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
Teaching the Doppler Effect in Astrophysics
The Doppler effect is a shift in the frequency of waves emitted from an object moving relative to the observer. By observing and analysing the Doppler shift in electromagnetic waves from astronomical objects, astronomers gain greater insight into the structure and operation of our universe. In this paper, a simple te...
0
1
0
0
0
0
Embedding Tarskian Semantics in Vector Spaces
We propose a new linear algebraic approach to the computation of Tarskian semantics in logic. We embed a finite model M in first-order logic with N entities in N-dimensional Euclidean space R^N by mapping entities of M to N dimensional one-hot vectors and k-ary relations to order-k adjacency tensors (multi-way arrays...
1
0
0
0
0
0
Constraints from Dust Mass and Mass Accretion Rate Measurements on Angular Momentum Transport in Protoplanetary Disks
We investigate the relation between disk mass and mass accretion rate to constrain the mechanism of angular momentum transport in protoplanetary disks. Dust mass and mass accretion rate in Chamaeleon I are correlated with a slope close to linear, similar to the one recently identified in Lupus. We investigate the eff...
0
1
0
0
0
0
Character-Word LSTM Language Models
We present a Character-Word Long Short-Term Memory Language Model which both reduces the perplexity with respect to a baseline word-level language model and reduces the number of parameters of the model. Character information can reveal structural (dis)similarities between words and can even be used when a word is ou...
1
0
0
0
0
0
Deep Convolutional Neural Networks for Raman Spectrum Recognition: A Unified Solution
Machine learning methods have found many applications in Raman spectroscopy, especially for the identification of chemical species. However, almost all of these methods require non-trivial preprocessing such as baseline correction and/or PCA as an essential step. Here we describe our unified solution for the identifi...
1
0
0
1
0
0
Suppression of material transfer at contacting surfaces: The effect of adsorbates on Al/TiN and Cu/diamond interfaces from first-principles calculations
The effect of monolayers of oxygen (O) and hydrogen (H) on the possibility of material transfer at aluminium/titanium nitride (Al/TiN) and copper/diamond (Cu/C$_{\text{dia}}$) interfaces, respectively, were investigated within the framework of density functional theory (DFT). To this end the approach, contact, and su...
0
1
0
0
0
0
Fine-grained ECG Classification Based on Deep CNN and Online Decision Fusion
Early recognition of abnormal rhythm in ECG signals is crucial for monitoring or diagnosing patients' cardiac conditions and increasing the success rate of the treatment. Classifying abnormal rhythms into fine-grained categories is very challenging due to the the broad taxonomy of rhythms, noises and lack of real-wor...
1
0
0
1
0
0
A Wavenet for Speech Denoising
Currently, most speech processing techniques use magnitude spectrograms as front-end and are therefore by default discarding part of the signal: the phase. In order to overcome this limitation, we propose an end-to-end learning method for speech denoising based on Wavenet. The proposed model adaptation retains Wavene...
1
0
0
0
0
0
Warped Product Space-times
Many classical results in relativity theory concerning spherically symmetric space-times have easy generalizations to warped product space-times, with a two-dimensional Lorentzian base and arbitrary dimensional Riemannian fibers. We first give a systematic presentation of the main geometric constructions, with emphas...
0
0
1
0
0
0
ALMA Observations of the Young Substellar Binary System 2M1207
We present ALMA observations of the 2M1207 system, a young binary made of a brown dwarf with a planetary-mass companion at a projected separation of about 40 au. We detect emission from dust continuum at 0.89 mm and from the $J = 3 - 2$ rotational transition of CO from a very compact disk around the young brown dwarf...
0
1
0
0
0
0
Multichannel Linear Prediction for Blind Reverberant Audio Source Separation
A class of methods based on multichannel linear prediction (MCLP) can achieve effective blind dereverberation of a source, when the source is observed with a microphone array. We propose an inventive use of MCLP as a pre-processing step for blind source separation with a microphone array. We show theoretically that, ...
1
0
0
0
0
0
SepNE: Bringing Separability to Network Embedding
Many successful methods have been proposed for learning low dimensional representations on large-scale networks, while almost all existing methods are designed in inseparable processes, learning embeddings for entire networks even when only a small proportion of nodes are of interest. This leads to great inconvenienc...
1
0
0
0
0
0
Opinion formation in a locally interacting community with recommender
We present a user of model interaction based on the physics of kinetic exchange, and extend it to individuals placed in a grid with local interaction. We show with numerical analysis and partial analytical results that the critical symmetry breaking transitions and percolation effects typical of the full interaction ...
