theorem for elliptic integrals of the first kin...
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Manuscripts in Time and Space: Experiments in Scriptometrics on an Old French Corpus
Witnesses of medieval literary texts, preserved in manuscript, are layered objects , being almost exclusively copies of copies. This results in multiple and hard to distinguish linguistic strata -- the author's scripta interacting with the scriptae of the various scribes -- in a context where literary written languag...
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Vertical Bifacial Solar Farms: Physics, Design, and Global Optimization
There have been sustained interest in bifacial solar cell technology since 1980s, with prospects of 30-50% increase in the output power from a stand-alone single panel. Moreover, a vertical bifacial panel reduces dust accumulation and provides two output peaks during the day, with the second peak aligned to the peak ...
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Maximally Correlated Principal Component Analysis
In the era of big data, reducing data dimensionality is critical in many areas of science. Widely used Principal Component Analysis (PCA) addresses this problem by computing a low dimensional data embedding that maximally explain variance of the data. However, PCA has two major weaknesses. Firstly, it only considers ...
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$\mathcal{G}$-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
It is well known that neural networks with rectified linear units (ReLU) activation functions are positively scale-invariant. Conventional algorithms like stochastic gradient descent optimize the neural networks in the vector space of weights, which is, however, not positively scale-invariant. This mismatch may lead ...
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Fantastic deductive systems in probability theory on generalizations of fuzzy structures
The aim of this paper is to introduce the notion of fantastic deductive systems on generalizations of fuzzy structures, and to emphasize their role in the probability theory on these algebras. We give a characterization of commutative pseudo-BE algebras and we generalize an axiom system consisting of four identities ...
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Bayesian Learning of Consumer Preferences for Residential Demand Response
In coming years residential consumers will face real-time electricity tariffs with energy prices varying day to day, and effective energy saving will require automation - a recommender system, which learns consumer's preferences from her actions. A consumer chooses a scenario of home appliance use to balance her comf...
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Beyond the Hazard Rate: More Perturbation Algorithms for Adversarial Multi-armed Bandits
Recent work on follow the perturbed leader (FTPL) algorithms for the adversarial multi-armed bandit problem has highlighted the role of the hazard rate of the distribution generating the perturbations. Assuming that the hazard rate is bounded, it is possible to provide regret analyses for a variety of FTPL algorithms...
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Calculation of the bulk modulus of mixed ionic crystal NH_4Cl_{1-x}Br_x
The ammonium halides present an interesting system for study in view of their polymorphism and the possible internal rotation of the ammonium ion. The static properties of the mixed ionic crystal NH$_4$Cl$_{1-x}$Br$_x$ have been recently investigated, using three-body potential model (TDPM) by the application of Vega...
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Hyers-Ulam stability of elliptic Möbius difference equation
The linear fractional map $ f(z) = \frac{az+ b}{cz + d} $ on the Riemann sphere with complex coefficients $ ad-bc \neq 0 $ is called Möbius map. If $ f $ satisfies $ ad-bc=1 $ and $ -2<a+d<2 $, then $ f $ is called $\textit{elliptic}$ Möbius map. Let $ \{ b_n \}_{n \in \mathbb{N}_0} $ be the solution of the elliptic ...
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Diffeological, Frölicher, and Differential Spaces
Differential calculus on Euclidean spaces has many generalisations. In particular, on a set $X$, a diffeological structure is given by maps from open subsets of Euclidean spaces to $X$, a differential structure is given by maps from $X$ to $\mathbb{R}$, and a Frölicher structure is given by maps from $\mathbb{R}$ to ...
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Elementary abelian subgroups in some special p-groups
Let $P$ be a finite $p$-group and $p$ be an odd prime. Let $\mathcal{A}_p(P)_{\geq2}$ be a poset consisting of elementary abelian subgroups of rank at least 2. If the derived subgroup $P'\cong C_p\times C_p$, then the spheres occurring in $\mathcal{A}_p(P)_{\geq2}$ all have the same dimension.
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Learning Plannable Representations with Causal InfoGAN
In recent years, deep generative models have been shown to 'imagine' convincing high-dimensional observations such as images, audio, and even video, learning directly from raw data. In this work, we ask how to imagine goal-directed visual plans -- a plausible sequence of observations that transition a dynamical syste...
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SGD Learns the Conjugate Kernel Class of the Network
We show that the standard stochastic gradient decent (SGD) algorithm is guaranteed to learn, in polynomial time, a function that is competitive with the best function in the conjugate kernel space of the network, as defined in Daniely, Frostig and Singer. The result holds for log-depth networks from a rich family of ...
