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
On the Statistical Efficiency of Optimal Kernel Sum Classifiers
We propose a novel combination of optimization tools with learning theory bounds in order to analyze the sample complexity of optimal kernel sum classifiers. This contrasts the typical learning theoretic results which hold for all (potentially suboptimal) classifiers. Our work also justifies assumptions made in prior...
1
0
0
1
0
0
Ultracold atoms in multiple-radiofrequency dressed adiabatic potentials
We present the first experimental demonstration of a multiple-radiofrequency dressed potential for the configurable magnetic confinement of ultracold atoms. We load cold $^{87}$Rb atoms into a double well potential with an adjustable barrier height, formed by three radiofrequencies applied to atoms in a static quadru...
0
1
0
0
0
0
Distribution Matching in Variational Inference
We show that Variational Autoencoders consistently fail to learn marginal distributions in latent and visible space. We ask whether this is a consequence of matching conditional distributions, or a limitation of explicit model and posterior distributions. We explore alternatives provided by marginal distribution matc...
0
0
0
1
0
0
Henkin constructions of models with size continuum
We survey the technique of constructing customized models of size continuum in omega steps and illustrate the method by giving new proofs of mostly old results within this rubric. One new theorem, which is joint with Saharon Shelah, is that a pseudominimal theory has an atomic model of size continuum.
0
0
1
0
0
0
Orthogonal groups in characteristic 2 acting on polytopes of high rank
We show that for all integers $m\geq 2$, and all integers $k\geq 2$, the orthogonal groups $\Orth^{\pm}(2m,\Fk)$ act on abstract regular polytopes of rank $2m$, and the symplectic groups $\Sp(2m,\Fk)$ act on abstract regular polytopes of rank $2m+1$.
0
0
1
0
0
0
Free LSD: Prior-Free Visual Landing Site Detection for Autonomous Planes
Full autonomy for fixed-wing unmanned aerial vehicles (UAVs) requires the capability to autonomously detect potential landing sites in unknown and unstructured terrain, allowing for self-governed mission completion or handling of emergency situations. In this work, we propose a perception system addressing this chall...
1
0
0
0
0
0
Semi-supervised and Active-learning Scenarios: Efficient Acoustic Model Refinement for a Low Resource Indian Language
We address the problem of efficient acoustic-model refinement (continuous retraining) using semi-supervised and active learning for a low resource Indian language, wherein the low resource constraints are having i) a small labeled corpus from which to train a baseline `seed' acoustic model and ii) a large training co...
1
0
0
0
0
0
Energy spectrum of cascade showers generated by cosmic ray muons in water
The spatial distribution of Cherenkov radiation from cascade showers generated by muons in water has been measured with Cherenkov water calorimeter (CWC) NEVOD. This result allowed to improve the techniques of treating cascade showers with unknown axes by means of CWC response analysis. The techniques of selecting th...
0
1
0
0
0
0
The limit point of the pentagram map
The pentagram map is a discrete dynamical system defined on the space of polygons in the plane. In the first paper on the subject, R. Schwartz proved that the pentagram map produces from each convex polygon a sequence of successively smaller polygons that converges exponentially to a point. We investigate the limit p...
0
0
1
0
0
0
Reconstruction formulas for Photoacoustic Imaging in Attenuating Media
In this paper we study the problem of photoacoustic inversion in a weakly attenuating medium. We present explicit reconstruction formulas in such media and show that the inversion based on such formulas is moderately ill--posed. Moreover, we present a numerical algorithm for imaging and demonstrate in numerical exper...
0
0
1
0
0
0
Rank Determination for Low-Rank Data Completion
Recently, fundamental conditions on the sampling patterns have been obtained for finite completability of low-rank matrices or tensors given the corresponding ranks. In this paper, we consider the scenario where the rank is not given and we aim to approximate the unknown rank based on the location of sampled entries ...
1
0
0
1
0
0
Network structure from rich but noisy data
Driven by growing interest in the sciences, industry, and among the broader public, a large number of empirical studies have been conducted in recent years of the structure of networks ranging from the internet and the world wide web to biological networks and social networks. The data produced by these experiments a...
1
1
0
0
0
0
Algebraic Foundations of Proof Refinement
We contribute a general apparatus for dependent tactic-based proof refinement in the LCF tradition, in which the statements of subgoals may express a dependency on the proofs of other subgoals; this form of dependency is extremely useful and can serve as an algorithmic alternative to extensions of LCF based on non-lo...