1
1
0
0
0
0
Integral representation of shallow neural network that attains the global minimum
We consider the supervised learning problem with shallow neural networks. According to our unpublished experiments conducted several years prior to this study, we had noticed an interesting similarity between the distribution of hidden parameters after backprobagation (BP) training, and the ridgelet spectrum of the s...
0
0
0
1
0
0
DoKnowMe: Towards a Domain Knowledge-driven Methodology for Performance Evaluation
Software engineering considers performance evaluation to be one of the key portions of software quality assurance. Unfortunately, there seems to be a lack of standard methodologies for performance evaluation even in the scope of experimental computer science. Inspired by the concept of "instantiation" in object-orien...
1
0
0
0
0
0
The Effect of Different Wavelengths on Porous Silicon Formation Process
Porous silicon layers (PS) have been prepared in this work via Photoelectrochemical etching process (PEC) of n type silicon wafer of 0.8 ohm.cm resistivity in hydrofluoric (HF) acid of 24.5 precent concentration at different etching times (5 to 25 min.). The irradiation has been achieved using Tungsten lamp with dif...
0
1
0
0
0
0
Topological dimension tunes activity patterns in hierarchical modular network models
Connectivity patterns of relevance in neuroscience and systems biology can be encoded in hierarchical modular networks (HMNs). Moreover, recent studies highlight the role of hierarchical modular organization in shaping brain activity patterns, providing an excellent substrate to promote both the segregation and integ...
0
1
0
0
0
0
DFTerNet: Towards 2-bit Dynamic Fusion Networks for Accurate Human Activity Recognition
Deep Convolutional Neural Networks (DCNNs) are currently popular in human activity recognition applications. However, in the face of modern artificial intelligence sensor-based games, many research achievements cannot be practically applied on portable devices. DCNNs are typically resource-intensive and too large to ...
0
0
0
1
0
0
Generalized stealthy hyperuniform processes : maximal rigidity and the bounded holes conjecture
We study translation invariant stochastic processes on $\mathbb{R}^d$ or $\mathbb{Z}^d$ whose diffraction spectrum or structure function $S(k)$, i.e. the Fourier transform of the truncated total pair correlation function, vanishes on an open set $U$ in the wave space. A key family of such processes are stealthy hyper...
0
1
0
0
0
0
High-frequency approximation of the interior dirichlet-to-neumann map and applications to the transmission eigenvalues
We study the high-frequency behavior of the Dirichlet-to-Neumann map for an arbitrary compact Riemannian manifold with a non-empty smooth boundary. We show that far from the real axis it can be approximated by a simpler operator. We use this fact to get new results concerning the location of the transmission eigenval...
0
0
1
0
0
0
Conformal scalar curvature equation on S^n: functions with two close critical points (twin pseudo-peaks)
By using the Lyapunov-Schmidt reduction method without perturbation, we consider existence results for the conformal scalar curvature on S^n (n greater or equal to 3) when the prescribed function (after being projected to R^n) has two close critical points, which have the same value (positive), equal "flatness" (twin...
0
0
1
0
0
0
Equivalence between non-Markovian and Markovian dynamics in epidemic spreading processes
A general formalism is introduced to allow the steady state of non-Markovian processes on networks to be reduced to equivalent Markovian processes on the same substrates. The example of an epidemic spreading process is considered in detail, where all the non-Markovian aspects are shown to be captured within a single ...
0
1
0
0
0
0
Attacking Binarized Neural Networks
Neural networks with low-precision weights and activations offer compelling efficiency advantages over their full-precision equivalents. The two most frequently discussed benefits of quantization are reduced memory consumption, and a faster forward pass when implemented with efficient bitwise operations. We propose a...
1
0
0
1
0
0
On Treewidth and Stable Marriage
Stable Marriage is a fundamental problem to both computer science and economics. Four well-known NP-hard optimization versions of this problem are the Sex-Equal Stable Marriage (SESM), Balanced Stable Marriage (BSM), max-Stable Marriage with Ties (max-SMT) and min-Stable Marriage with Ties (min-SMT) problems. In this...
1
0
0
0
0
0
A Holistic Approach to Forecasting Wholesale Energy Market Prices
Electricity market price predictions enable energy market participants to shape their consumption or supply while meeting their economic and environmental objectives. By utilizing the basic properties of the supply-demand matching process performed by grid operators, we develop a method to recover energy market's str...
