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
Rank Two Non-Commutative Laurent Phenomenon and Pseudo-Positivity
We study polynomial generalizations of the Kontsevich automorphisms acting on the skew-field of formal rational expressions in two non-commuting variables. Our main result is the Laurentness and pseudo-positivity of iterations of these automorphisms. The resulting expressions are described combinatorially using a gen...
0
0
1
0
0
0
Faster Coordinate Descent via Adaptive Importance Sampling
Coordinate descent methods employ random partial updates of decision variables in order to solve huge-scale convex optimization problems. In this work, we introduce new adaptive rules for the random selection of their updates. By adaptive, we mean that our selection rules are based on the dual residual or the primal-...
1
0
1
1
0
0
On the role of synaptic stochasticity in training low-precision neural networks
Stochasticity and limited precision of synaptic weights in neural network models are key aspects of both biological and hardware modeling of learning processes. Here we show that a neural network model with stochastic binary weights naturally gives prominence to exponentially rare dense regions of solutions with a nu...
1
1
0
1
0
0
Secants, bitangents, and their congruences
A congruence is a surface in the Grassmannian $\mathrm{Gr}(1,\mathbb{P}^3)$ of lines in projective $3$-space. To a space curve $C$, we associate the Chow hypersurface in $\mathrm{Gr}(1,\mathbb{P}^3)$ consisting of all lines which intersect $C$. We compute the singular locus of this hypersurface, which contains the co...
0
0
1
0
0
0
Convergence of Stochastic Approximation Monte Carlo and modified Wang-Landau algorithms: Tests for the Ising model
We investigate the behavior of the deviation of the estimator for the density of states (DOS) with respect to the exact solution in the course of Wang-Landau and Stochastic Approximation Monte Carlo (SAMC) simulations of the two-dimensional Ising model. We find that the deviation saturates in the Wang-Landau case. Th...
0
1
0
0
0
0
On the approximation by convolution type double singular integral operators
In this paper, we prove the pointwise convergence and the rate of pointwise convergence for a family of singular integral operators in two-dimensional setting in the following form: \begin{equation*} L_{\lambda }\left( f;x,y\right) =\underset{D}{\iint }f\left( t,s\right) K_{\lambda }\left( t-x,s-y\right) dsdt,\text{ ...
0
0
1
0
0
0
Characterization of polynomials whose large powers have all positive coefficients
We give a criterion which characterizes a homogeneous real multi-variate polynomial to have the property that all sufficiently large powers of the polynomial (as well as their products with any given positive homogeneous polynomial) have positive coefficients. Our result generalizes a result of De Angelis, which corr...
0
0
1
0
0
0
The Moon Illusion explained by the Projective Consciousness Model
The Moon often appears larger near the perceptual horizon and smaller high in the sky though the visual angle subtended is invariant. We show how this illusion results from the optimization of a projective geometrical frame for conscious perception through free energy minimization, as articulated in the Projective Co...
0
0
0
0
1
0
Bloch line dynamics within moving domain walls in 3D ferromagnets
We study field-driven magnetic domain wall dynamics in garnet strips by large-scale three-dimensional micromagnetic simulations. The domain wall propagation velocity as a function of the applied field exhibits a low-field linear part terminated by a sudden velocity drop at a threshold field magnitude, related to the ...
0
1
0
0
0
0
Approaching the UCT problem via crossed products of the Razak-Jacelon algebra
We show that the UCT problem for separable, nuclear $\mathrm C^*$-algebras relies only on whether the UCT holds for crossed products of certain finite cyclic group actions on the Razak-Jacelon algebra. This observation is analogous to and in fact recovers a characterization of the UCT problem in terms of finite group...
0
0
1
0
0
0
Some Remarks about the Complexity of Epidemics Management
Recent outbreaks of Ebola, H1N1 and other infectious diseases have shown that the assumptions underlying the established theory of epidemics management are too idealistic. For an improvement of procedures and organizations involved in fighting epidemics, extended models of epidemics management are required. The neces...
0
1
0
0
0
0
Entanglement Entropy in Excited States of the Quantum Lifshitz Model
We investigate the entanglement properties of an infinite class of excited states in the quantum Lifshitz model (QLM). The presence of a conformal quantum critical point in the QLM makes it unusually tractable for a model above one spatial dimension, enabling the ground state entanglement entropy for an arbitrary dom...