1
0
0
0
0
0
Transfer Learning for Neural Semantic Parsing
The goal of semantic parsing is to map natural language to a machine interpretable meaning representation language (MRL). One of the constraints that limits full exploration of deep learning technologies for semantic parsing is the lack of sufficient annotation training data. In this paper, we propose using sequence-...
1
0
0
0
0
0
Definable Valuations induced by multiplicative subgroups and NIP Fields
We study the algebraic implications of the non-independence property (NIP) and variants thereof (dp-minimality) on infinite fields, motivated by the conjecture that all such fields which are neither real closed nor separably closed admit a definable henselian valuation. Our results mainly focus on Hahn fields and bui...
0
0
1
0
0
0
Bridging the Gap Between Layout Pattern Sampling and Hotspot Detection via Batch Active Learning
Layout hotpot detection is one of the main steps in modern VLSI design. A typical hotspot detection flow is extremely time consuming due to the computationally expensive mask optimization and lithographic simulation. Recent researches try to facilitate the procedure with a reduced flow including feature extraction, t...
0
0
0
1
0
0
iCorr : Complex correlation method to detect origin of replication in prokaryotic and eukaryotic genomes
Computational prediction of origin of replication (ORI) has been of great interest in bioinformatics and several methods including GC Skew, Z curve, auto-correlation etc. have been explored in the past. In this paper, we have extended the auto-correlation method to predict ORI location with much higher resolution for...
0
1
0
0
0
0
On the Power Spectral Density Applied to the Analysis of Old Canvases
A routine task for art historians is painting diagnostics, such as dating or attribution. Signal processing of the X-ray image of a canvas provides useful information about its fabric. However, previous methods may fail when very old and deteriorated artworks or simply canvases of small size are studied. We present a...
1
0
1
0
0
0
Simons' type formula for slant submanifolds of complex space form
In this paper, we study a slant submanifold of a complex space form. We also obtain an integral formula of Simons' type for a Kaehlerian slant submanifold in a complex space form and apply it to prove our main result.
0
0
1
0
0
0
Eco-evolutionary feedbacks - theoretical models and perspectives
1. Theoretical models pertaining to feedbacks between ecological and evolutionary processes are prevalent in multiple biological fields. An integrative overview is currently lacking, due to little crosstalk between the fields and the use of different methodological approaches. 2. Here we review a wide range of models...
0
0
0
0
1
0
Unusual behavior of cuprates explained by heterogeneous charge localization
The cuprate high-temperature superconductors are among the most intensively studied materials, yet essential questions regarding their principal phases and the transitions between them remain unanswered. Generally thought of as doped charge-transfer insulators, these complex lamellar oxides exhibit pseudogap, strange...
0
1
0
0
0
0
An Agile Software Engineering Method to Design Blockchain Applications
Cryptocurrencies and their foundation technology, the Blockchain, are reshaping finance and economics, allowing a decentralized approach enabling trusted applications with no trusted counterpart. More recently, the Blockchain and the programs running on it, called Smart Contracts, are also finding more and more appli...
1
0
0
0
0
0
Optimizing Prediction Intervals by Tuning Random Forest via Meta-Validation
Recent studies have shown that tuning prediction models increases prediction accuracy and that Random Forest can be used to construct prediction intervals. However, to our best knowledge, no study has investigated the need to, and the manner in which one can, tune Random Forest for optimizing prediction intervals { t...
0
0
0
1
0
0
Explicit construction of RIP matrices is Ramsey-hard
Matrices $\Phi\in\R^{n\times p}$ satisfying the Restricted Isometry Property (RIP) are an important ingredient of the compressive sensing methods. While it is known that random matrices satisfy the RIP with high probability even for $n=\log^{O(1)}p$, the explicit construction of such matrices defied the repeated effo...
0
0
0
1
0
0
Rocket Launching: A Universal and Efficient Framework for Training Well-performing Light Net
Models applied on real time response task, like click-through rate (CTR) prediction model, require high accuracy and rigorous response time. Therefore, top-performing deep models of high depth and complexity are not well suited for these applications with the limitations on the inference time. In order to further imp...
1
0
0
1
0
0
The CMS HGCAL detector for HL-LHC upgrade
The High Luminosity LHC (HL-LHC) will integrate 10 times more luminosity than the LHC, posing significant challenges for radiation tolerance and event pileup on detectors, especially for forward calorimetry, and hallmarks the issue for future colliders. As part of its HL-LHC upgrade program, the CMS collaboration is ...