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Towards information optimal simulation of partial differential equations
Most simulation schemes for partial differential equations (PDEs) focus on minimizing a simple error norm of a discretized version of a field. This paper takes a fundamentally different approach; the discretized field is interpreted as data providing information about a real physical field that is unknown. This infor...
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Verifying Quantum Programs: From Quipper to QPMC
In this paper we present a translation from the quantum programming language Quipper to the QPMC model checker, with the main aim of verifying Quipper programs. Quipper is an embedded functional programming language for quantum computation. It is above all a circuit description language, for this reason it uses the v...
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Topological semimetal state and field-induced Fermi surface reconstruction in antiferromagnetic monopnictide NdSb
We report the experimental realization of Dirac semimetal state in NdSb, a material with antiferromagnetic ground state. The occurrence of topological semimetal state has been well supported by our band structure calculations and the experimental observation of chiral anomaly induced negative magnetoresistance. A fie...
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Joint Prediction of Depths, Normals and Surface Curvature from RGB Images using CNNs
Understanding the 3D structure of a scene is of vital importance, when it comes to developing fully autonomous robots. To this end, we present a novel deep learning based framework that estimates depth, surface normals and surface curvature by only using a single RGB image. To the best of our knowledge this is the fi...
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Motif and Hypergraph Correlation Clustering
Motivated by applications in social and biological network analysis, we introduce a new form of agnostic clustering termed~\emph{motif correlation clustering}, which aims to minimize the cost of clustering errors associated with both edges and higher-order network structures. The problem may be succinctly described a...
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Adversarial Imitation via Variational Inverse Reinforcement Learning
We consider a problem of learning the reward and policy from expert examples under unknown dynamics in high-dimensional scenarios. Our proposed method builds on the framework of generative adversarial networks and introduces the empowerment-regularized maximum-entropy inverse reinforcement learning to learn near-opti...
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Intrinsically motivated reinforcement learning for human-robot interaction in the real-world
For a natural social human-robot interaction, it is essential for a robot to learn the human-like social skills. However, learning such skills is notoriously hard due to the limited availability of direct instructions from people to teach a robot. In this paper, we propose an intrinsically motivated reinforcement lea...
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Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
We propose a novel online alternating minimization (AltMin) algorithm for training deep neural networks, provide theoretical convergence guarantees and demonstrate its advantages on several classification tasks as compared both to standard backpropagation with stochastic gradient descent (backprop-SGD) and to offline...
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Minimax Game-Theoretic Approach to Multiscale H-infinity Optimal Filtering
Sensing in complex systems requires large-scale information exchange and on-the-go communications over heterogeneous networks and integrated processing platforms. Many networked cyber-physical systems exhibit hierarchical infrastructures of information flows, which naturally leads to a multi-level tree-like informati...
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Topology of irrationally indifferent attractors
We study the attractors of a class of holomorphic systems with an irrationally indifferent fixed point. We prove a trichotomy for the topology of the attractor based on the arithmetic of the rotation number at the fixed point. That is, the attractor is either a Jordan curve, a one-sided hairy circle, or a Cantor bouq...
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Crystalline Soda Can Metamaterial exhibiting Graphene-like Dispersion at subwavelength scale
Graphene, a honeycomb lattice of carbon atoms ruled by tight-binding interaction, exhibits extraordinary electronic properties due to the presence of Dirac cones within its band structure. These intriguing singularities have naturally motivated the discovery of their classical analogues. In this work, we present a ge...
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Modeling Retinal Ganglion Cell Population Activity with Restricted Boltzmann Machines
The retina is a complex nervous system which encodes visual stimuli before higher order processing occurs in the visual cortex. In this study we evaluated whether information about the stimuli received by the retina can be retrieved from the firing rate distribution of Retinal Ganglion Cells (RGCs), exploiting High-D...
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Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics
In {\em{Holm}, Proc. Roy. Soc. A 471 (2015)} stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian f...
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A general framework for solving convex optimization problems involving the sum of three convex functions
In this paper, we consider solving a class of convex optimization problem which minimizes the sum of three convex functions $f(x)+g(x)+h(Bx)$, where $f(x)$ is differentiable with a Lipschitz continuous gradient, $g(x)$ and $h(x)$ have a closed-form expression of their proximity operators and $B$ is a bounded linear o...
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Testing isotropy in the Two Micron All-Sky redshift survey with information entropy
We use information entropy to test the isotropy in the nearby galaxy distribution mapped by the Two Micron All-Sky redshift survey (2MRS). We find that the galaxy distribution is highly anisotropic on small scales. The radial anisotropy gradually decreases with increasing length scales and the observed anisotropy is ...