0
1
0
0
0
0
Poisson-Fermi Formulation of Nonlocal Electrostatics in Electrolyte Solutions
We present a nonlocal electrostatic formulation of nonuniform ions and water molecules with interstitial voids that uses a Fermi-like distribution to account for steric and correlation effects in electrolyte solutions. The formulation is based on the volume exclusion of hard spheres leading to a steric potential and ...
0
1
0
0
0
0
Learning to Transfer
Transfer learning borrows knowledge from a source domain to facilitate learning in a target domain. Two primary issues to be addressed in transfer learning are what and how to transfer. For a pair of domains, adopting different transfer learning algorithms results in different knowledge transferred between them. To d...
1
0
0
1
0
0
Strong Metric Subregularity of Mappings in Variational Analysis and Optimization
Although the property of strong metric subregularity of set-valued mappings has been present in the literature under various names and with various definitions for more than two decades, it has attracted much less attention than its older "siblings", the metric regularity and the strong metric regularity. The purpose...
0
0
1
0
0
0
Systematic Identification of LAEs for Visible Exploration and Reionization Research Using Subaru HSC (SILVERRUSH). I. Program Strategy and Clustering Properties of ~2,000 Lya Emitters at z=6-7 over the 0.3-0.5 Gpc$^2$ Survey Area
We present the SILVERRUSH program strategy and clustering properties investigated with $\sim 2,000$ Ly$\alpha$ emitters at $z=5.7$ and $6.6$ found in the early data of the Hyper Suprime-Cam (HSC) Subaru Strategic Program survey exploiting the carefully designed narrowband filters. We derive angular correlation functi...
0
1
0
0
0
0
Experimental study of mini-magnetosphere
Magnetosphere at ion kinetic scales, or mini-magnetosphere, possesses unusual features as predicted by numerical simulations. However, there are practically no data on the subject from space observations and the data which are available are far too incomplete. In the present work we describe results of laboratory exp...
0
1
0
0
0
0
Matrix KP: tropical limit and Yang-Baxter maps
We study soliton solutions of matrix Kadomtsev-Petviashvili (KP) equations in a tropical limit, in which their support at fixed time is a planar graph and polarizations are attached to its constituting lines. There is a subclass of "pure line soliton solutions" for which we find that, in this limit, the distribution ...
0
1
0
0
0
0
Poster Abstract: LPWA-MAC - a Low Power Wide Area network MAC protocol for cyber-physical systems
Low-Power Wide-Area Networks (LPWANs) are being successfully used for the monitoring of large-scale systems that are delay-tolerant and which have low-bandwidth requirements. The next step would be instrumenting these for the control of Cyber-Physical Systems (CPSs) distributed over large areas which require more ban...
1
0
0
0
0
0
Asymptotic Enumeration of Compacted Binary Trees
A compacted tree is a graph created from a binary tree such that repeatedly occurring subtrees in the original tree are represented by pointers to existing ones, and hence every subtree is unique. Such representations form a special class of directed acyclic graphs. We are interested in the asymptotic number of compa...
1
0
0
0
0
0
The STAR MAPS-based PiXeL detector
The PiXeL detector (PXL) for the Heavy Flavor Tracker (HFT) of the STAR experiment at RHIC is the first application of the state-of-the-art thin Monolithic Active Pixel Sensors (MAPS) technology in a collider environment. Custom built pixel sensors, their readout electronics and the detector mechanical structure are ...
0
1
0
0
0
0
Complete intersection monomial curves and the Cohen-Macaulayness of their tangent cones
Let $C({\bf n})$ be a complete intersection monomial curve in the 4-dimensional affine space. In this paper we study the complete intersection property of the monomial curve $C({\bf n}+w{\bf v})$, where $w>0$ is an integer and ${\bf v} \in \mathbb{N}^{4}$. Also we investigate the Cohen-Macaulayness of the tangent con...
0
0
1
0
0
0
Stable and unstable vortex knots in a trapped Bose-Einstein condensate
The dynamics of a quantum vortex torus knot ${\cal T}_{P,Q}$ and similar knots in an atomic Bose-Einstein condensate at zero temperature in the Thomas-Fermi regime has been considered in the hydrodynamic approximation. The condensate has a spatially nonuniform equilibrium density profile $\rho(z,r)$ due to an externa...
0
1
0
0
0
0
Design of Configurable Sequential Circuits in Quantum-dot Cellular Automata
Quantum-dot cellular automata (QCA) is a likely candidate for future low power nano-scale electronic devices. Sequential circuits in QCA attract more attention due to its numerous application in digital industry. On the other hand, configurable devices provide low device cost and efficient utilization of device area....