0
1
0
0
0
0
Complete Classification of Generalized Santha-Vazirani Sources
Let $\mathcal{F}$ be a finite alphabet and $\mathcal{D}$ be a finite set of distributions over $\mathcal{F}$. A Generalized Santha-Vazirani (GSV) source of type $(\mathcal{F}, \mathcal{D})$, introduced by Beigi, Etesami and Gohari (ICALP 2015, SICOMP 2017), is a random sequence $(F_1, \dots, F_n)$ in $\mathcal{F}^n$,...
1
0
0
0
0
0
Hermann Hankel's "On the general theory of motion of fluids", an essay including an English translation of the complete Preisschrift from 1861
The present is a companion paper to "A contemporary look at Hermann Hankel's 1861 pioneering work on Lagrangian fluid dynamics" by Frisch, Grimberg and Villone (2017). Here we present the English translation of the 1861 prize manuscript from Göttingen University "Zur allgemeinen Theorie der Bewegung der Flüssigkeiten...
0
1
1
0
0
0
Targeted Damage to Interdependent Networks
The giant mutually connected component (GMCC) of an interdependent or multiplex network collapses with a discontinuous hybrid transition under random damage to the network. If the nodes to be damaged are selected in a targeted way, the collapse of the GMCC may occur significantly sooner. Finding the minimal damage se...
1
0
0
0
0
0
The limit of the Hermitian-Yang-Mills flow on reflexive sheaves
In this paper, we study the asymptotic behavior of the Hermitian-Yang-Mills flow on a reflexive sheaf. We prove that the limiting reflexive sheaf is isomorphic to the double dual of the graded sheaf associated to the Harder-Narasimhan-Seshadri filtration, this answers a question by Bando and Siu.
0
0
1
0
0
0
High-accuracy phase-field models for brittle fracture based on a new family of degradation functions
Phase-field approaches to fracture based on energy minimization principles have been rapidly gaining popularity in recent years, and are particularly well-suited for simulating crack initiation and growth in complex fracture networks. In the phase-field framework, the surface energy associated with crack formation is...
0
1
1
0
0
0
Straggler Mitigation in Distributed Optimization Through Data Encoding
Slow running or straggler tasks can significantly reduce computation speed in distributed computation. Recently, coding-theory-inspired approaches have been applied to mitigate the effect of straggling, through embedding redundancy in certain linear computational steps of the optimization algorithm, thus completing t...
1
0
0
1
0
0
Inference Trees: Adaptive Inference with Exploration
We introduce inference trees (ITs), a new class of inference methods that build on ideas from Monte Carlo tree search to perform adaptive sampling in a manner that balances exploration with exploitation, ensures consistency, and alleviates pathologies in existing adaptive methods. ITs adaptively sample from hierarchi...
0
0
0
1
0
0
Application of backpropagation neural networks to both stages of fingerprinting based WIPS
We propose a scheme to employ backpropagation neural networks (BPNNs) for both stages of fingerprinting-based indoor positioning using WLAN/WiFi signal strengths (FWIPS): radio map construction during the offline stage, and localization during the online stage. Given a training radio map (TRM), i.e., a set of coordin...
1
0
0
1
0
0
Bayesian Bootstraps for Massive Data
Recently, two scalable adaptations of the bootstrap have been proposed: the bag of little bootstraps (BLB; Kleiner et al., 2014) and the subsampled double bootstrap (SDB; Sengupta et al., 2016). In this paper, we introduce Bayesian bootstrap analogues to the BLB and SDB that have similar theoretical and computational...
0
0
0
1
0
0
Show, Adapt and Tell: Adversarial Training of Cross-domain Image Captioner
Impressive image captioning results are achieved in domains with plenty of training image and sentence pairs (e.g., MSCOCO). However, transferring to a target domain with significant domain shifts but no paired training data (referred to as cross-domain image captioning) remains largely unexplored. We propose a novel...
1
0
0
0
0
0
Faster Fuzzing: Reinitialization with Deep Neural Models
We improve the performance of the American Fuzzy Lop (AFL) fuzz testing framework by using Generative Adversarial Network (GAN) models to reinitialize the system with novel seed files. We assess performance based on the temporal rate at which we produce novel and unseen code paths. We compare this approach to seed fi...
