title
stringlengths
7
239
abstract
stringlengths
7
2.76k
cs
int64
0
1
phy
int64
0
1
math
int64
0
1
stat
int64
0
1
quantitative biology
int64
0
1
quantitative finance
int64
0
1
Spitzer Secondary Eclipses of Qatar-1b
Previous secondary eclipse observations of the hot Jupiter Qatar-1b in the Ks band suggest that it may have an unusually high day side temperature, indicative of minimal heat redistribution. There have also been indications that the orbit may be slightly eccentric, possibly forced by another planet in the system. We ...
0
1
0
0
0
0
Dielectric response of Anderson and pseudogapped insulators
Using a combination of analytic and numerical methods, we study the polarizability of a (non-interacting) Anderson insulator in one, two, and three dimensions and demonstrate that, in a wide range of parameters, it scales proportionally to the square of the localization length, contrary to earlier claims based on the...
0
1
0
0
0
0
Epidemiological modeling of the 2005 French riots: a spreading wave and the role of contagion
As a large-scale instance of dramatic collective behaviour, the 2005 French riots started in a poor suburb of Paris, then spread in all of France, lasting about three weeks. Remarkably, although there were no displacements of rioters, the riot activity did travel. Access to daily national police data has allowed us t...
1
1
0
0
0
0
Option Pricing in Illiquid Markets with Jumps
The classical linear Black--Scholes model for pricing derivative securities is a popular model in financial industry. It relies on several restrictive assumptions such as completeness, and frictionless of the market as well as the assumption on the underlying asset price dynamics following a geometric Brownian motion...
0
0
0
0
0
1
A Knowledge-Based Analysis of the Blockchain Protocol
At the heart of the Bitcoin is a blockchain protocol, a protocol for achieving consensus on a public ledger that records bitcoin transactions. To the extent that a blockchain protocol is used for applications such as contract signing and making certain transactions (such as house sales) public, we need to understand ...
1
0
0
0
0
0
Convergence Analysis of Optimization Algorithms
The regret bound of an optimization algorithms is one of the basic criteria for evaluating the performance of the given algorithm. By inspecting the differences between the regret bounds of traditional algorithms and adaptive one, we provide a guide for choosing an optimizer with respect to the given data set and the...
1
0
1
1
0
0
On the combinatorics of the 2-class classification problem
A set of points $X = X_B \cup X_R \subseteq \mathbb{R}^d$ is linearly separable if the convex hulls of $X_B$ and $X_R$ are disjoint, hence there exists a hyperplane separating $X_B$ from $X_R$. Such a hyperplane provides a method for classifying new points, according to which side of the hyperplane the new points lie...
1
0
0
0
0
0
Laboratory evidence of dynamo amplification of magnetic fields in a turbulent plasma
Magnetic fields are ubiquitous in the Universe. Extragalactic disks, halos and clusters have consistently been shown, via diffuse radio-synchrotron emission and Faraday rotation measurements, to exhibit magnetic field strengths ranging from a few nG to tens of $\mu$G. The energy density of these fields is typically c...
0
1
0
0
0
0
Radiating Electron Interaction with Multiple Colliding Electromagnetic Waves: Random Walk Trajectories, Levy Flights, Limit Circles, and Attractors (Survey of the Structurally Determinate Patterns)
The multiple colliding laser pulse concept formulated in Ref. [1] is beneficial for achieving an extremely high amplitude of coherent electromagnetic field. Since the topology of electric and magnetic fields oscillating in time of multiple colliding laser pulses is far from trivial and the radiation friction effects ...
0
1
0
0
0
0
Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks
In this work, we jointly address the problem of text detection and recognition in natural scene images based on convolutional recurrent neural networks. We propose a unified network that simultaneously localizes and recognizes text with a single forward pass, avoiding intermediate processes like image cropping and fe...
1
0
0
0
0
0
Evidence for OH or H2O on the surface of 433 Eros and 1036 Ganymed
Water and hydroxyl, once thought to be found only in the primitive airless bodies that formed beyond roughly 2.5-3 AU, have recently been detected on the Moon and Vesta, which both have surfaces dominated by evolved, non-primitive compositions. In both these cases, the water/OH is thought to be exogenic, either broug...
0
1
0
0
0
0
Jump Locations of Jump-Diffusion Processes with State-Dependent Rates
We propose a general framework for studying jump-diffusion systems driven by both Gaussian noise and a jump process with state-dependent intensity. Of particular natural interest are the jump locations: the system evaluated at the jump times. However, the state-dependence of the jump rate provides direct coupling bet...