1
0
0
0
0
0
ADINE: An Adaptive Momentum Method for Stochastic Gradient Descent
Two major momentum-based techniques that have achieved tremendous success in optimization are Polyak's heavy ball method and Nesterov's accelerated gradient. A crucial step in all momentum-based methods is the choice of the momentum parameter $m$ which is always suggested to be set to less than $1$. Although the choi...
1
0
0
1
0
0
Symplectic rational $G$-surfaces and equivariant symplectic cones
We give characterizations of a finite group $G$ acting symplectically on a rational surface ($\mathbb{C}P^2$ blown up at two or more points). In particular, we obtain a symplectic version of the dichotomy of $G$-conic bundles versus $G$-del Pezzo surfaces for the corresponding $G$-rational surfaces, analogous to a cl...
0
0
1
0
0
0
Biderivations of the twisted Heisenberg-Virasoro algebra and their applications
In this paper, the biderivations without the skew-symmetric condition of the twisted Heisenberg-Virasoro algebra are presented. We find some non-inner and non-skew-symmetric biderivations. As applications, the characterizations of the forms of linear commuting maps and the commutative post-Lie algebra structures on t...
0
0
1
0
0
0
A Data Science Approach to Understanding Residential Water Contamination in Flint
When the residents of Flint learned that lead had contaminated their water system, the local government made water-testing kits available to them free of charge. The city government published the results of these tests, creating a valuable dataset that is key to understanding the causes and extent of the lead contami...
1
0
0
1
0
0
Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems
In this paper, we introduce a stochastic projected subgradient method for weakly convex (i.e., uniformly prox-regular) nonsmooth, nonconvex functions---a wide class of functions which includes the additive and convex composite classes. At a high-level, the method is an inexact proximal point iteration in which the st...
1
0
1
0
0
0
Solvable Integration Problems and Optimal Sample Size Selection
We compute the integral of a function or the expectation of a random variable with minimal cost and use, for our new algorithm and for upper bounds of the complexity, i.i.d. samples. Under certain assumptions it is possible to select a sample size based on a variance estimation, or -- more generally -- based on an es...
0
0
0
1
0
0
Label Stability in Multiple Instance Learning
We address the problem of \emph{instance label stability} in multiple instance learning (MIL) classifiers. These classifiers are trained only on globally annotated images (bags), but often can provide fine-grained annotations for image pixels or patches (instances). This is interesting for computer aided diagnosis (C...
1
0
0
1
0
0
New indicators for assessing the quality of in silico produced biomolecules: the case study of the aptamer-Angiopoietin-2 complex
Computational procedures to foresee the 3D structure of aptamers are in continuous progress. They constitute a crucial input to research, mainly when the crystallographic counterpart of the structures in silico produced is not present. At now, many codes are able to perform structure and binding prediction, although ...
0
0
0
0
1
0
A finite element method for elliptic problems with observational boundary data
In this paper we propose a finite element method for solving elliptic equations with the observational Dirichlet boundary data which may subject to random noises. The method is based on the weak formulation of Lagrangian multiplier. We show the convergence of the random finite element error in expectation and, when t...
0
0
1
0
0
0
Sum-Product Graphical Models
This paper introduces a new probabilistic architecture called Sum-Product Graphical Model (SPGM). SPGMs combine traits from Sum-Product Networks (SPNs) and Graphical Models (GMs): Like SPNs, SPGMs always enable tractable inference using a class of models that incorporate context specific independence. Like GMs, SPGMs...
1
0
0
1
0
0
Dependence of the Martian radiation environment on atmospheric depth: Modeling and measurement
The energetic particle environment on the Martian surface is influenced by solar and heliospheric modulation and changes in the local atmospheric pressure (or column depth). The Radiation Assessment Detector (RAD) on board the Mars Science Laboratory rover Curiosity on the surface of Mars has been measuring this effe...
0
1
0
0
0
0
Transactional Partitioning: A New Abstraction for Main-Memory Databases
The growth in variety and volume of OLTP (Online Transaction Processing) applications poses a challenge to OLTP systems to meet performance and cost demands in the existing hardware landscape. These applications are highly interactive (latency sensitive) and require update consistency. They target commodity hardware ...
1
0
0
0
0
0
Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign
Until recently, social media was seen to promote democratic discourse on social and political issues. However, this powerful communication platform has come under scrutiny for allowing hostile actors to exploit online discussions in an attempt to manipulate public opinion. A case in point is the ongoing U.S. Congress...