1
0
0
0
0
0
Contego: An Adaptive Framework for Integrating Security Tasks in Real-Time Systems
Embedded real-time systems (RTS) are pervasive. Many modern RTS are exposed to unknown security flaws, and threats to RTS are growing in both number and sophistication. However, until recently, cyber-security considerations were an afterthought in the design of such systems. Any security mechanisms integrated into RT...
1
0
0
0
0
0
Second Order Analysis for Joint Source-Channel Coding with Markovian Source
We derive the second order rates of joint source-channel coding, whose source obeys an irreducible and ergodic Markov process when the channel is a discrete memoryless, while a previous study solved it only in a special case. We also compare the joint source-channel scheme with the separation scheme in the second ord...
1
0
1
0
0
0
Interface currents and magnetization in singlet-triplet superconducting heterostructures: Role of chiral and helical domains
Chiral and helical domain walls are generic defects of topological spin-triplet superconductors. We study theoretically the magnetic and transport properties of superconducting singlet-triplet-singlet heterostructure as a function of the phase difference between the singlet leads in the presence of chiral and helical...
0
1
0
0
0
0
Implicit Weight Uncertainty in Neural Networks
Modern neural networks tend to be overconfident on unseen, noisy or incorrectly labelled data and do not produce meaningful uncertainty measures. Bayesian deep learning aims to address this shortcoming with variational approximations (such as Bayes by Backprop or Multiplicative Normalising Flows). However, current ap...
1
0
0
1
0
0
A systematic analysis of the XMM-Newton background: III. Impact of the magnetospheric environment
A detailed characterization of the particle induced background is fundamental for many of the scientific objectives of the Athena X-ray telescope, thus an adequate knowledge of the background that will be encountered by Athena is desirable. Current X-ray telescopes have shown that the intensity of the particle induce...
0
1
0
0
0
0
DeepPermNet: Visual Permutation Learning
We present a principled approach to uncover the structure of visual data by solving a novel deep learning task coined visual permutation learning. The goal of this task is to find the permutation that recovers the structure of data from shuffled versions of it. In the case of natural images, this task boils down to r...
1
0
0
0
0
0
ADE String Chains and Mirror Symmetry
6d superconformal field theories (SCFTs) are the SCFTs in the highest possible dimension. They can be geometrically engineered in F-theory by compactifying on non-compact elliptic Calabi-Yau manifolds. In this paper we focus on the class of SCFTs whose base geometry is determined by $-2$ curves intersecting according...
0
0
1
0
0
0
(non)-automaticity of completely multiplicative sequences having negligible many non-trivial prime factors
In this article we consider the completely multiplicative sequences $(a_n)_{n \in \mathbf{N}}$ defined on a field $\mathbf{K}$ and satisfying $$\sum_{p| p \leq n, a_p \neq 1, p \in \mathbf{P}}\frac{1}{p}<\infty,$$ where $\mathbf{P}$ is the set of prime numbers. We prove that if such sequences are automatic then they ...
0
0
1
0
0
0
Timing Aware Dummy Metal Fill Methodology
In this paper, we analyzed parasitic coupling capacitance coming from dummy metal fill and its impact on timing. Based on the modeling, we proposed two approaches to minimize the timing impact from dummy metal fill. The first approach applies more spacing between critical nets and metal fill, while the second approac...
1
0
0
0
0
0
Asymptotic efficiency of the proportional compensation scheme for a large number of producers
We consider a manager, who allocates some fixed total payment amount between $N$ rational agents in order to maximize the aggregate production. The profit of $i$-th agent is the difference between the compensation (reward) obtained from the manager and the production cost. We compare (i) the \emph{normative} compensa...
1
0
0
0
0
0
Non-equilibrium statistical mechanics of continuous attractors
Continuous attractors have been used to understand recent neuroscience experiments where persistent activity patterns encode internal representations of external attributes like head direction or spatial location. However, the conditions under which the emergent bump of neural activity in such networks can be manipul...
0
0
0
0
1
0
Some results on the existence of t-all-or-nothing transforms over arbitrary alphabets
A $(t, s, v)$-all-or-nothing transform is a bijective mapping defined on $s$-tuples over an alphabet of size $v$, which satisfies the condition that the values of any $t$ input co-ordinates are completely undetermined, given only the values of any $s-t$ output co-ordinates. The main question we address in this paper ...
1
0
1
0
0
0
Exhaustive Exploration of the Failure-oblivious Computing Search Space
High-availability of software systems requires automated handling of crashes in presence of errors. Failure-oblivious computing is one technique that aims to achieve high availability. We note that failure-obliviousness has not been studied in depth yet, and there is very few study that helps understand why failure-o...