1
0
0
1
0
0
Matched bipartite block model with covariates
Community detection or clustering is a fundamental task in the analysis of network data. Many real networks have a bipartite structure which makes community detection challenging. In this paper, we consider a model which allows for matched communities in the bipartite setting, in addition to node covariates with info...
1
0
0
1
0
0
Topological Interference Management with Decoded Message Passing
The topological interference management (TIM) problem studies partially-connected interference networks with no channel state information except for the network topology (i.e., connectivity graph) at the transmitters. In this paper, we consider a similar problem in the uplink cellular networks, while message passing ...
1
0
0
0
0
0
Robust Regression via Mutivariate Regression Depth
This paper studies robust regression in the settings of Huber's $\epsilon$-contamination models. We consider estimators that are maximizers of multivariate regression depth functions. These estimators are shown to achieve minimax rates in the settings of $\epsilon$-contamination models for various regression problems...
0
0
1
1
0
0
Quotients of Buildings as $W$-Groupoids
We introduce structures which model the quotients of buildings by type-preserving group actions. These structures, which we call W-groupoids, generalize Bruhat decompositions, chambers systems of type M, and Tits amalgams. We define the fundamental group of a W-groupoid, and characterize buildings as connected simply...
0
0
1
0
0
0
Birth of the GUP and its effect on the entropy of the Universe in Lie-$N$-algebra
In this paper, the origin of the generalized uncertainty principle (GUP) in an $M$-dimensional theory with Lie-$N$-algebra is considered. This theory which we name GLNA(Generalized Lie-$N$-Algebra)-theory can be reduced to $M$-theory with $M=11$ and $N=3$. In this theory, at the beginning, two energies with positive ...
0
1
0
0
0
0
Data-adaptive smoothing for optimal-rate estimation of possibly non-regular parameters
We consider nonparametric inference of finite dimensional, potentially non-pathwise differentiable target parameters. In a nonparametric model, some examples of such parameters that are always non pathwise differentiable target parameters include probability density functions at a point, or regression functions at a ...
0
0
1
1
0
0
Knowledge Transfer for Out-of-Knowledge-Base Entities: A Graph Neural Network Approach
Knowledge base completion (KBC) aims to predict missing information in a knowledge base.In this paper, we address the out-of-knowledge-base (OOKB) entity problem in KBC:how to answer queries concerning test entities not observed at training time. Existing embedding-based KBC models assume that all test entities are a...
1
0
0
0
0
0
Feature Engineering for Predictive Modeling using Reinforcement Learning
Feature engineering is a crucial step in the process of predictive modeling. It involves the transformation of given feature space, typically using mathematical functions, with the objective of reducing the modeling error for a given target. However, there is no well-defined basis for performing effective feature eng...
1
0
0
1
0
0
Cellular automata connections
It is shown that any two cellular automata (CA) in rule space can be connected by a continuous path parameterized by a real number $\kappa \in (0, \infty)$, each point in the path corresponding to a coupled map lattice (CML). In the limits $\kappa \to 0$ and $\kappa \to \infty$ the CML becomes each of the two CA ente...
0
1
1
0
0
0
Hypothesis Testing via Euclidean Separation
We discuss an "operational" approach to testing convex composite hypotheses when the underlying distributions are heavy-tailed. It relies upon Euclidean separation of convex sets and can be seen as an extension of the approach to testing by convex optimization developed in [8, 12]. In particular, we show how one can ...
0
0
1
1
0
0
Detecting in-plane tension induced crystal plasticity transition with nanoindentation
We present experimental data and simulations on the effects of in-plane tension on nanoindentation hardness and pop-in noise. Nanoindentation experiments using a Berkovich tip are performed on bulk polycrystaline Al samples, under tension in a custom 4pt-bending fixture. The hardness displays a transition, for indent...
0
1
0
0
0
0
A novel approach for fast mining frequent itemsets use N-list structure based on MapReduce
Frequent Pattern Mining is a one field of the most significant topics in data mining. In recent years, many algorithms have been proposed for mining frequent itemsets. A new algorithm has been presented for mining frequent itemsets based on N-list data structure called Prepost algorithm. The Prepost algorithm is enha...
1
0
0
0
0
0
Resonant thermalization of periodically driven strongly correlated electrons
We study the dynamics of the Fermi-Hubbard model driven by a time-periodic modulation of the interaction within nonequilibrium Dynamical Mean-Field Theory. For moderate interaction, we find clear evidence of thermalization to a genuine infinite-temperature state with no residual oscillations. Quite differently, in th...