1
0
0
0
0
0
Event-Radar: Real-time Local Event Detection System for Geo-Tagged Tweet Streams
The local event detection is to use posting messages with geotags on social networks to reveal the related ongoing events and their locations. Recent studies have demonstrated that the geo-tagged tweet stream serves as an unprecedentedly valuable source for local event detection. Nevertheless, how to effectively extr...
1
0
0
0
0
0
Computing metric hulls in graphs
We prove that, given a closure function the smallest preimage of a closed set can be calculated in polynomial time in the number of closed sets. This confirms a conjecture of Albenque and Knauer and implies that there is a polynomial time algorithm to compute the convex hull-number of a graph, when all its convex sub...
1
0
0
0
0
0
Evolutionary games on cycles with strong selection
Evolutionary games on graphs describe how strategic interactions and population structure determine evolutionary success, quantified by the probability that a single mutant takes over a population. Graph structures, compared to the well-mixed case, can act as amplifiers or suppressors of selection by increasing or de...
0
1
0
0
0
0
Epsilon-shapes: characterizing, detecting and thickening thin features in geometric models
We focus on the analysis of planar shapes and solid objects having thin features and propose a new mathematical model to characterize them. Based on our model, that we call an epsilon-shape, we show how thin parts can be effectively and efficiently detected by an algorithm, and propose a novel approach to thicken the...
1
0
0
0
0
0
Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning
The learning of domain-invariant representations in the context of domain adaptation with neural networks is considered. We propose a new regularization method that minimizes the discrepancy between domain-specific latent feature representations directly in the hidden activation space. Although some standard distribu...
0
0
0
1
0
0
Understanding Geometry of Encoder-Decoder CNNs
Encoder-decoder networks using convolutional neural network (CNN) architecture have been extensively used in deep learning literatures thanks to its excellent performance for various inverse problems in computer vision, medical imaging, etc. However, it is still difficult to obtain coherent geometric view why such an...
1
0
0
1
0
0
AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks
ShuffleNet is a state-of-the-art light weight convolutional neural network architecture. Its basic operations include group, channel-wise convolution and channel shuffling. However, channel shuffling is manually designed empirically. Mathematically, shuffling is a multiplication by a permutation matrix. In this paper...
1
0
0
1
0
0
ACDC: Altering Control Dependence Chains for Automated Patch Generation
Once a failure is observed, the primary concern of the developer is to identify what caused it in order to repair the code that induced the incorrect behavior. Until a permanent repair is afforded, code repair patches are invaluable. The aim of this work is to devise an automated patch generation technique that proce...
1
0
0
0
0
0
Proceedings Eighth Workshop on Intersection Types and Related Systems
This volume contains a final and revised selection of papers presented at the Eighth Workshop on Intersection Types and Related Systems (ITRS 2016), held on June 26, 2016 in Porto, in affiliation with FSCD 2016.
1
0
0
0
0
0
Microlensing of Extremely Magnified Stars near Caustics of Galaxy Clusters
Recent observations of lensed galaxies at cosmological distances have detected individual stars that are extremely magnified when crossing the caustics of lensing clusters. In idealized cluster lenses with smooth mass distributions, two images of a star of radius $R$ approaching a caustic brighten as $t^{-1/2}$ and r...
0
1
0
0
0
0
NFFT meets Krylov methods: Fast matrix-vector products for the graph Laplacian of fully connected networks
The graph Laplacian is a standard tool in data science, machine learning, and image processing. The corresponding matrix inherits the complex structure of the underlying network and is in certain applications densely populated. This makes computations, in particular matrix-vector products, with the graph Laplacian a ...
0
0
0
1
0
0
Convergence rate of a simulated annealing algorithm with noisy observations
In this paper we propose a modified version of the simulated annealing algorithm for solving a stochastic global optimization problem. More precisely, we address the problem of finding a global minimizer of a function with noisy evaluations. We provide a rate of convergence and its optimized parametrization to ensure...
0
0
1
1
0
0
Trans-allelic model for prediction of peptide:MHC-II interactions
Major histocompatibility complex class two (MHC-II) molecules are trans-membrane proteins and key components of the cellular immune system. Upon recognition of foreign peptides expressed on the MHC-II binding groove, helper T cells mount an immune response against invading pathogens. Therefore, mechanistic identifica...
0
0
0
1
0
0
Improved Speech Reconstruction from Silent Video
Speechreading is the task of inferring phonetic information from visually observed articulatory facial movements, and is a notoriously difficult task for humans to perform. In this paper we present an end-to-end model based on a convolutional neural network (CNN) for generating an intelligible and natural-sounding ac...