1
0
0
0
0
0
Theoretical Accuracy in Cosmological Growth Estimation
We elucidate the importance of the consistent treatment of gravity-model specific non-linearities when estimating the growth of cosmological structures from redshift space distortions (RSD). Within the context of standard perturbation theory (SPT), we compare the predictions of two theoretical templates with redshift...
0
1
0
0
0
0
Model-Robust Counterfactual Prediction Method
We develop a novel method for counterfactual analysis based on observational data using prediction intervals for units under different exposures. Unlike methods that target heterogeneous or conditional average treatment effects of an exposure, the proposed approach aims to take into account the irreducible dispersion...
0
0
1
1
0
0
Exponentiated Generalized Pareto Distribution: Properties and applications towards Extreme Value Theory
The Generalized Pareto Distribution (GPD) plays a central role in modelling heavy tail phenomena in many applications. Applying the GPD to actual datasets however is a non-trivial task. One common way suggested in the literature to investigate the tail behaviour is to take logarithm to the original dataset in order t...
0
0
1
1
0
0
Learning with Average Top-k Loss
In this work, we introduce the {\em average top-$k$} (\atk) loss as a new aggregate loss for supervised learning, which is the average over the $k$ largest individual losses over a training dataset. We show that the \atk loss is a natural generalization of the two widely used aggregate losses, namely the average loss...
1
0
0
1
0
0
Reflexive polytopes arising from perfect graphs
Reflexive polytopes form one of the distinguished classes of lattice polytopes. Especially reflexive polytopes which possess the integer decomposition property are of interest. In the present paper, by virtue of the algebraic technique on Grönbner bases, a new class of reflexive polytopes which possess the integer de...
0
0
1
0
0
0
Meta Networks
Neural networks have been successfully applied in applications with a large amount of labeled data. However, the task of rapid generalization on new concepts with small training data while preserving performances on previously learned ones still presents a significant challenge to neural network models. In this work,...
1
0
0
1
0
0
Variable selection for clustering with Gaussian mixture models: state of the art
The mixture models have become widely used in clustering, given its probabilistic framework in which its based, however, for modern databases that are characterized by their large size, these models behave disappointingly in setting out the model, making essential the selection of relevant variables for this type of ...
1
0
0
1
0
0
Analysing Magnetism Using Scanning SQUID Microscopy
Scanning superconducting quantum interference device microscopy (SSM) is a scanning probe technique that images local magnetic flux, which allows for mapping of magnetic fields with high field and spatial accuracy. Many studies involving SSM have been published in the last decades, using SSM to make qualitative state...
0
1
0
0
0
0
Algorithms for solving optimization problems arising from deep neural net models: nonsmooth problems
Machine Learning models incorporating multiple layered learning networks have been seen to provide effective models for various classification problems. The resulting optimization problem to solve for the optimal vector minimizing the empirical risk is, however, highly nonconvex. This alone presents a challenge to ap...
0
0
0
1
0
0
On the essential self-adjointness of singular sub-Laplacians
We prove a general essential self-adjointness criterion for sub-Laplacians on complete sub-Riemannian manifolds, defined with respect to singular measures. As a consequence, we show that the intrinsic sub-Laplacian (i.e. defined w.r.t. Popp's measure) is essentially self-adjoint on the equiregular connected component...
0
0
1
0
0
0
Are Saddles Good Enough for Deep Learning?
Recent years have seen a growing interest in understanding deep neural networks from an optimization perspective. It is understood now that converging to low-cost local minima is sufficient for such models to become effective in practice. However, in this work, we propose a new hypothesis based on recent theoretical ...
1
0
0
1
0
0
Monotonicity and enclosure methods for the p-Laplace equation
We show that the convex hull of a monotone perturbation of a homogeneous background conductivity in the $p$-conductivity equation is determined by knowledge of the nonlinear Dirichlet-Neumann operator. We give two independent proofs, one of which is based on the monotonicity method and the other on the enclosure meth...
0
0
1
0
0
0
Tension and chemical efficiency of Myosin-II motors
Recent experiments demonstrate that molecular motors from the Myosin II family serve as cross-links inducing active tension in the cytoskeletal network. Here we revise the Brownian ratchet model, previously studied in the context of active transport along polymer tracks, in setups resembling a motor in a polymer netw...