0
1
0
0
0
0
Fusible HSTs and the randomized k-server conjecture
We exhibit an $O((\log k)^6)$-competitive randomized algorithm for the $k$-server problem on any metric space. It is shown that a potential-based algorithm for the fractional $k$-server problem on hierarchically separated trees (HSTs) with competitive ratio $f(k)$ can be used to obtain a randomized algorithm for any ...
1
0
1
0
0
0
BPS spectra and 3-manifold invariants
We provide a physical definition of new homological invariants $\mathcal{H}_a (M_3)$ of 3-manifolds (possibly, with knots) labeled by abelian flat connections. The physical system in question involves a 6d fivebrane theory on $M_3$ times a 2-disk, $D^2$, whose Hilbert space of BPS states plays the role of a basic bui...
0
0
1
0
0
0
Nonzero positive solutions of a multi-parameter elliptic system with functional BCs
We prove, by topological methods, new results on the existence of nonzero positive weak solutions for a class of multi-parameter second order elliptic systems subject to functional boundary conditions. The setting is fairly general and covers the case of multi-point, integral and nonlinear boundary conditions. We als...
0
0
1
0
0
0
Emotion Recognition from Speech based on Relevant Feature and Majority Voting
This paper proposes an approach to detect emotion from human speech employing majority voting technique over several machine learning techniques. The contribution of this work is in two folds: firstly it selects those features of speech which is most promising for classification and secondly it uses the majority voti...
1
0
0
1
0
0
The basic principles and the structure and algorithmically software of computing by hypercomplex number
In article the basic principles put in a basis of algorithmicallysoftware of hypercomplex number calculations, structure of a software, structure of functional subsystems are considered. The most important procedures included in subsystems are considered, program listings and examples of their application are given.
1
0
0
0
0
0
Drawing cone spherical metrics via Strebel differentials
Cone spherical metrics are conformal metrics with constant curvature one and finitely many conical singularities on compact Riemann surfaces. By using Strebel differentials as a bridge, we construct a new class of cone spherical metrics on compact Riemann surfaces by drawing on the surfaces some class of connected me...
0
0
1
0
0
0
Thermoelectric radiation detector based on superconductor/ferromagnet systems
We suggest a new type of an ultrasensitive detector of electromagnetic fields exploiting the giant thermoelectric effect recently found in superconductor/ferromagnet hybrid structures. Compared to other types of superconducting detectors where the detected signal is based on variations of the detector impedance, the ...
0
1
0
0
0
0
Upper estimates of Christoffel function on convex domains
New upper bounds on the pointwise behaviour of Christoffel function on convex domains in ${\mathbb{R}}^d$ are obtained. These estimates are established by explicitly constructing the corresponding "needle"-like algebraic polynomials having small integral norm on the domain, and are stated in terms of few easy-to-meas...
0
0
1
0
0
0
Special Lagrangian and deformed Hermitian Yang-Mills on tropical manifold
From string theory, the notion of deformed Hermitian Yang-Mills connections has been introduced by Mariño, Minasian, Moore and Strominger. After that, Leung, Yau and Zaslow proved that it naturally appears as mirror objects of special Lagrangian submanifolds via Fourier-Mukai transform between dual torus fibrations. ...
0
0
1
0
0
0
An introduction to the qualitative and quantitative theory of homogenization
We present an introduction to periodic and stochastic homogenization of ellip- tic partial differential equations. The first part is concerned with the qualitative theory, which we present for equations with periodic and random coefficients in a unified approach based on Tartar's method of oscillating test functions....
0
0
1
0
0
0
A Computational Study of Yttria-Stabilized Zirconia: I. Using Crystal Chemistry to Search for the Ground State on a Glassy Energy Landscape
Yttria-stabilized zirconia (YSZ), a ZrO2-Y2O3 solid solution that contains a large population of oxygen vacancies, is widely used in energy and industrial applications. Past computational studies correctly predicted the anion diffusivity but not the cation diffusivity, which is important for material processing and s...
0
1
0
0
0
0
Reactive Power Compensation Game under Prospect-Theoretic Framing Effects
Reactive power compensation is an important challenge in current and future smart power systems. However, in the context of reactive power compensation, most existing studies assume that customers can assess their compensation value, i.e., Var unit, objectively. In this paper, customers are assumed to make decisions ...