1
0
0
0
0
0
Cluster-based Haldane state in edge-shared tetrahedral spin-cluster chain: Fedotovite K$_2$Cu$_3$O(SO$_4$)$_3$
Fedotovite K$_2$Cu$_3$O(SO$_4$)$_3$ is a candidate of new quantum spin systems, in which the edge-shared tetrahedral (EST) spin-clusters consisting of Cu$^{2+}$ are connected by weak inter-cluster couplings to from one-dimensional array. Comprehensive experimental studies by magnetic susceptibility, magnetization, he...
0
1
0
0
0
0
Super-Isolated Elliptic Curves and Abelian Surfaces in Cryptography
We call a simple abelian variety over $\mathbb{F}_p$ super-isolated if its ($\mathbb{F}_p$-rational) isogeny class contains no other varieties. The motivation for considering these varieties comes from concerns about isogeny based attacks on the discrete log problem. We heuristically estimate that the number of super...
1
0
1
0
0
0
Long Short-Term Memory (LSTM) networks with jet constituents for boosted top tagging at the LHC
Multivariate techniques based on engineered features have found wide adoption in the identification of jets resulting from hadronic top decays at the Large Hadron Collider (LHC). Recent Deep Learning developments in this area include the treatment of the calorimeter activation as an image or supplying a list of jet c...
1
0
0
1
0
0
Tangent measures of elliptic harmonic measure and applications
Tangent measure and blow-up methods, are powerful tools for understanding the relationship between the infinitesimal structure of the boundary of a domain and the behavior of its harmonic measure. We introduce a method for studying tangent measures of elliptic measures in arbitrary domains associated with (possibly n...
0
0
1
0
0
0
Aroma: Code Recommendation via Structural Code Search
Programmers often write code which have similarity to existing code written somewhere. A tool that could help programmers to search such similar code would be immensely useful. Such a tool could help programmers to extend partially written code snippets to completely implement necessary functionality, help to discove...
1
0
0
0
0
0
On Hoffman's conjectural identity
In this paper, we shall prove the equality \[ \zeta(3,\{2\}^{n},1,2)=\zeta(\{2\}^{n+3})+2\zeta(3,3,\{2\}^{n}) \] conjectured by Hoffman using certain identities among iterated integrals on $\mathbb{P}^{1}\setminus\{0,1,\infty,z\}$.
0
0
1
0
0
0
Parametric gain and wavelength conversion via third order nonlinear optics a CMOS compatible waveguide
We demonstrate sub-picosecond wavelength conversion in the C-band via four wave mixing in a 45cm long high index doped silica spiral waveguide. We achieve an on/off conversion efficiency (signal to idler) of +16.5dB as well as a parametric gain of +15dB for a peak pump power of 38W over a wavelength range of 100nm. F...
0
1
0
0
0
0
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization
In this paper, we develop a new accelerated stochastic gradient method for efficiently solving the convex regularized empirical risk minimization problem in mini-batch settings. The use of mini-batches is becoming a golden standard in the machine learning community, because mini-batch settings stabilize the gradient ...
1
0
1
1
0
0
Automatically Leveraging MapReduce Frameworks for Data-Intensive Applications
MapReduce is a popular programming paradigm for developing large-scale, data-intensive computation. Many frameworks that implement this paradigm have recently been developed. To leverage these frameworks, however, developers must become familiar with their APIs and rewrite existing code. Casper is a new tool that aut...
1
0
0
0
0
0
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise
In this paper, we propose a unified view of gradient-based algorithms for stochastic convex composite optimization. By extending the concept of estimate sequence introduced by Nesterov, we interpret a large class of stochastic optimization methods as procedures that iteratively minimize a surrogate of the objective. ...
1
0
0
1
0
0
Results of the first NaI scintillating calorimeter prototypes by COSINUS
Over almost three decades the TAUP conference has seen a remarkable momentum gain in direct dark matter search. An important accelerator were first indications for a modulating signal rate in the DAMA/NaI experiment reported in 1997. Today the presence of an annual modulation, which matches in period and phase the ex...
0
1
0
0
0
0
Deep SNP: An End-to-end Deep Neural Network with Attention-based Localization for Break-point Detection in SNP Array Genomic data
Diagnosis and risk stratification of cancer and many other diseases require the detection of genomic breakpoints as a prerequisite of calling copy number alterations (CNA). This, however, is still challenging and requires time-consuming manual curation. As deep-learning methods outperformed classical state-of-the-art...