0
1
0
0
0
0
Token-based Function Computation with Memory
In distributed function computation, each node has an initial value and the goal is to compute a function of these values in a distributed manner. In this paper, we propose a novel token-based approach to compute a wide class of target functions to which we refer as "Token-based function Computation with Memory" (TCM...
1
0
0
1
0
0
Simple property of heterogeneous aspiration dynamics: Beyond weak selection
How individuals adapt their behavior in cultural evolution remains elusive. Theoretical studies have shown that the update rules chosen to model individual decision making can dramatically modify the evolutionary outcome of the population as a whole. This hints at the complexities of considering the personality of in...
0
0
0
0
1
0
Warm dark matter and the ionization history of the Universe
In warm dark matter scenarios structure formation is suppressed on small scales with respect to the cold dark matter case, reducing the number of low-mass halos and the fraction of ionized gas at high redshifts and thus, delaying reionization. This has an impact on the ionization history of the Universe and measureme...
0
1
0
0
0
0
High quality factor manganese-doped aluminum lumped-element kinetic inductance detectors sensitive to frequencies below 100 GHz
Aluminum lumped-element kinetic inductance detectors (LEKIDs) sensitive to millimeter-wave photons have been shown to exhibit high quality factors, making them highly sensitive and multiplexable. The superconducting gap of aluminum limits aluminum LEKIDs to photon frequencies above 100 GHz. Manganese-doped aluminum (...
0
1
0
0
0
0
Tetramer Bound States in Heteronuclear Systems
We calculate the universal spectrum of trimer and tetramer states in heteronuclear mixtures of ultracold atoms with different masses in the vicinity of the heavy-light dimer threshold. To extract the energies, we solve the three- and four-body problem for simple two- and three-body potentials tuned to the universal r...
0
1
0
0
0
0
Dark Energy Cosmological Models with General forms of Scale Factor
In this paper, we have constructed dark energy models in an anisotropic Bianchi-V space-time and studied the role of anisotropy in the evolution of dark energy. We have considered anisotropic dark energy fluid with different pressure gradients along different spatial directions. In order to obtain a deterministic sol...
0
1
0
0
0
0
Mutual Kernel Matrix Completion
With the huge influx of various data nowadays, extracting knowledge from them has become an interesting but tedious task among data scientists, particularly when the data come in heterogeneous form and have missing information. Many data completion techniques had been introduced, especially in the advent of kernel me...
1
0
0
1
0
0
Quantum Klein Space and Superspace
We give an algebraic quantization, in the sense of quantum groups, of the complex Minkowski space, and we examine the real forms corresponding to the signatures $(3,1)$, $(2,2)$, $(4,0)$, constructing the corresponding quantum metrics and providing an explicit presentation of the quantized coordinate algebras. In par...
0
0
1
0
0
0
Bayesian Lasso Posterior Sampling via Parallelized Measure Transport
It is well known that the Lasso can be interpreted as a Bayesian posterior mode estimate with a Laplacian prior. Obtaining samples from the full posterior distribution, the Bayesian Lasso, confers major advantages in performance as compared to having only the Lasso point estimate. Traditionally, the Bayesian Lasso is...
0
0
0
1
0
0
Endogeneous Dynamics of Intraday Liquidity
In this paper we investigate the endogenous information contained in four liquidity variables at a five minutes time scale on equity markets around the world: the traded volume, the bid-ask spread, the volatility and the volume at first limits of the orderbook. In the spirit of Granger causality, we measure the level...
0
0
0
0
0
1
Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks
Data diversity is critical to success when training deep learning models. Medical imaging data sets are often imbalanced as pathologic findings are generally rare, which introduces significant challenges when training deep learning models. In this work, we propose a method to generate synthetic abnormal MRI images wi...
0
0
0
1
0
0
Adaptive Feature Representation for Visual Tracking
Robust feature representation plays significant role in visual tracking. However, it remains a challenging issue, since many factors may affect the experimental performance. The existing method which combine different features by setting them equally with the fixed weight could hardly solve the issues, due to the dif...
1
0
0
0
0
0
An analysis of the SPARSEVA estimate for the finite sample data case
In this paper, we develop an upper bound for the SPARSEVA (SPARSe Estimation based on a VAlidation criterion) estimation error in a general scheme, i.e., when the cost function is strongly convex and the regularized norm is decomposable for a pair of subspaces. We show how this general bound can be applied to a spars...