0
1
1
0
0
0
Dust evolution with active galactic nucleus feedback in elliptical galaxies
We have recently suggested that dust growth in the cold gas phase dominates the dust abundance in elliptical galaxies while dust is efficiently destroyed in the hot X-ray emitting plasma (hot gas). In order to understand the dust evolution in elliptical galaxies, we construct a simple model that includes dust growth ...
0
1
0
0
0
0
Generative-Discriminative Variational Model for Visual Recognition
The paradigm shift from shallow classifiers with hand-crafted features to end-to-end trainable deep learning models has shown significant improvements on supervised learning tasks. Despite the promising power of deep neural networks (DNN), how to alleviate overfitting during training has been a research topic of inte...
1
0
0
0
0
0
PCA-Initialized Deep Neural Networks Applied To Document Image Analysis
In this paper, we present a novel approach for initializing deep neural networks, i.e., by turning PCA into neural layers. Usually, the initialization of the weights of a deep neural network is done in one of the three following ways: 1) with random values, 2) layer-wise, usually as Deep Belief Network or as auto-enc...
1
0
0
1
0
0
On a frame theoretic measure of quality of LTI systems
It is of practical significance to define the notion of a measure of quality of a control system, i.e., a quantitative extension of the classical notion of controllability. In this article we demonstrate that the three standard measures of quality involving the trace, minimum eigenvalue, and the determinant of the co...
1
0
1
0
0
0
Fuzzy Clustering Data Given on the Ordinal Scale Based on Membership and Likelihood Functions Sharing
A task of clustering data given in the ordinal scale under conditions of overlapping clusters has been considered. It's proposed to use an approach based on memberhsip and likelihood functions sharing. A number of performed experiments proved effectiveness of the proposed method. The proposed method is characterized ...
1
0
0
0
0
0
The ALICE O2 common driver for the C-RORC and CRU read-out cards
ALICE (A Large Ion Collider Experiment) is the heavy-ion detector designed to study the strongly interacting state of matter realized in relativistic heavy-ion collisions at the CERN Large Hadron Collider (LHC). A major upgrade of the experiment is planned during the 2019-2020 long shutdown. In order to cope with a d...
1
1
0
0
0
0
Adapting control policies from simulation to reality using a pairwise loss
This paper proposes an approach to domain transfer based on a pairwise loss function that helps transfer control policies learned in simulation onto a real robot. We explore the idea in the context of a 'category level' manipulation task where a control policy is learned that enables a robot to perform a mating task ...
1
0
0
0
0
0
Evidence against a supervoid causing the CMB Cold Spot
We report the results of the 2dF-VST ATLAS Cold Spot galaxy redshift survey (2CSz) based on imaging from VST ATLAS and spectroscopy from 2dF AAOmega over the core of the CMB Cold Spot. We sparsely surveyed the inner 5$^{\circ}$ radius of the Cold Spot to a limit of $i_{AB} \le 19.2$, sampling $\sim7000$ galaxies at $...
0
1
0
0
0
0
How to Produce an Arbitrarily Small Tensor to Scalar Ratio
We construct a toy a model which demonstrates that large field single scalar inflation can produce an arbitrarily small scalar to tensor ratio in the window of e-foldings recoverable from CMB experiments. This is done by generalizing the $\alpha$-attractor models to allow the potential to approach a constant as rapid...
0
1
0
0
0
0
Meta Learning Shared Hierarchies
We develop a metalearning approach for learning hierarchically structured policies, improving sample efficiency on unseen tasks through the use of shared primitives---policies that are executed for large numbers of timesteps. Specifically, a set of primitives are shared within a distribution of tasks, and are switche...
1
0
0
0
0
0
The bright-star masks for the HSC-SSP survey
We present the procedure to build and validate the bright-star masks for the Hyper-Suprime-Cam Strategic Subaru Proposal (HSC-SSP) survey. To identify and mask the saturated stars in the full HSC-SSP footprint, we rely on the Gaia and Tycho-2 star catalogues. We first assemble a pure star catalogue down to $G_{\rm Ga...
0
1
0
0
0
0
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
Generative adversarial networks (GANs) are a family of generative models that do not minimize a single training criterion. Unlike other generative models, the data distribution is learned via a game between a generator (the generative model) and a discriminator (a teacher providing training signal) that each minimize...