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VEGAS: A VST Early-type GAlaxy Survey. II. Photometric study of giant ellipticals and their stellar halos
Observations of diffuse starlight in the outskirts of galaxies are thought to be a fundamental source of constraints on the cosmological context of galaxy assembly in the $\Lambda$CDM model. Such observations are not trivial because of the extreme faintness of such regions. In this work, we investigate the photometri...
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Homological dimension formulas for trivial extension algebras
Let $A= \Lambda \oplus C$ be a trivial extension algebra. The aim of this paper is to establish formulas for the projective dimension and the injective dimension for a certain class of $A$-modules which is expressed by using the derived functors $- \otimes^{\mathbb{L}}_{\Lambda}C$ and $\mathbb{R}\text{Hom}_{\Lambda}(...
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Spread of entanglement in a Sachdev-Ye-Kitaev chain
We study the spread of Rényi entropy between two halves of a Sachdev-Ye-Kitaev (SYK) chain of Majorana fermions, prepared in a thermofield double (TFD) state. The SYK chain model is a model of chaotic many-body systems, which describes a one-dimensional lattice of Majorana fermions, with spatially local random quarti...
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The weak order on integer posets
We explore lattice structures on integer binary relations (i.e. binary relations on the set $\{1, 2, \dots, n\}$ for a fixed integer $n$) and on integer posets (i.e. partial orders on the set $\{1, 2, \dots, n\}$ for a fixed integer $n$). We first observe that the weak order on the symmetric group naturally extends t...
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Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization
Undetected overfitting can occur when there are significant redundancies between training and validation data. We describe AVE, a new measure of training-validation redundancy for ligand-based classification problems that accounts for the similarity amongst inactive molecules as well as active. We investigated seven ...
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Inverse dispersion method for calculation of complex photonic band diagram and $\cal{PT}$-symmetry
We suggest an inverse dispersion method for calculating photonic band diagram for materials with arbitrary frequency-dependent dielectric functions. The method is able to calculate the complex wave vector for a given frequency by solving the eigenvalue problem with a non-Hermitian operator. The analogy with $\cal{PT}...
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MmWave vehicle-to-infrastructure communication: Analysis of urban microcellular networks
Vehicle-to-infrastructure (V2I) communication may provide high data rates to vehicles via millimeter-wave (mmWave) microcellular networks. This paper uses stochastic geometry to analyze the coverage of urban mmWave microcellular networks. Prior work used a pathloss model with a line-of-sight probability function base...
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Resolvent estimates on asymptotically cylindrical manifolds and on the half line
Manifolds with infinite cylindrical ends have continuous spectrum of increasing multiplicity as energy grows, and in general embedded resonances and eigenvalues can accumulate at infinity. However, we prove that if geodesic trapping is sufficiently mild, then such an accumulation is ruled out, and moreover the cutoff...
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On absolutely normal and continued fraction normal numbers
We give a construction of a real number that is normal to all integer bases and continued fraction normal. The computation of the first n digits of its continued fraction expansion performs in the order of n^4 mathematical operations. The construction works by defining successive refinements of appropriate subinterva...
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Combinatorial properties of the G-degree
A strong interaction is known to exist between edge-colored graphs (which encode PL pseudo-manifolds of arbitrary dimension) and random tensor models (as a possible approach to the study of Quantum Gravity). The key tool is the {\it G-degree} of the involved graphs, which drives the {\it $1/N$ expansion} in the tenso...
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Quasi-random Agents for Image Transition and Animation
Quasi-random walks show similar features as standard random walks, but with much less randomness. We utilize this established model from discrete mathematics and show how agents carrying out quasi-random walks can be used for image transition and animation. The key idea is to generalize the notion of quasi-random wal...
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Deep Speaker Verification: Do We Need End to End?
End-to-end learning treats the entire system as a whole adaptable black box, which, if sufficient data are available, may learn a system that works very well for the target task. This principle has recently been applied to several prototype research on speaker verification (SV), where the feature learning and classif...
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Neural Models for Documents with Metadata
Most real-world document collections involve various types of metadata, such as author, source, and date, and yet the most commonly-used approaches to modeling text corpora ignore this information. While specialized models have been developed for particular applications, few are widely used in practice, as customizat...
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Single Image Super-resolution via a Lightweight Residual Convolutional Neural Network
Recent years have witnessed great success of convolutional neural network (CNN) for various problems both in low and high level visions. Especially noteworthy is the residual network which was originally proposed to handle high-level vision problems and enjoys several merits. This paper aims to extend the merits of r...
