A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Paper identifies resting positions using EGG, ECG, respiration rate, and SpO2.
We study the space of Killing fields on the four dimensional AdS spacetime . Two subsets and are identified: (the spinor Killing fields) is constructed from imaginary Killing spinors, and (the observer Killing fields) consists of all hypersurface orthog…
For any positive integer r, we exhibit a knot Kr with (20 2 r--1 + 1) crossings whose Jones polynomial V (Kr) is equal to 1 mod-ulo 2 r. Our construction rests on a certain 20-crossing tangle T 20 which is undetectable by the Kauffman bracket polynomial pair mod 2.
We apply the Riemannian Penrose inequality and the Riemannian positive mass theorem to derive inequalities on the boundary of a class of compact Riemannian -manifolds with nonnegative scalar curvature. The boundary of such a manifold has a CMC component, i.e. a -sphere with positive constant mean curvature; and t…
BrainSurfCNN predicts task contrasts from resting-state fingerprints, improving accuracy over baseline.
We investigate activities that have different periods of duration. We define the profit intensity as a measure of this economic category. The profit intensity in a repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability di…
In recent years, significant attention has been devoted towards integrating deep learning technologies in the healthcare domain. However, to safely and practically deploy deep learning models for home health monitoring, two significant challenges must be addressed: the models should be (1) robust against noise; and (2)…
The paper tackles rested bandits with non-decreasing and concave rewards, deriving lower bounds and an efficient algorithm.
Study on spin-zero rest-mass fields using conformal geometric method.
New algorithm handles both decaying and non-decaying bandit problems.
Graph-Triggered Bandits unify rested and restless bandits with graph-defined arm interactions.
We study the smallest positive eigenvalue of the Laplace-Beltrami operator on a closed hyperbolic 3-manifold which fibers over the circle, with fiber a closed surface of genus . We show the existence of a constant only depending on so that $λ_1(M)\in [C^{-1}/{\rm vol}(M)^2, C\log {\rm vo…
We show that a tensor field of any rank integrates to zero over all broken rays if and only if it is a symmetrized covariant derivative of a lower order tensor which satisfies a symmetry condition at the reflecting part of the boundary and vanishes on the rest. This is done in a geometry with non-positive sectional cur…
FlexServe simplifies deployment of PyTorch models as REST endpoints.
As the advancement of information security, human recognition as its core technology, has absorbed an increasing amount of attention in the past few years. A myriad of biometric features including fingerprint, face, iris, have been applied to security systems, which are occasionally considered vulnerable to forgery and…
We present some stylized facts exhibited by the time series of returns of the Mexican Stock Exchange Index (IPC) and compare them to a sample of both developed (USA, UK and Japan) and emerging markets (Brazil and India). The period of study is 1997-2011. The stylized facts are related mostly to the probability distribu…
Proposes SOVR loss to improve adversarial robustness by increasing logit margins.
Training of one-vs.-rest SVMs can be parallelized over the number of classes in a straight forward way. Given enough computational resources, one-vs.-rest SVMs can thus be trained on data involving a large number of classes. The same cannot be stated, however, for the so-called all-in-one SVMs, which require solving a …
Machine learning techniques have gained prominence for the analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview of various unsupervised and supervised machine learning applications to rs-fMRI. We present a methodical taxonomy of machine learning methods in resting…
Stochastic encoding improves gender classification of brain networks from UK Biobank data.
Resting-state functional MRI (rs-fMRI) is a rich imaging modality that captures spontaneous brain activity patterns, revealing clues about the connectomic organization of the human brain. While many rs-fMRI studies have focused on static measures of functional connectivity, there has been a recent surge in examining th…
This paper proposes a practical approach for automatic sleep stage classification based on a multi-level feature learning framework and Recurrent Neural Network (RNN) classifier using heart rate and wrist actigraphy derived from a wearable device. The feature learning framework is designed to extract low- and mid-level…
The electrocardiogram (ECG) is a widely-used medical test, typically consisting of 12 voltage versus time traces collected from surface recordings over the heart. Here we hypothesize that a deep neural network can predict an important future clinical event (one-year all-cause mortality) from ECG voltage-time traces. We…
We present a method for fast resting-state fMRI spatial decomposi-tions of very large datasets, based on the reduction of the temporal dimension before applying dictionary learning on concatenated individual records from groups of subjects. Introducing a measure of correspondence between spatial decompositions of rest …
The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but wheth…
REST framework predicts stock trends by considering stock-specific and related-stock events.
New algorithm identifies best arm in rested bandit setting.
Paper breaks down risk contribution into inherent and correlation risk components.
Conditions for scalar curvature on compact manifolds under conformal deformation.
REST improves robustness of black-box models to geometric transformations.
Study examines Bitcoin's volatility and returns using stochastic volatility model.
Study of coloured invariants of torus knots using algebras.
In this paper we investigate the usage of adversarial perturbations for the purpose of privacy from human perception and model (machine) based detection. We employ adversarial perturbations for obfuscating certain variables in raw data while preserving the rest. Current adversarial perturbation methods are used for dat…
Dynamic functional connectivity (FC) has in recent years become a topic of interest in the neuroimaging community. Several models and methods exist for both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), and the results point towards the conclusion that FC exhibits dynamic changes. The e…
Study proves solenoidal injectivity for tensor fields on curved manifolds with low regularity.
Bayesian model detects altered neural circuits in MCI patients.
Resting-state brain networks represent the intrinsic state of the brain during the majority of cognitive and sensorimotor tasks. However, no study has yet presented concise predictors of task-induced vigilance variability from spectrospatial features of the pre-task, resting-state electroencephalograms (EEG). We asked …
In a rotationally symmetric space $\oM$ around an axis A (whose precise definition includes all real space forms), we consider a domain limited by two equidistant hypersurfaces orthogonal to A. Let $M \subset \oM$ be a revolution hypersurface generated by a graph over A, with boundary in and orthogonal…
The paper solves three problems related to monostable polyhedra.
In this paper, we aimed at reviewing present literature on employing nonlinear analysis in combination with machine learning methods, in depression detection or prediction task. We are focusing on an affordable data-driven approach, applicable for everyday clinical practice, and in particular, those based on electroenc…
ST-GCN improves rs-fMRI prediction accuracy by modeling spatio-temporal graph connectivity.
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate…
Diagonal Frog: High-order positivity-preserving FD schemes for anisotropic Fokker-Planck equations
We consider when a smooth vector bundle endowed with a connection possesses non-trivial, local parallel sections. This is accomplished by means of a derived flag of subsets of the bundle. The procedure is algebraic and rests upon the Frobenius Theorem.
New method controls FDR for sparse GLMs, identifying positive and negative relationships.
Study finds PLI functional connectivity feature superior for depression recognition.
We give a proof to the Li-Yau-Hamilton type inequality claimed by Perelman on the fundamental solution to the conjugate heat equation. The rest of the paper is devoted to improving the known differential inequalities of Li-Yau-Hamilton type via monotonicity formulae.
A rational homology sphere whose Heegaard Floer homology is the same as that of a lens space is called an L-space. We classify pretzel knots with any number of tangles which admit L-space surgeries. This rests on Gabai's classification of fibered pretzel links.