0
0
0
0
1
0
$(L,M)$-fuzzy convex structures
In this paper, the notion of $(L,M)$-fuzzy convex structures is introduced. It is a generalization of $L$-convex structures and $M$-fuzzifying convex structures. In our definition of $(L,M)$-fuzzy convex structures, each $L$-fuzzy subset can be regarded as an $L$-convex set to some degree. The notion of convexity pre...
0
0
1
0
0
0
Passive Compliance Control of Aerial Manipulators
This paper presents a passive compliance control for aerial manipulators to achieve stable environmental interactions. The main challenge is the absence of actuation along body-planar directions of the aerial vehicle which might be required during the interaction to preserve passivity. The controller proposed in this...
1
0
0
0
0
0
The phase retrieval problem for solutions of the Helmholtz equation
In this paper we consider the phase retrieval problem for Herglotz functions, that is, solutions of the Helmholtz equation $\Delta u+\lambda^2u=0$ on domains $\Omega\subset\mathbb{R}^d$, $d\geq2$. In dimension $d=2$, if $u,v$ are two such solutions then $|u|=|v|$ implies that either $u=cv$ or $u=c\bar v$ for some $c\...
0
0
1
0
0
0
Counting intersecting and pairs of cross-intersecting families
A family of subsets of $\{1,\ldots,n\}$ is called {\it intersecting} if any two of its sets intersect. A classical result in extremal combinatorics due to Erdős, Ko, and Rado determines the maximum size of an intersecting family of $k$-subsets of $\{1,\ldots, n\}$. In this paper we study the following problem: how ma...
1
0
1
0
0
0
Zero-field Skyrmions with a High Topological Number in Itinerant Magnets
Magnetic skyrmions are swirling spin textures with topologically protected noncoplanarity. Recently, skyrmions with the topological number of unity have been extensively studied in both experiment and theory. We here show that a skyrmion crystal with an unusually high topological number of two is stabilized in itiner...
0
1
0
0
0
0
DoShiCo Challenge: Domain Shift in Control Prediction
Training deep neural network policies end-to-end for real-world applications so far requires big demonstration datasets in the real world or big sets consisting of a large variety of realistic and closely related 3D CAD models. These real or virtual data should, moreover, have very similar characteristics to the cond...
1
0
0
0
0
0
Knowledge Discovery from Layered Neural Networks based on Non-negative Task Decomposition
Interpretability has become an important issue in the machine learning field, along with the success of layered neural networks in various practical tasks. Since a trained layered neural network consists of a complex nonlinear relationship between large number of parameters, we failed to understand how they could ach...
0
0
0
1
0
0
Optimal Stopping for Interval Estimation in Bernoulli Trials
We propose an optimal sequential methodology for obtaining confidence intervals for a binomial proportion $\theta$. Assuming that an i.i.d. random sequence of Benoulli($\theta$) trials is observed sequentially, we are interested in designing a)~a stopping time $T$ that will decide when is the best time to stop sampli...
0
0
0
1
0
0
Derivation of a Non-autonomous Linear Boltzmann Equation from a Heterogeneous Rayleigh Gas
A linear Boltzmann equation with nonautonomous collision operator is rigorously derived in the Boltzmann-Grad limit for the deterministic dynamics of a Rayleigh gas where a tagged particle is undergoing hard-sphere collisions with heterogeneously distributed background particles, which do not interact among each othe...
0
0
1
0
0
0
On Blockwise Symmetric Matchgate Signatures and Higher Domain \#CSP
For any $n\geq 3$ and $ q\geq 3$, we prove that the {\sc Equality} function $(=_n)$ on $n$ variables over a domain of size $q$ cannot be realized by matchgates under holographic transformations. This is a consequence of our theorem on the structure of blockwise symmetric matchgate signatures. %due to the rank of the ...
1
0
0
0
0
0
Deconfined quantum critical points: symmetries and dualities
The deconfined quantum critical point (QCP), separating the Néel and valence bond solid phases in a 2D antiferromagnet, was proposed as an example of $2+1$D criticality fundamentally different from standard Landau-Ginzburg-Wilson-Fisher {criticality}. In this work we present multiple equivalent descriptions of deconf...
0
1
0
0
0
0
Ensemble Methods as a Defense to Adversarial Perturbations Against Deep Neural Networks
Deep learning has become the state of the art approach in many machine learning problems such as classification. It has recently been shown that deep learning is highly vulnerable to adversarial perturbations. Taking the camera systems of self-driving cars as an example, small adversarial perturbations can cause the ...