1
0
0
1
0
0
The Tensor Memory Hypothesis
We discuss memory models which are based on tensor decompositions using latent representations of entities and events. We show how episodic memory and semantic memory can be realized and discuss how new memory traces can be generated from sensory input: Existing memories are the basis for perception and new memories ...
1
0
0
1
0
0
Data-driven Approach to Measuring the Level of Press Freedom Using Media Attention Diversity from Unfiltered News
Published by Reporters Without Borders every year, the Press Freedom Index (PFI) reflects the fear and tension in the newsroom pushed by the government and private sectors. While the PFI is invaluable in monitoring media environments worldwide, the current survey-based method has inherent limitations to updates in te...
1
0
0
0
0
0
Advanced Satellite-based Frequency Transfer at the 10^{-16} Level
Advanced satellite-based frequency transfers by TWCP and IPPP have been performed between NICT and KRISS. We confirm that the disagreement between them is less than 1x10^{-16} at an averaging time of several days. Additionally, an intercontinental frequency ratio measurement of Sr and Yb optical lattice clocks was di...
0
1
0
0
0
0
Are there needles in a moving haystack? Adaptive sensing for detection of dynamically evolving signals
In this paper we investigate the problem of detecting dynamically evolving signals. We model the signal as an $n$ dimensional vector that is either zero or has $s$ non-zero components. At each time step $t\in \mathbb{N}$ the non-zero components change their location independently with probability $p$. The statistical...
0
0
1
1
0
0
Image-based Localization using Hourglass Networks
In this paper, we propose an encoder-decoder convolutional neural network (CNN) architecture for estimating camera pose (orientation and location) from a single RGB-image. The architecture has a hourglass shape consisting of a chain of convolution and up-convolution layers followed by a regression part. The up-convol...
1
0
0
0
0
0
Suppression of Decoherence of a Spin-Boson System by Time-Periodic Control
We consider a finite-dimensional quantum system coupled to the bosonic radiation field and subject to a time-periodic control operator. Assuming the validity of a certain dynamic decoupling condition we approximate the system's time evolution with respect to the non-interacting dynamics. For sufficiently small coupli...
0
0
1
0
0
0
Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations
The model-based control of building heating systems for energy saving encounters severe physical, mathematical and calibration difficulties in the numerous attempts that has been published until now. This topic is addressed here via a new model-free control setting, where the need of any mathematical description disa...
1
0
0
0
0
0
Trace Properties from Separation Logic Specifications
We propose a formal approach for relating abstract separation logic library specifications with the trace properties they enforce on interactions between a client and a library. Separation logic with abstract predicates enforces a resource discipline that constrains when and how calls may be made between a client and...
1
0
0
0
0
0
Estimation of Local Degree Distributions via Local Weighted Averaging and Monte Carlo Cross-Validation
Owing to their capability of summarising interactions between elements of a system, networks have become a common type of data in many fields. As networks can be inhomogeneous, in that different regions of the network may exhibit different topologies, an important topic concerns their local properties. This paper foc...
0
0
0
1
0
0
The ALMA Phasing System: A Beamforming Capability for Ultra-High-Resolution Science at (Sub)Millimeter Wavelengths
The Atacama Millimeter/submillimeter Array (ALMA) Phasing Project (APP) has developed and deployed the hardware and software necessary to coherently sum the signals of individual ALMA antennas and record the aggregate sum in Very Long Baseline Interferometry (VLBI) Data Exchange Format. These beamforming capabilities...
0
1
0
0
0
0
Signatures of two-step impurity mediated vortex lattice melting in Bose-Einstein Condensates
We simulate a rotating 2D BEC to study the melting of a vortex lattice in presence of random impurities. Impurities are introduced either through a protocol in which vortex lattice is produced in an impurity potential or first creating the vortex lattice in the absence of random pinning and then cranking up the (co-r...
0
1
0
0
0
0
Cycle Consistent Adversarial Denoising Network for Multiphase Coronary CT Angiography
In coronary CT angiography, a series of CT images are taken at different levels of radiation dose during the examination. Although this reduces the total radiation dose, the image quality during the low-dose phases is significantly degraded. To address this problem, here we propose a novel semi-supervised learning te...
0
0
0
1
0
0
The multidimensional truncated Moment Problem: Carathéodory Numbers
Let $\mathcal{A}$ be a finite-dimensional subspace of $C(\mathcal{X};\mathbb{R})$, where $\mathcal{X}$ is a locally compact Hausdorff space, and $\mathsf{A}=\{f_1,\dots,f_m\}$ a basis of $\mathcal{A}$. A sequence $s=(s_j)_{j=1}^m$ is called a moment sequence if $s_j=\int f_j(x) \, d\mu(x)$, $j=1,\dots,m$, for some po...