1
0
0
0
0
0
Some remarks on protolocalizations and protoadditive reflections
We investigate additional properties of protolocalizations, introduced and studied by F. Borceux, M. M. Clementino, M. Gran, and L. Sousa, and of protoadditive reflections, introduced and studied by T. Everaert and M. Gran. Among other things we show that there are no non-trivial (protolocalizations and) protoadditiv...
0
0
1
0
0
0
Resonances near Thresholds in slightly Twisted Waveguides
We consider the Dirichlet Laplacian in a straight three dimensional waveguide with non-rotationally invariant cross section, perturbed by a twisting of small amplitude. It is well known that such a perturbation does not create eigenvalues below the essential spectrum. However, around the bottom of the spectrum, we pr...
0
0
1
0
0
0
Trapping and displacement of liquid collars and plugs in rough-walled tubes
A liquid film wetting the interior of a long circular cylinder redistributes under the action of surface tension to form annular collars or occlusive plugs. These equilibrium structures are invariant under axial translation within a perfectly smooth uniform tube and therefore can be displaced axially by very weak ext...
0
1
0
0
0
0
Topological Brain Network Distances
Existing brain network distances are often based on matrix norms. The element-wise differences in the existing matrix norms may fail to capture underlying topological differences. Further, matrix norms are sensitive to outliers. A major disadvantage to element-wise distance calculations is that it could be severely a...
0
0
0
0
1
0
The challenge of decentralized marketplaces
Online trust systems are playing an important role in to-days world and face various challenges in building them. Billions of dollars of products and services are traded through electronic commerce, files are shared among large peer-to-peer networks and smart contracts can potentially replace paper contracts with dig...
1
0
0
0
0
0
Radially resolved simulations of collapsing pebble clouds in protoplanetary discs
We study the collapse of pebble clouds with a statistical model to find the internal structure of comet-sized planetesimals. Pebble-pebble collisions occur during the collapse and the outcome of these collisions affect the resulting structure of the planetesimal. We expand our previous models by allowing the individu...
0
1
0
0
0
0
Accelerating equilibrium isotope effect calculations: I. Stochastic thermodynamic integration with respect to mass
Accurate path integral Monte Carlo or molecular dynamics calculations of isotope effects have until recently been expensive because of the necessity to reduce three types of errors present in such calculations: statistical errors due to sampling, path integral discretization errors, and thermodynamic integration erro...
0
1
0
0
0
0
CoAP over ICN
The Constrained Application Protocol (CoAP) is a specialized Web transfer protocol for resource-oriented applications intended to run on constrained devices, typically part of the Internet of Things. In this paper we leverage Information-Centric Networking (ICN), deployed within the domain of a network provider that ...
1
0
0
0
0
0
Nonequilibrium mode-coupling theory for dense active systems of self-propelled particles
The physics of active systems of self-propelled particles, in the regime of a dense liquid state, is an open puzzle of great current interest, both for statistical physics and because such systems appear in many biological contexts. We develop a nonequilibrium mode-coupling theory (MCT) for such systems, where activi...
0
1
0
0
0
0
Symmetry Protected Dynamical Symmetry in the Generalized Hubbard Models
In this letter we present a theorem on the dynamics of the generalized Hubbard models. This theorem shows that the symmetry of the single particle Hamiltonian can protect a kind of dynamical symmetry driven by the interactions. Here the dynamical symmetry refers to that the time evolution of certain observables are s...
0
1
0
0
0
0
Machine-learning a virus assembly fitness landscape
Realistic evolutionary fitness landscapes are notoriously difficult to construct. A recent cutting-edge model of virus assembly consists of a dodecahedral capsid with $12$ corresponding packaging signals in three affinity bands. This whole genome/phenotype space consisting of $3^{12}$ genomes has been explored via co...
0
0
0
0
1
0
A multilevel block building algorithm for fast modeling generalized separable systems
Data-driven modeling plays an increasingly important role in different areas of engineering. For most of existing methods, such as genetic programming (GP), the convergence speed might be too slow for large scale problems with a large number of variables. It has become the bottleneck of GP for practical applications....
0
0
1
0
0
0
Competition and Selection Among Conventions
In many domains, a latent competition among different conventions determines which one will come to dominate. One sees such effects in the success of community jargon, of competing frames in political rhetoric, or of terminology in technical contexts. These effects have become widespread in the online domain, where t...