0
0
0
1
0
0
The unrolled quantum group inside Lusztig's quantum group of divided powers
In this letter we prove that the unrolled small quantum group, appearing in quantum topology, is a Hopf subalgebra of Lusztig's quantum group of divided powers. We do so by writing down non-obvious primitive elements with the right adjoint action. We also construct a new larger Hopf algebra that contains the full unr...
0
0
1
0
0
0
Forward Collision Vehicular Radar with IEEE 802.11: Feasibility Demonstration through Measurements
Increasing safety and automation in transportation systems has led to the proliferation of radar and IEEE 802.11 dedicated short range communication (DSRC) in vehicles. Current implementations of vehicular radar devices, however, are expensive, use a substantial amount of bandwidth, and are susceptible to multiple se...
1
0
0
0
0
0
Link Before You Share: Managing Privacy Policies through Blockchain
With the advent of numerous online content providers, utilities and applications, each with their own specific version of privacy policies and its associated overhead, it is becoming increasingly difficult for concerned users to manage and track the confidential information that they share with the providers. Users c...
1
0
0
0
0
0
Holistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Pooling
Accurately predicting and detecting interstitial lung disease (ILD) patterns given any computed tomography (CT) slice without any pre-processing prerequisites, such as manually delineated regions of interest (ROIs), is a clinically desirable, yet challenging goal. The majority of existing work relies on manually-prov...
1
0
0
0
0
0
Convergence Results for Neural Networks via Electrodynamics
We study whether a depth two neural network can learn another depth two network using gradient descent. Assuming a linear output node, we show that the question of whether gradient descent converges to the target function is equivalent to the following question in electrodynamics: Given $k$ fixed protons in $\mathbb{...
1
1
0
0
0
0
The norm residue symbol for higher local fields
Since the development of higher local class field theory, several explicit reciprocity laws have been constructed. In particular, there are formulas describing the higher-dimensional Hilbert symbol given, among others, by M. Kurihara, A. Zinoviev and S. Vostokov. K. Kato also has explicit formulas for the higher-dime...
0
0
1
0
0
0
Optimizing tree decompositions in MSO
The classic algorithm of Bodlaender and Kloks [J. Algorithms, 1996] solves the following problem in linear fixed-parameter time: given a tree decomposition of a graph of (possibly suboptimal) width $k$, compute an optimum-width tree decomposition of the graph. In this work, we prove that this problem can also be solv...
1
0
0
0
0
0
Nonparametric relative error estimation of the regression function for censored data
Let $ (T_i)_i$ be a sequence of independent identically distributed (i.i.d.) random variables (r.v.) of interest distributed as $ T$ and $(X_i)_i$ be a corresponding vector of covariates taking values on $ \mathbb{R}^d$. In censorship models the r.v. $T$ is subject to random censoring by another r.v. $C$. In this pap...
0
0
1
1
0
0
Intelligent Home Energy Management System for Distributed Renewable Generators, Dispatchable Residential Loads and Distributed Energy Storage Devices
This paper presents an intelligent home energy management system integrated with dispatchable loads (e.g., clothes washers and dryers), distributed renewable generators (e.g., roof-top solar panels), and distributed energy storage devices (e.g., plug-in electric vehicles). The overall goal is to reduce the total oper...
0
0
1
0
0
0
Interpretable Structure-Evolving LSTM
This paper develops a general framework for learning interpretable data representation via Long Short-Term Memory (LSTM) recurrent neural networks over hierarchal graph structures. Instead of learning LSTM models over the pre-fixed structures, we propose to further learn the intermediate interpretable multi-level gra...
1
0
0
0
0
0
On Optimization over Tail Distributions
We investigate the use of optimization to compute bounds for extremal performance measures. This approach takes a non-parametric viewpoint that aims to alleviate the issue of model misspecification possibly encountered by conventional methods in extreme event analysis. We make two contributions towards solving these ...
0
0
0
1
0
0
Isotropic covariance functions on graphs and their edges
We develop parametric classes of covariance functions on linear networks and their extension to graphs with Euclidean edges, i.e., graphs with edges viewed as line segments or more general sets with a coordinate system allowing us to consider points on the graph which are vertices or points on an edge. Our covariance...