0
0
1
0
0
0
Inspiration, Captivation, and Misdirection: Emergent Properties in Networks of Online Navigation
The World Wide Web (WWW) has fundamentally changed the ways billions of people are able to access information. Thus, understanding how people seek information online is an important issue of study. Wikipedia is a hugely important part of information provision on the web, with hundreds of millions of users browsing an...
1
0
0
0
0
0
Multiphase Aluminum A356 Foam Formation Process Simulation Using Lattice Boltzmann Method
Shan-Chen model is a numerical scheme to simulate multiphase fluid flows using Lattice Boltzmann approach. The original Shan-Chen model suffers from inability to accurately predict behavior of air bubbles interacting in a non-aqueous fluid. In the present study, we extended the Shan-Chen model to take the effect of t...
1
1
0
0
0
0
Deformations of coisotropic submanifolds in Jacobi manifolds
In this thesis, we study the deformation problem of coisotropic submanifolds in Jacobi manifolds. In particular we attach two algebraic invariants to any coisotropic submanifold $S$ in a Jacobi manifold, namely the $L_\infty[1]$-algebra and the BFV-complex of $S$. Our construction generalizes and unifies analogous co...
0
0
1
0
0
0
Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets
The complexity of a learning task is increased by transformations in the input space that preserve class identity. Visual object recognition for example is affected by changes in viewpoint, scale, illumination or planar transformations. While drastically altering the visual appearance, these changes are orthogonal to...
1
0
0
1
0
0
Covering compact metric spaces greedily
A general greedy approach to construct coverings of compact metric spaces by metric balls is given and analyzed. The analysis is a continuous version of Chvatal's analysis of the greedy algorithm for the weighted set cover problem. The approach is demonstrated in an exemplary manner to construct efficient coverings o...
0
0
1
0
0
0
Gauge covariances and nonlinear optical responses
The formalism of the reduced density matrix is pursued in both length and velocity gauges of the perturbation to the crystal Hamiltonian. The covariant derivative is introduced as a convenient representation of the position operator. This allow us to write compact expressions for the reduced density matrix in any ord...
0
1
0
0
0
0
Quasi-Static Internal Magnetic Field Detected in the Pseudogap Phase of Bi$_{2+x}$Sr$_{2-x}$CaCu$_2$O$_{8+δ}$ by $μ$SR
We report muon spin relaxation ($\mu$SR) measurements of optimally-doped and overdoped Bi$_{2+x}$Sr$_{2-x}$CaCu$_2$O$_{8+\delta}$ (Bi2212) single crystals that reveal the presence of a weak temperature-dependent quasi-static internal magnetic field of electronic origin in the superconducting (SC) and pseudogap (PG) p...
0
1
0
0
0
0
Auto-Encoding Total Correlation Explanation
Advances in unsupervised learning enable reconstruction and generation of samples from complex distributions, but this success is marred by the inscrutability of the representations learned. We propose an information-theoretic approach to characterizing disentanglement and dependence in representation learning using ...
0
0
0
1
0
0
A Characterisation of Open Bisimilarity using an Intuitionistic Modal Logic
Open bisimilarity is the original notion of bisimilarity to be introduced for the pi-calculus that is a congruence. In open bisimilarity, free names in processes are treated as variables that may be instantiated lazily; in contrast to early and late bisimilarity where free names are constants. We build on the establi...
1
0
0
0
0
0
Using data science as a community advocacy tool to promote equity in urban renewal programs: An analysis of Atlanta's Anti-Displacement Tax Fund
Cities across the United States are undergoing great transformation and urban growth. Data and data analysis has become an essential element of urban planning as cities use data to plan land use and development. One great challenge is to use the tools of data science to promote equity along with growth. The city of A...
1
0
0
0
0
0
General Bayesian inference schemes in infinite mixture models
Bayesian statistical models allow us to formalise our knowledge about the world and reason about our uncertainty, but there is a need for better procedures to accurately encode its complexity. One way to do so is through compositional models, which are formed by combining blocks consisting of simpler models. One can ...
0
0
0
1
0
0
Glow: Generative Flow with Invertible 1x1 Convolutions
Flow-based generative models (Dinh et al., 2014) are conceptually attractive due to tractability of the exact log-likelihood, tractability of exact latent-variable inference, and parallelizability of both training and synthesis. In this paper we propose Glow, a simple type of generative flow using an invertible 1x1 c...