1
1
0
0
0
0
Tradeoff Between Delay and High SNR Capacity in Quantized MIMO Systems
Analog-to-digital converters (ADCs) are a major contributor to the power consumption of multiple-input multiple-output (MIMO) communication systems with large number of antennas. Use of low resolution ADCs has been proposed as a means to decrease power consumption in MIMO receivers. However, reducing the ADC resoluti...
1
0
0
0
0
0
Formal Synthesis of Control Strategies for Positive Monotone Systems
We design controllers from formal specifications for positive discrete-time monotone systems that are subject to bounded disturbances. Such systems are widely used to model the dynamics of transportation and biological networks. The specifications are described using signal temporal logic (STL), which can express a b...
1
0
1
0
0
0
Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural Networks
Progress in deep learning is slowed by the days or weeks it takes to train large models. The natural solution of using more hardware is limited by diminishing returns, and leads to inefficient use of additional resources. In this paper, we present a large batch, stochastic optimization algorithm that is both faster t...
1
0
0
1
0
0
Signal propagation in sensing and reciprocating cellular systems with spatial and structural heterogeneity
Sensing and reciprocating cellular systems (SARs) are important for the operation of many biological systems. Production in interferon (IFN) SARs is achieved through activation of the Jak-Stat pathway, and downstream upregulation of IFN regulatory factor (IRF)-3 and IFN transcription, but the role that high and low a...
0
0
0
0
1
0
A New Family of Asymmetric Distributions for Modeling Light-Tailed and Right-Skewed Data
A new three-parameter cumulative distribution function defined on $(\alpha,\infty)$, for some $\alpha\geq0$, with asymmetric probability density function and showing exponential decays at its both tails, is introduced. The new distribution is near to familiar distributions like the gamma and log-normal distributions,...
0
0
1
1
0
0
Secret-Key-Aided Scheme for Securing Untrusted DF Relaying Networks
This paper proposes a new scheme to secure the transmissions in an untrusted decode-and-forward (DF) relaying network. A legitimate source node, Alice, sends her data to a legitimate destination node, Bob, with the aid of an untrusted DF relay node, Charlie. To secure the transmissions from Charlie during relaying ti...
1
0
0
0
0
0
On deep speaker embeddings for text-independent speaker recognition
We investigate deep neural network performance in the textindependent speaker recognition task. We demonstrate that using angular softmax activation at the last classification layer of a classification neural network instead of a simple softmax activation allows to train a more generalized discriminative speaker embe...
0
0
0
1
0
0
Accurate Computation of Marginal Data Densities Using Variational Bayes
Bayesian model selection and model averaging rely on estimates of marginal data densities (MDDs) also known as marginal likelihoods. Estimation of MDDs is often nontrivial and requires elaborate numerical integration methods. We propose using the variational Bayes posterior density as a weighting density within the c...
0
0
0
1
0
0
Random matrices and the New York City subway system
We analyze subway arrival times in the New York City subway system. We find regimes where the gaps between trains exhibit both (unitarily invariant) random matrix statistics and Poisson statistics. The departure from random matrix statistics is captured by the value of the Coulomb potential along the subway route. Th...
0
1
0
0
0
0
Weakening of the diamagnetic shielding in FeSe$_{1-x}$S$_x$ at high pressures
The superconducting transition of FeSe$_{1-x}$S$_x$ with three distinct sulphur concentrations $x$ was studied under hydrostatic pressure up to $\sim$70 kbar via bulk AC susceptibility. The pressure dependence of the superconducting transition temperature ($T_c$) features a small dome-shaped variation at low pressure...
0
1
0
0
0
0
Incremental Skip-gram Model with Negative Sampling
This paper explores an incremental training strategy for the skip-gram model with negative sampling (SGNS) from both empirical and theoretical perspectives. Existing methods of neural word embeddings, including SGNS, are multi-pass algorithms and thus cannot perform incremental model update. To address this problem, ...
1
0
0
0
0
0
Continuous-Time Accelerated Methods via a Hybrid Control Lens
Treating optimization methods as dynamical systems can be traced back centuries ago in order to comprehend the notions and behaviors of optimization methods. Lately, this mind set has become the driving force to design new optimization methods. Inspired by the recent dynamical system viewpoint of Nesterov's fast meth...
1
0
0
0
0
0
Fast-Slow Recurrent Neural Networks
Processing sequential data of variable length is a major challenge in a wide range of applications, such as speech recognition, language modeling, generative image modeling and machine translation. Here, we address this challenge by proposing a novel recurrent neural network (RNN) architecture, the Fast-Slow RNN (FS-...