0
0
1
1
0
0
The Remarkable Similarity of Massive Galaxy Clusters From z~0 to z~1.9
We present the results of a Chandra X-ray survey of the 8 most massive galaxy clusters at z>1.2 in the South Pole Telescope 2500 deg^2 survey. We combine this sample with previously-published Chandra observations of 49 massive X-ray-selected clusters at 0<z<0.1 and 90 SZ-selected clusters at 0.25<z<1.2 to constrain t...
0
1
0
0
0
0
Rigorous estimates for the relegation algorithm
We revisit the relegation algorithm by Deprit et al. (Celest. Mech. Dyn. Astron. 79:157-182, 2001) in the light of the rigorous Nekhoroshev's like theory. This relatively recent algorithm is nowadays widely used for implementing closed form analytic perturbation theories, as it generalises the classical Birkhoff norm...
0
1
0
0
0
0
Linear Pentapods with a Simple Singularity Variety
There exists a bijection between the configuration space of a linear pentapod and all points $(u,v,w,p_x,p_y,p_z)\in\mathbb{R}^{6}$ located on the singular quadric $\Gamma: u^2+v^2+w^2=1$, where $(u,v,w)$ determines the orientation of the linear platform and $(p_x,p_y,p_z)$ its position. Then the set of all singular ...
1
0
0
0
0
0
Neural Networks as Interacting Particle Systems: Asymptotic Convexity of the Loss Landscape and Universal Scaling of the Approximation Error
Neural networks, a central tool in machine learning, have demonstrated remarkable, high fidelity performance on image recognition and classification tasks. These successes evince an ability to accurately represent high dimensional functions, potentially of great use in computational and applied mathematics. That said...
0
0
0
1
0
0
Adaptive Similar Triangles Method: a Stable Alternative to Sinkhorn's Algorithm for Regularized Optimal Transport
In this paper, we are motivated by two important applications: entropy-regularized optimal transport problem and road or IP traffic demand matrix estimation by entropy model. Both of them include solving a special type of optimization problem with linear equality constraints and objective given as a sum of an entropy...
0
0
1
0
0
0
Images of Ideals under Derivations and $\mathcal E$-Derivations of Univariate Polynomial Algebras over a Field of Characteristic Zero
Let $K$ be a field of characteristic zero and $x$ a free variable. A $K$-$\mathcal E$-derivation of $K[x]$ is a $K$-linear map of the form $\operatorname{I}-\phi$ for some $K$-algebra endomorphism $\phi$ of $K[x]$, where $\operatorname{I}$ denotes the identity map of $K[x]$. In this paper we study the image of an ide...
0
0
1
0
0
0
Maximum genus of the Jenga like configurations
We treat the boundary of the union of blocks in the Jenga game as a surface with a polyhedral structure and consider its genus. We generalize the game and determine the maximum genus of the generalized game.
0
0
1
0
0
0
A Decidable Very Expressive Description Logic for Databases (Extended Version)
We introduce $\mathcal{DLR}^+$, an extension of the n-ary propositionally closed description logic $\mathcal{DLR}$ to deal with attribute-labelled tuples (generalising the positional notation), projections of relations, and global and local objectification of relations, able to express inclusion, functional, key, and...
1
0
0
0
0
0
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction
Developing a Brain-Computer Interface~(BCI) for seizure prediction can help epileptic patients have a better quality of life. However, there are many difficulties and challenges in developing such a system as a real-life support for patients. Because of the nonstationary nature of EEG signals, normal and seizure patt...
1
0
0
1
0
0
Centrality measures for graphons: Accounting for uncertainty in networks
As relational datasets modeled as graphs keep increasing in size and their data-acquisition is permeated by uncertainty, graph-based analysis techniques can become computationally and conceptually challenging. In particular, node centrality measures rely on the assumption that the graph is perfectly known -- a premis...
1
0
1
1
0
0
A time-periodic mechanical analog of the quantum harmonic oscillator
We theoretically investigate the stability and linear oscillatory behavior of a naturally unstable particle whose potential energy is harmonically modulated. We find this fundamental dynamical system is analogous in time to a quantum harmonic oscillator. In a certain modulation limit, a.k.a. the Kapitza regime, the m...
0
1
0
0
0
0
Anharmonicity and the isotope effect in superconducting lithium at high pressures: a first-principles approach
Recent experiments [Schaeffer 2015] have shown that lithium presents an extremely anomalous isotope effect in the 15-25 GPa pressure range. In this article we have calculated the anharmonic phonon dispersion of $\mathrm{^7Li}$ and $\mathrm{^6Li}$ under pressure, their superconducting transition temperatures, and the ...