0
0
0
1
0
0
Pohozaev identity for the fractional $p-$Laplacian on $\mathbb{R}^N$
By virtue of a suitable approximation argument, we prove a Pohozaev identity for nonlinear nonlocal problems on $\mathbb{R}^N$ involving the fractional $p-$Laplacian operator. Furthermore we provide an application of the identity to show that some relevant levels of the energy functional associated with the problem c...
0
0
1
0
0
0
A Second Wave of Expanders over Finite Fields
This is an expository survey on recent sum-product results in finite fields. We present a number of sum-product or "expander" results that say that if $|A| > p^{2/3}$ then some set determined by sums and product of elements of $A$ is nearly as large as possible, and if $|A|<p^{2/3}$ then the set in question is signif...
0
0
1
0
0
0
Homology of torus knots
Using the method of Elias-Hogancamp and combinatorics of toric braids we give an explicit formula for the triply graded Khovanov-Rozansky homology of an arbitrary torus knot, thereby proving some of the conjectures of Aganagic-Shakirov, Cherednik, Gorsky-Negut and Oblomkov-Rasmussen-Shende.
0
0
1
0
0
0
2-associahedra
For any $r\geq 1$ and $\mathbf{n} \in \mathbb{Z}_{\geq0}^r \setminus \{\mathbf0\}$ we construct a poset $W_{\mathbf{n}}$ called a 2-associahedron. The 2-associahedra arose in symplectic geometry, where they are expected to control maps between Fukaya categories of different symplectic manifolds. We prove that the com...
0
0
1
0
0
0
Anisotropic thermophoresis
Colloidal migration in temperature gradient is referred to as thermophoresis. In contrast to particles with spherical shape, we show that elongated colloids may have a thermophoretic response that varies with the colloid orientation. Remarkably, this can translate into a non-vanishing thermophoretic force in the dire...
0
1
0
0
0
0
Ultra-Wideband Aided Fast Localization and Mapping System
This paper proposes an ultra-wideband (UWB) aided localization and mapping system that leverages on inertial sensor and depth camera. Inspired by the fact that visual odometry (VO) system, regardless of its accuracy in the short term, still faces challenges with accumulated errors in the long run or under unfavourabl...
1
0
0
0
0
0
Modular Sensor Fusion for Semantic Segmentation
Sensor fusion is a fundamental process in robotic systems as it extends the perceptual range and increases robustness in real-world operations. Current multi-sensor deep learning based semantic segmentation approaches do not provide robustness to under-performing classes in one modality, or require a specific archite...
1
0
0
0
0
0
Thickness-dependent electronic and magnetic properties of $γ'$-Fe$_{\mathrm 4}$N atomic layers on Cu(001)
Growth, electronic and magnetic properties of $\gamma'$-Fe$_{4}$N atomic layers on Cu(001) are studied by scanning tunneling microscopy/spectroscopy and x-ray absorption spectroscopy/magnetic circular dichroism. A continuous film of ordered trilayer $\gamma'$-Fe$_{4}$N is obtained by Fe deposition under N$_{2}$ atmos...
0
1
0
0
0
0
Error Characterization, Mitigation, and Recovery in Flash Memory Based Solid-State Drives
NAND flash memory is ubiquitous in everyday life today because its capacity has continuously increased and cost has continuously decreased over decades. This positive growth is a result of two key trends: (1) effective process technology scaling, and (2) multi-level (e.g., MLC, TLC) cell data coding. Unfortunately, t...
1
0
0
0
0
0
Unified Backpropagation for Multi-Objective Deep Learning
A common practice in most of deep convolutional neural architectures is to employ fully-connected layers followed by Softmax activation to minimize cross-entropy loss for the sake of classification. Recent studies show that substitution or addition of the Softmax objective to the cost functions of support vector mach...
1
0
0
1
0
0
Information-Theoretic Representation Learning for Positive-Unlabeled Classification
Recent advances in weakly supervised classification allow us to train a classifier only from positive and unlabeled (PU) data. However, existing PU classification methods typically require an accurate estimate of the class-prior probability, which is a critical bottleneck particularly for high-dimensional data. This ...
1
0
0
1
0
0
Aspects of Chaitin's Omega
The halting probability of a Turing machine,also known as Chaitin's Omega, is an algorithmically random number with many interesting properties. Since Chaitin's seminal work, many popular expositions have appeared, mainly focusing on the metamathematical or philosophical significance of Omega (or debating against it)...