1
0
0
0
0
0
On OR Many-Access Channels
OR multi-access channel is a simple model where the channel output is the Boolean OR among the Boolean channel inputs. We revisit this model, showing that employing Bloom filter, a randomized data structure, as channel inputs achieves its capacity region with joint decoding and the symmetric sum rate of $\ln 2$ bits ...
1
0
1
0
0
0
TwiInsight: Discovering Topics and Sentiments from Social Media Datasets
Social media platforms contain a great wealth of information which provides opportunities for us to explore hidden patterns or unknown correlations, and understand people's satisfaction with what they are discussing. As one showcase, in this paper, we present a system, TwiInsight which explores the insight of Twitter...
1
0
0
0
0
0
The Promise and Peril of Human Evaluation for Model Interpretability
Transparency, user trust, and human comprehension are popular ethical motivations for interpretable machine learning. In support of these goals, researchers evaluate model explanation performance using humans and real world applications. This alone presents a challenge in many areas of artificial intelligence. In thi...
1
0
0
1
0
0
Guided Unfoldings for Finding Loops in Standard Term Rewriting
In this paper, we reconsider the unfolding-based technique that we have introduced previously for detecting loops in standard term rewriting. We improve it by guiding the unfolding process, using distinguished positions in the rewrite rules. This results in a depth-first computation of the unfoldings, whereas the ori...
1
0
0
0
0
0
Nutrients and biomass dynamics in photo-sequencing batch reactors treating wastewater with high nutrients loadings
The present study investigates different strategies for the treatment of a mixture of digestate from an anaerobic digester diluted and secondary effluent from a high rate algal pond. To this aim, the performance of two photo-sequencing batch reactors (PSBRs) operated at high nutrients loading rates and different soli...
0
0
0
0
1
0
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
Random Fourier features is one of the most popular techniques for scaling up kernel methods, such as kernel ridge regression. However, despite impressive empirical results, the statistical properties of random Fourier features are still not well understood. In this paper we take steps toward filling this gap. Specifi...
1
0
0
1
0
0
Charge reconstruction study of the DAMPE Silicon-Tungsten Tracker with ion beams
The DArk Matter Particle Explorer (DAMPE) is one of the four satellites within Strategic Pioneer Research Program in Space Science of the Chinese Academy of Science (CAS). DAMPE can detect electrons, photons in a wide energy range (5 GeV to 10 TeV) and ions up to iron (100GeV to 100 TeV). Silicon-Tungsten Tracker (ST...
0
1
0
0
0
0
Scalable Cryogenic Read-out Circuit for a Superconducting Nanowire Single-Photon Detector System
The superconducting nanowire single photon detector (SNSPD) is a leading technology for quantum information science applications using photons, and they are finding increasing uses in photon-starved classical imaging applications. Critical detector characteristics, such as timing resolution (jitter), reset time and m...
0
1
0
0
0
0
String principal bundles and Courant algebroids
Just like Atiyah Lie algebroids encode the infinitesimal symmetries of principal bundles, exact Courant algebroids are believed to encode the infinitesimal symmetries of $S^1$-gerbes. At the same time, transitive Courant algebroids may be viewed as the higher analogue of Atiyah Lie algebroids, and the non-commutative...
0
0
1
0
0
0
Electroforming-Free TaOx Memristors using Focused Ion Beam Irradiations
We demonstrate creation of electroforming-free TaOx memristive devices using focused ion beam irradiations to locally define conductive filaments in TaOx films. Electrical characterization shows that these irradiations directly create fully functional memristors without the need for electroforming. Ion beam forming o...
0
1
0
0
0
0
Optimal hypothesis testing for stochastic block models with growing degrees
The present paper considers testing an Erdos--Renyi random graph model against a stochastic block model in the asymptotic regime where the average degree of the graph grows with the graph size n. Our primary interest lies in those cases in which the signal-to-noise ratio is at a constant level. Focusing on symmetric ...
1
0
1
1
0
0
Generalized End-to-End Loss for Speaker Verification
In this paper, we propose a new loss function called generalized end-to-end (GE2E) loss, which makes the training of speaker verification models more efficient than our previous tuple-based end-to-end (TE2E) loss function. Unlike TE2E, the GE2E loss function updates the network in a way that emphasizes examples that ...