0
1
0
0
0
0
Time-resolved polarimetry of the superluminous SN 2015bn with the Nordic Optical Telescope
We present imaging polarimetry of the superluminous supernova SN 2015bn, obtained over nine epochs between $-$20 and $+$46 days with the Nordic Optical Telescope. This was a nearby, slowly-evolving Type I superluminous supernova that has been studied extensively and for which two epochs of spectropolarimetry are also...
0
1
0
0
0
0
Deep Bayesian Active Learning with Image Data
Even though active learning forms an important pillar of machine learning, deep learning tools are not prevalent within it. Deep learning poses several difficulties when used in an active learning setting. First, active learning (AL) methods generally rely on being able to learn and update models from small amounts o...
1
0
0
1
0
0
Robust Optical Flow Estimation in Rainy Scenes
Optical flow estimation in the rainy scenes is challenging due to background degradation introduced by rain streaks and rain accumulation effects in the scene. Rain accumulation effect refers to poor visibility of remote objects due to the intense rainfall. Most existing optical flow methods are erroneous when applie...
1
0
0
0
0
0
Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation and Experimentation
Among the many additive manufacturing (AM) processes for metallic materials, selective laser melting (SLM) is arguably the most versatile in terms of its potential to realize complex geometries along with tailored microstructure. However, the complexity of the SLM process, and the need for predictive relation of powd...
1
1
0
0
0
0
Numerical Methods for Pulmonary Image Registration
Due to complexity and invisibility of human organs, diagnosticians need to analyze medical images to determine where the lesion region is, and which kind of disease is, in order to make precise diagnoses. For satisfying clinical purposes through analyzing medical images, registration plays an essential role. For inst...
0
1
0
0
0
0
Solving Non-parametric Inverse Problem in Continuous Markov Random Field using Loopy Belief Propagation
In this paper, we address the inverse problem, or the statistical machine learning problem, in Markov random fields with a non-parametric pair-wise energy function with continuous variables. The inverse problem is formulated by maximum likelihood estimation. The exact treatment of maximum likelihood estimation is int...
1
1
0
1
0
0
Topology Adaptive Graph Convolutional Networks
Spectral graph convolutional neural networks (CNNs) require approximation to the convolution to alleviate the computational complexity, resulting in performance loss. This paper proposes the topology adaptive graph convolutional network (TAGCN), a novel graph convolutional network defined in the vertex domain. We pro...
1
0
0
1
0
0
Suspensions of finite-size neutrally-buoyant spheres in turbulent duct flow
We study the turbulent square duct flow of dense suspensions of neutrally-buoyant spherical particles. Direct numerical simulations (DNS) are performed in the range of volume fractions $\phi=0-0.2$, using the immersed boundary method (IBM) to account for the dispersed phase. Based on the hydraulic diameter a Reynolds...
0
1
0
0
0
0
Far-from-equilibrium transport of excited carriers in nanostructures
Transport of charged carriers in regimes of strong non-equilibrium is critical in a wide array of applications ranging from solar energy conversion and semiconductor devices to quantum information. Plasmonic hot-carrier science brings this regime of transport physics to the forefront since photo-excited carriers must...
0
1
0
0
0
0
On annihilators of bounded $(\frak g, \frak k)$-modules
Let $\frak g$ be a semisimple Lie algebra and $\frak k\subset\frak g$ be a reductive subalgebra. We say that a $\frak g$-module $M$ is a bounded $(\frak g, \frak k)$-module if $M$ is a direct sum of simple finite-dimensional $\frak k$-modules and the multiplicities of all simple $\frak k$-modules in that direct sum a...
0
0
1
0
0
0
Neutron Star Planets: Atmospheric processes and habitability
Of the roughly 3000 neutron stars known, only a handful have sub-stellar companions. The most famous of these are the low-mass planets around the millisecond pulsar B1257+12. New evidence indicates that observational biases could still hide a wide variety of planetary systems around most neutron stars. We consider th...
0
1
0
0
0
0
Discrete Time-Crystalline Order in Cavity and Circuit QED Systems
Discrete time crystals are a recently proposed and experimentally observed out-of-equilibrium dynamical phase of Floquet systems, where the stroboscopic evolution of a local observable repeats itself at an integer multiple of the driving period. We address this issue in a driven-dissipative setup, focusing on the mod...
0
1
0
0
0
0