1
0
1
0
0
0
This Looks Like That: Deep Learning for Interpretable Image Recognition
When we are faced with challenging image classification tasks, we often explain our reasoning by dissecting the image, and pointing out prototypical aspects of one class or another. The mounting evidence for each of the classes helps us make our final decision. In this work, we introduce a deep network architecture t...
0
0
0
1
0
0
Deep Learning in the Automotive Industry: Applications and Tools
Deep Learning refers to a set of machine learning techniques that utilize neural networks with many hidden layers for tasks, such as image classification, speech recognition, language understanding. Deep learning has been proven to be very effective in these domains and is pervasively used by many Internet services. ...
1
0
0
0
0
0
Design, Engineering and Optimization of a Grid-Tie Multicell Inverter for Energy Storage Applications
Multilevel converters have found many applications within renewable energy systems thanks to their unique capability of generating multiple voltage levels. However, these converters need multiple DC sources and the voltage balancing over capacitors for these systems is cumbersome. In this work, a new grid-tie multice...
0
1
0
0
0
0
An infinitely differentiable function with compact support: Definition and properties
This is the English translation of my old paper 'Definición y estudio de una función indefinidamente diferenciable de soporte compacto', Rev. Real Acad. Ciencias 76 (1982) 21-38. In it a function (essentially Fabius function) is defined and given its main properties, including: unicity, interpretation as a probabilit...
0
0
1
0
0
0
Analysis of bacterial population growth using extended logistic growth model with distributed delay
In the present work, we develop a delayed Logistic growth model to study the effects of decontamination on the bacterial population in the ambient environment. Using the linear stability analysis, we study different case scenarios, where bacterial population may establish at the positive equilibrium or go extinct due...
0
0
0
0
1
0
Reverse Quantum Annealing Approach to Portfolio Optimization Problems
We investigate a hybrid quantum-classical solution method to the mean-variance portfolio optimization problems. Starting from real financial data statistics and following the principles of the Modern Portfolio Theory, we generate parametrized samples of portfolio optimization problems that can be related to quadratic...
0
0
0
0
0
1
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations
Modern deep transfer learning approaches have mainly focused on learning generic feature vectors from one task that are transferable to other tasks, such as word embeddings in language and pretrained convolutional features in vision. However, these approaches usually transfer unary features and largely ignore more st...
0
0
0
1
0
0
Learning to cluster in order to transfer across domains and tasks
This paper introduces a novel method to perform transfer learning across domains and tasks, formulating it as a problem of learning to cluster. The key insight is that, in addition to features, we can transfer similarity information and this is sufficient to learn a similarity function and clustering network to perfo...
1
0
0
0
0
0
Modeling Perceptual Aliasing in SLAM via Discrete-Continuous Graphical Models
Perceptual aliasing is one of the main causes of failure for Simultaneous Localization and Mapping (SLAM) systems operating in the wild. Perceptual aliasing is the phenomenon where different places generate a similar visual (or, in general, perceptual) footprint. This causes spurious measurements to be fed to the SLA...
1
0
0
0
0
0
Sparse distributed representation, hierarchy, critical periods, metaplasticity: the keys to lifelong fixed-time learning and best-match retrieval
Among the more important hallmarks of human intelligence, which any artificial general intelligence (AGI) should have, are the following. 1. It must be capable of on-line learning, including with single/few trials. 2. Memories/knowledge must be permanent over lifelong durations, safe from catastrophic forgetting. Som...
0
0
0
0
1
0
Efficient implementations of the modified Gram-Schmidt orthogonalization with a non-standard inner product
The modified Gram-Schmidt (MGS) orthogonalization is one of the most well-used algorithms for computing the thin QR factorization. MGS can be straightforwardly extended to a non-standard inner product with respect to a symmetric positive definite matrix $A$. For the thin QR factorization of an $m \times n$ matrix wit...
0
0
1
0
0
0
On the isoperimetric constant, covariance inequalities and $L_p$-Poincaré inequalities in dimension one
Firstly, we derive in dimension one a new covariance inequality of $L_{1}-L_{\infty}$ type that characterizes the isoperimetric constant as the best constant achieving the inequality. Secondly, we generalize our result to $L_{p}-L_{q}$ bounds for the covariance. Consequently, we recover Cheeger's inequality without u...
0
0
1
1
0
0
Faster arbitrary-precision dot product and matrix multiplication
We present algorithms for real and complex dot product and matrix multiplication in arbitrary-precision floating-point and ball arithmetic. A low-overhead dot product is implemented on the level of GMP limb arrays; it is about twice as fast as previous code in MPFR and Arb at precision up to several hundred bits. Up ...