1
0
0
1
0
0
Penalized pairwise pseudo likelihood for variable selection with nonignorable missing data
The regularization approach for variable selection was well developed for a completely observed data set in the past two decades. In the presence of missing values, this approach needs to be tailored to different missing data mechanisms. In this paper, we focus on a flexible and generally applicable missing data mech...
0
0
0
1
0
0
Fast embedding of multilayer networks: An algorithm and application to group fMRI
Learning interpretable features from complex multilayer networks is a challenging and important problem. The need for such representations is particularly evident in multilayer networks of the brain, where nodal characteristics may help model and differentiate regions of the brain according to individual, cognitive t...
1
0
0
0
0
0
Towards Better Summarizing Bug Reports with Crowdsourcing Elicited Attributes
Recent years have witnessed the growing demands for resolving numerous bug reports in software maintenance. Aiming to reduce the time testers/developers take in perusing bug reports, the task of bug report summarization has attracted a lot of research efforts in the literature. However, no systematic analysis has bee...
1
0
0
0
0
0
Extraordinary linear dynamic range in laser-defined functionalized graphene photodetectors
Graphene-based photodetectors have demonstrated mechanical flexibility, large operating bandwidth, and broadband spectral response. However, their linear dynamic range (LDR) is limited by graphene's intrinsichot-carrier dynamics, which causes deviation from a linear photoresponse at low incident powers. At the same t...
0
1
0
0
0
0
Efficient Transfer Learning Schemes for Personalized Language Modeling using Recurrent Neural Network
In this paper, we propose an efficient transfer leaning methods for training a personalized language model using a recurrent neural network with long short-term memory architecture. With our proposed fast transfer learning schemes, a general language model is updated to a personalized language model with a small amou...
1
0
0
0
0
0
Convergence of ground state solutions for nonlinear Schrödinger equations on graphs
We consider the nonlinear Schrödinger equation $-\Delta u+(\lambda a(x)+1)u=|u|^{p-1}u$ on a locally finite graph $G=(V,E)$. We prove via the Nehari method that if $a(x)$ satisfies certain assumptions, for any $\lambda>1$, the equation admits a ground state solution $u_\lambda$. Moreover, as $\lambda\rightarrow \inft...
0
0
1
0
0
0
Error Analysis of the Stochastic Linear Feedback Particle Filter
This paper is concerned with the convergence and long-term stability analysis of the feedback particle filter (FPF) algorithm. The FPF is an interacting system of $N$ particles where the interaction is designed such that the empirical distribution of the particles approximates the posterior distribution. It is known ...
1
0
0
0
0
0
Geometry in the Courtroom
There has been a recent media blitz on a cohort of mathematicians valiantly working to fix America's democratic system by combatting gerrymandering with geometry. While statistics commonly features in the courtroom (forensics, DNA analysis, etc.), the gerrymandering news raises a natural question: in what other ways ...
0
0
1
0
0
0
Proof of Concept of Wireless TERS Monitoring
Temporary earth retaining structures (TERS) help prevent collapse during construction excavation. To ensure that these structures are operating within design specifications, load forces on supports must be monitored. Current monitoring approaches are expensive, sparse, off-line, and thus difficult to integrate into p...
1
0
0
0
0
0
Hyperrigid subsets of Cuntz-Krieger algebras and the property of rigidity at zero
A subset $\mathcal{G}$ generating a $C^*$-algebra $A$ is said to be hyperrigid if for every faithful nondegenerate $*$-representation $A\subseteq B(H)$ and a sequence $\phi_n:B(H) \to B(H)$ of unital completely positive maps, we have that \[ \lim_{n\to\infty}\phi_n(g)= g~~\text{for all } g\in \mathcal{G} ~~ \implies ...
0
0
1
0
0
0
Chiral Mott insulators in frustrated Bose-Hubbard models on ladders and two-dimensional lattices: a combined perturbative and density matrix renormalization group study
We study the fully gapped chiral Mott insulator (CMI) of frustrated Bose-Hubbard models on ladders and two-dimensional lattices by perturbative strong-coupling analysis and density matrix renormalization group (DMRG). First we show the existence of a low-lying exciton state on all geometries carrying the correct quan...
0
1
0
0
0
0
Thermodynamic Limit of Interacting Particle Systems over Time-varying Sparse Random Networks
We establish a functional weak law of large numbers for observable macroscopic state variables of interacting particle systems (e.g., voter and contact processes) over fast time-varying sparse random networks of interactions. We show that, as the number of agents $N$ grows large, the proportion of agents $\left(\over...
0
0
1
0
0
0