0
0
1
1
0
0
Towards Probabilistic Formal Modeling of Robotic Cell Injection Systems
Cell injection is a technique in the domain of biological cell micro-manipulation for the delivery of small volumes of samples into the suspended or adherent cells. It has been widely applied in various areas, such as gene injection, in-vitro fertilization (IVF), intracytoplasmic sperm injection (ISCI) and drug devel...
1
0
0
0
0
0
Representations of language in a model of visually grounded speech signal
We present a visually grounded model of speech perception which projects spoken utterances and images to a joint semantic space. We use a multi-layer recurrent highway network to model the temporal nature of spoken speech, and show that it learns to extract both form and meaning-based linguistic knowledge from the in...
1
0
0
0
0
0
Long-Term Video Interpolation with Bidirectional Predictive Network
This paper considers the challenging task of long-term video interpolation. Unlike most existing methods that only generate few intermediate frames between existing adjacent ones, we attempt to speculate or imagine the procedure of an episode and further generate multiple frames between two non-consecutive frames in ...
1
0
0
0
0
0
Evolutionary dynamics of cooperation in neutral populations
Cooperation is a difficult proposition in the face of Darwinian selection. Those that defect have an evolutionary advantage over cooperators who should therefore die out. However, spatial structure enables cooperators to survive through the formation of homogeneous clusters, which is the hallmark of network reciproci...
1
0
0
0
0
0
Large global-in-time solutions to a nonlocal model of chemotaxis
We consider the parabolic-elliptic model for the chemotaxis with fractional (anomalous) diffusion. Global-in-time solutions are constructed under (nearly) optimal assumptions on the size of radial initial data. Moreover, criteria for blowup of radial solutions in terms of suitable Morrey spaces norms are derived.
0
0
1
0
0
0
Microservices: Granularity vs. Performance
Microservice Architectures (MA) have the potential to increase the agility of software development. In an era where businesses require software applications to evolve to support software emerging requirements, particularly for Internet of Things (IoT) applications, we examine the issue of microservice granularity and...
1
0
0
0
0
0
The strictly-correlated electron functional for spherically symmetric systems revisited
The strong-interaction limit of the Hohenberg-Kohn functional defines a multimarginal optimal transport problem with Coulomb cost. From physical arguments, the solution of this limit is expected to yield strictly-correlated particle positions, related to each other by co-motion functions (or optimal maps), but the ex...
0
1
0
0
0
0
A stable numerical strategy for Reynolds-Rayleigh-Plesset coupling
The coupling of Reynolds and Rayleigh-Plesset equations has been used in several works to simulate lubricated devices considering cavitation. The numerical strategies proposed so far are variants of a staggered strategy where Reynolds equation is solved considering the bubble dynamics frozen, and then the Rayleigh-Pl...
0
1
0
0
0
0
Accelerated Sparse Subspace Clustering
State-of-the-art algorithms for sparse subspace clustering perform spectral clustering on a similarity matrix typically obtained by representing each data point as a sparse combination of other points using either basis pursuit (BP) or orthogonal matching pursuit (OMP). BP-based methods are often prohibitive in pract...
1
0
0
1
0
0
Prediction of helium vapor quality in steady state Two-phase operation for SST-1 Toroidal field magnets
Steady State Superconducting Tokamak (SST-1) at the Institute for Plasma Research (IPR) is an operational device and is the first superconducting Tokamak in India. Superconducting Magnets System (SCMS) in SST-1 comprises of sixteen Toroidal field (TF) magnets and nine Poloidal Field (PF) magnets manufactured using Nb...
0
1
0
0
0
0
Synthesis of Highly Anisotropic Semiconducting GaTe Nanomaterials and Emerging Properties Enabled by Epitaxy
Pseudo-one dimensional (pseudo-1D) materials are a new-class of materials where atoms are arranged in chain like structures in two-dimensions (2D). Examples include recently discovered black phosphorus, ReS2 and ReSe2 from transition metal dichalcogenides, TiS3 and ZrS3 from transition metal trichalcogenides and most...
0
1
0
0
0
0
Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents
This paper outlines a methodological approach for designing adaptive agents driving themselves near points of criticality. Using a synthetic approach we construct a conceptual model that, instead of specifying mechanistic requirements to generate criticality, exploits the maintenance of an organizational structure ca...
1
1
0
0
0
0
Projection Free Rank-Drop Steps
The Frank-Wolfe (FW) algorithm has been widely used in solving nuclear norm constrained problems, since it does not require projections. However, FW often yields high rank intermediate iterates, which can be very expensive in time and space costs for large problems. To address this issue, we propose a rank-drop metho...
0
0
0
1
0
0