1
0
0
0
0
0
Improving Distributed Representations of Tweets - Present and Future
Unsupervised representation learning for tweets is an important research field which helps in solving several business applications such as sentiment analysis, hashtag prediction, paraphrase detection and microblog ranking. A good tweet representation learning model must handle the idiosyncratic nature of tweets whic...
1
0
0
0
0
0
Tverberg-type theorems for matroids: A counterexample and a proof
Bárány, Kalai, and Meshulam recently obtained a topological Tverberg-type theorem for matroids, which guarantees multiple coincidences for continuous maps from a matroid complex to d-dimensional Euclidean space, if the matroid has sufficiently many disjoint bases. They make a conjecture on the connectivity of k-fold ...
0
0
1
0
0
0
Near-Perfect Conversion of a Propagating Plane Wave into a Surface Wave Using Metasurfaces
In this paper, theoretical and numerical studies of perfect/nearly-perfect conversion of a plane wave into a surface wave are presented. The problem of determining the electromagnetic properties of an inhomogeneous lossless boundary which would fully transform an incident plane wave into a surface wave propagating al...
0
1
0
0
0
0
A National Research Agenda for Intelligent Infrastructure
Our infrastructure touches the day-to-day life of each of our fellow citizens, and its capabilities, integrity and sustainability are crucial to the overall competitiveness and prosperity of our country. Unfortunately, the current state of U.S. infrastructure is not good: the American Society of Civil Engineers' late...
1
0
0
0
0
0
Surface Edge Explorer (SEE): Planning Next Best Views Directly from 3D Observations
Surveying 3D scenes is a common task in robotics. Systems can do so autonomously by iteratively obtaining measurements. This process of planning observations to improve the model of a scene is called Next Best View (NBV) planning. NBV planning approaches often use either volumetric (e.g., voxel grids) or surface (e.g...
1
0
0
0
0
0
N/O abundance ratios in gamma-ray burst and supernova host galaxies at z<4. Comparison with AGN, starburst and HII regions
The distribution of N/O abundance ratios calculated by the detailed modelling of different galaxy spectra at z<4 is investigated. Supernova (SN) and long gamma-ray-burst (LGRB) host galaxies cover different redshift domains. N/O in SN hosts increases due to secondary N production towards low z (0.01) accompanying the...
0
1
0
0
0
0
Baselines and a datasheet for the Cerema AWP dataset
This paper presents the recently published Cerema AWP (Adverse Weather Pedestrian) dataset for various machine learning tasks and its exports in machine learning friendly format. We explain why this dataset can be interesting (mainly because it is a greatly controlled and fully annotated image dataset) and present ba...
0
0
0
1
0
0
Characterizing Directed and Undirected Networks via Multidimensional Walks with Jumps
Estimating distributions of node characteristics (labels) such as number of connections or citizenship of users in a social network via edge and node sampling is a vital part of the study of complex networks. Due to its low cost, sampling via a random walk (RW) has been proposed as an attractive solution to this task...
1
1
0
0
0
0
Tensorial Recurrent Neural Networks for Longitudinal Data Analysis
Traditional Recurrent Neural Networks assume vectorized data as inputs. However many data from modern science and technology come in certain structures such as tensorial time series data. To apply the recurrent neural networks for this type of data, a vectorisation process is necessary, while such a vectorisation lea...
1
0
0
1
0
0
End-to-End Learning for the Deep Multivariate Probit Model
The multivariate probit model (MVP) is a popular classic model for studying binary responses of multiple entities. Nevertheless, the computational challenge of learning the MVP model, given that its likelihood involves integrating over a multidimensional constrained space of latent variables, significantly limits its...
0
0
0
1
0
0
Purity and separation for oriented matroids
Leclerc and Zelevinsky, motivated by the study of quasi-commuting quantum flag minors, introduced the notions of strongly separated and weakly separated collections. These notions are closely related to the theory of cluster algebras, to the combinatorics of the double Bruhat cells, and to the totally positive Grassm...
0
0
1
0
0
0
Random Manifolds have no Totally Geodesic Submanifolds
For $n\geq 4$ we show that generic closed Riemannian $n$-manifolds have no nontrivial totally geodesic submanifolds, answering a question of Spivak. An immediate consequence is a severe restriction on the isometry group of a generic Riemannian metric. Both results are widely believed to be true, but we are not aware ...