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Variations of BPS structure and a large rank limit
We study a class of flat bundles, of finite rank $N$, which arise naturally from the Donaldson-Thomas theory of a Calabi-Yau threefold $X$ via the notion of a variation of BPS structure. We prove that in a large $N$ limit their flat sections converge to the solutions to certain infinite dimensional Riemann-Hilbert pr...
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Strong correlations between the exponent $α$ and the particle number for a Renyi-monoatomic gas in Gibbs' statistical mechanics
Appealing to the 1902 Gibbs' formalism for classical statistical mechanics (SM), the first SM axiomatic theory ever that successfully explained equilibrium thermodynamics, we will here show that already at the classical level there is a strong correlation between the Renyi's exponent $\alpha$ and the number of partic...
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Smooth backfitting of proportional hazards -- A new approach projecting survival data
Smooth backfitting has proven to have a number of theoretical and practical advantages in structured regression. Smooth backfitting projects the data down onto the structured space of interest providing a direct link between data and estimator. This paper introduces the ideas of smooth backfitting to survival analysi...
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Trajectory Tracking Using Motion Primitives for the Purcell's Swimmer
Locomotion at low Reynolds numbers is a topic of growing interest, spurred by its various engineering and medical applications. This paper presents a novel prototype and a locomotion algorithm for the 3-link planar Purcell's swimmer based on Lie algebraic notions. The kinematic model based on Cox theory of the protot...
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Data Analysis in Multimedia Quality Assessment: Revisiting the Statistical Tests
Assessment of multimedia quality relies heavily on subjective assessment, and is typically done by human subjects in the form of preferences or continuous ratings. Such data is crucial for analysis of different multimedia processing algorithms as well as validation of objective (computational) methods for the said pu...
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Removing Isolated Zeroes by Homotopy
Suppose that the inverse image of the zero vector by a continuous map $f:{\mathbb R}^n\to{\mathbb R}^q$ has an isolated point $P$. There is a local obstruction to removing this isolated zero by a small perturbation, generalizing the notion of index for vector fields, the $q=n$ case. The existence of a continuous map ...
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Continuous cocycle superrigidity for coinduced actions and relative ends
We prove that certain coinduced actions for an inclusion of finitely generated commensurated subgroups with relative one end are continuous cocycle superrigid actions. We also show the necessity for the relative end assumption.
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Brownian ratchets: How stronger thermal noise can reduce diffusion
We study diffusion properties of an inertial Brownian motor moving on a ratchet substrate, i.e. a periodic structure with broken reflection symmetry. The motor is driven by an unbiased time-periodic symmetric force which takes the system out of thermal equilibrium. For selected parameter sets, the system is in a non-...
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Wadge Degrees of $ω$-Languages of Petri Nets
We prove that $\omega$-languages of (non-deterministic) Petri nets and $\omega$-languages of (non-deterministic) Turing machines have the same topological complexity: the Borel and Wadge hierarchies of the class of $\omega$-languages of (non-deterministic) Petri nets are equal to the Borel and Wadge hierarchies of th...
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Is there agreement on the prestige of scholarly book publishers in the Humanities? DELPHI over survey results
Despite having an important role supporting assessment processes, criticism towards evaluation systems and the categorizations used are frequent. Considering the acceptance by the scientific community as an essential issue for using rankings or categorizations in research evaluation, the aim of this paper is testing ...
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Zero-Shot Recognition using Dual Visual-Semantic Mapping Paths
Zero-shot recognition aims to accurately recognize objects of unseen classes by using a shared visual-semantic mapping between the image feature space and the semantic embedding space. This mapping is learned on training data of seen classes and is expected to have transfer ability to unseen classes. In this paper, w...
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Spoken Language Biomarkers for Detecting Cognitive Impairment
In this study we developed an automated system that evaluates speech and language features from audio recordings of neuropsychological examinations of 92 subjects in the Framingham Heart Study. A total of 265 features were used in an elastic-net regularized binomial logistic regression model to classify the presence ...
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Performance Analysis of Low-Density Parity-Check Codes over 2D Interference Channels via Density Evolution
The theoretical analysis of detection and decoding of low-density parity-check (LDPC) codes transmitted over channels with two-dimensional (2D) interference and additive white Gaussian noise (AWGN) is provided in this paper. The detection and decoding system adopts the joint iterative detection and decoding scheme (J...
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Novel market approach for locally balancing renewable energy production and flexible demand
Future electricity distribution grids will host a considerable share of variable renewable energy sources and local storage resources. Moreover, they will face new load structures due for example to the growth of the electric vehicle market. These trends raise the need for new paradigms for distribution grids operati...
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