0
0
1
0
0
0
Kinematically Redundant Octahedral Motion Platform for Virtual Reality Simulations
We propose a novel design of a parallel manipulator of Stewart Gough type for virtual reality application of single individuals; i.e. an omni-directional treadmill is mounted on the motion platform in order to improve VR immersion by giving feedback to the human body. For this purpose we modify the well-known octahed...
1
0
0
0
0
0
Loss Max-Pooling for Semantic Image Segmentation
We introduce a novel loss max-pooling concept for handling imbalanced training data distributions, applicable as alternative loss layer in the context of deep neural networks for semantic image segmentation. Most real-world semantic segmentation datasets exhibit long tail distributions with few object categories comp...
1
0
0
1
0
0
Nonlinear Traveling Internal Waves in Depth-Varying Currents
In this work, we study the nonlinear traveling waves in density stratified fluids with depth varying shear currents. Beginning the formulation of the water-wave problem due to [1], we extend the work of [4] and [18] to examine the interface between two fluids of differing densities and varying linear shear. We derive...
0
1
0
0
0
0
Instabilities of Internal Gravity Wave Beams
Internal gravity waves play a primary role in geophysical fluids: they contribute significantly to mixing in the ocean and they redistribute energy and momentum in the middle atmosphere. Until recently, most studies were focused on plane wave solutions. However, these solutions are not a satisfactory description of m...
0
1
0
0
0
0
Multiphoton-Excited Fluorescence of Silicon-Vacancy Color Centers in Diamond
Silicon-vacancy color centers in nanodiamonds are promising as fluorescent labels for biological applications, with a narrow, non-bleaching emission line at 738\,nm. Two-photon excitation of this fluorescence offers the possibility of low-background detection at significant tissue depth with high three-dimensional sp...
0
1
0
0
0
0
Exploring Latent Semantic Factors to Find Useful Product Reviews
Online reviews provided by consumers are a valuable asset for e-Commerce platforms, influencing potential consumers in making purchasing decisions. However, these reviews are of varying quality, with the useful ones buried deep within a heap of non-informative reviews. In this work, we attempt to automatically identi...
1
0
0
1
0
0
Thermodynamically-consistent semi-classical $\ell$-changing rates
We compare the results of the semi-classical (SC) and quantum-mechanical (QM) formalisms for angular-momentum changing transitions in Rydberg atom collisions given by Vrinceanu & Flannery, J. Phys. B 34, L1 (2001), and Vrinceanu, Onofrio & Sadeghpour, ApJ 747, 56 (2012), with those of the SC formalism using a modifie...
0
1
0
0
0
0
A Fourier transform for the quantum Toda lattice
We introduce an algebraic Fourier transform for the quantum Toda lattice.
0
0
1
0
0
0
Semi-supervised learning
Semi-supervised learning deals with the problem of how, if possible, to take advantage of a huge amount of not classified data, to perform classification, in situations when, typically, the labelled data are few. Even though this is not always possible (it depends on how useful is to know the distribution of the unla...
0
0
1
1
0
0
The Cosmic-Ray Neutron Rover - Mobile Surveys of Field Soil Moisture and the Influence of Roads
Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic-Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture non-invasively by surveying large regions with a ground-based vehicle....
0
1
0
0
0
0
Invariance in Constrained Switching
We study discrete time linear constrained switching systems with additive disturbances, in which the switching may be on the system matrices, the disturbance sets, the state constraint sets or a combination of the above. In our general setting, a switching sequence is admissible if it is accepted by an automaton. For...
1
0
1
0
0
0
On the choice of the low-dimensional domain for global optimization via random embeddings
The challenge of taking many variables into account in optimization problems may be overcome under the hypothesis of low effective dimensionality. Then, the search of solutions can be reduced to the random embedding of a low dimensional space into the original one, resulting in a more manageable optimization problem....
0
0
1
1
0
0
Distributed resource allocation through utility design - Part II: applications to submodular, supermodular and set covering problems
A fundamental component of the game theoretic approach to distributed control is the design of local utility functions. In Part I of this work we showed how to systematically design local utilities so as to maximize the induced worst case performance. The purpose of the present manuscript is to specialize the general...
1
0
0
0
0
0
Quasiparticle band structure engineering in van der Waals heterostructures via dielectric screening
The idea of combining different two-dimensional (2D) crystals in van der Waals heterostructures (vdWHs) has led to a new paradigm for band structure engineering with atomic precision. Due to the weak interlayer couplings, the band structures of the individual 2D crystals are largely preserved upon formation of the he...
0
1
0
0
0
0