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.
Automate residual plot assessment with R package and Shiny application
HIP method extended to multi-class, Poisson, and Zero-Inflated Poisson outcomes with an R Shiny app.
PDSim simulates and estimates commodity futures prices using polynomial diffusion models.
A new method selects important variables for clustering from dependency networks.
This paper describes structuring data and constructing plots to explore forest classification models interactively. A forest classifier is an example of an ensemble, produced by bagging multiple trees. The process of bagging and combining results from multiple trees, produces numerous diagnostics which, with interactiv…
Android and Facebook provide third-party applications with access to users' private data and the ability to perform potentially sensitive operations (e.g., post to a user's wall or place phone calls). As a security measure, these platforms restrict applications' privileges with permission systems: users must approve th…
Existing applications include a huge amount of knowledge that is out of reach for deep neural networks. This paper presents a novel approach for integrating calls to existing applications into deep learning architectures. Using this approach, we estimate each application's functionality with an estimator, which is impl…
Curved flats linked to pairs of Lie applicable surfaces.
Interactive applications incorporating high-data rate sensing and computer vision are becoming possible due to novel runtime systems and the use of parallel computation resources. To allow interactive use, such applications require careful tuning of multiple application parameters to meet required fidelity and latency …
An overview of some of the recent developments in the theory of valuations on convex sets and its generalizations to manifolds is given. The exposition is focused towards applications to integral geometry; several of such applications are discussed.
The aim of this paper is to discuss some applications of general topology in computer algorithms including modeling and simulation, and also in computer graphics and image processing. While the progress in these areas heavily depends on advances in computing hardware, the major intellectual achievements are the algorit…
Survey of deep RL in intelligent transportation systems.
TUV Austria proposes certification for ML applications to ensure reliability.
MetaDVFS uses device and application metadata to improve DVFS efficiency.
Isoparametric hypersurfaces and their application to special geometries
A New Trinomial Recombination Tree Algorithm and Its Applications
This paper reviews Douglas curvature in Finsler geometry.
We present an overview of some recent applications of Higgs bundles and the Hitchin fibration.
Survey of statistical queries and their applications.
A widely applicable Bayesian information criterion (Watanabe, 2013) is applicable for both regular and singular models in the model selection problem. This criterion tends to overestimate the log marginal likelihood. We identify an overestimating term of a widely applicable Bayesian information criterion. Adjustment of…
Multitask learning and transfer learning have proven to be useful in the field of machine learning when additional knowledge is available to help a prediction task. We aim at deriving methods following these paradigms for use in autotuning, where the goal is to find the optimal performance parameters of an application …
We consider an application involving a financial quadratic portfolio of options, when the joint underlying log-returns changes with multivariate elliptic distribution. This motivates the needs for methods for the approximation of multiple integrals over hyperboloids. A transformation is used to reduce the hyperboloid i…
Context-awareness in smart mobile applications is a growing area of study, because of it's intelligence in the applications. In order to build context-aware intelligent applications, mining contextual behavioral rules of individual smartphone users utilizing their phone log data is the key. However, to mine these rules…
We give a survey on eta invariants including methods of computation and applications in differential topology.
Survey of LLMs in finance tasks, highlighting progress and challenges.
We survey the different versions of Floer homology that can be associated to three-manifolds. We also discuss their applications, particularly to questions about surgery, homology cobordism, and four-manifolds with boundary. We then describe Floer stable homotopy types, the related Pin(2)-equivariant Seiberg-Witten Flo…
Novel GLMMNet model tackles high-cardinality categorical features in actuarial applications.
Large multi-tenant production clusters often have to handle a variety of jobs and applications with a variety of complex resource usage characteristics. It is non-trivial and non-optimal to manually create placement rules for scheduling that would decide which applications should co-locate. In this paper, we present De…
Sep-SpectralNet improves SE for broader applicability and scalability.
Explains isometric immersions and their applications.
Hierarchical beta process has found interesting applications in recent years. In this paper we present a modified hierarchical beta process prior with applications to hierarchical modeling of multiple data sources. The novel use of the prior over a hierarchical factor model allows factors to be shared across different …
A new process model for machine learning applications with quality assurance.
In this paper, we consider a problem of failure prediction in the context of predictive maintenance applications. We present a new approach for rare failures prediction, based on a general methodology, which takes into account peculiar properties of technical systems. We illustrate the applicability of the method on th…
Many Internet-of-Things (IoT) applications demand fast and accurate understanding of a few key events in their surrounding environment. Deep Convolutional Neural Networks (CNNs) have emerged as an effective approach to understand speech, images, and similar high dimensional data types. Algorithmic performance of modern…
Expands Bredon's trick for applications in geometry and topology.
Refined theorem on linear perturbations with applications in singularity theory and optimization.
The application of stochastic variance reduction to optimization has shown remarkable recent theoretical and practical success. The applicability of these techniques to the hard non-convex optimization problems encountered during training of modern deep neural networks is an open problem. We show that naive application…
In recent years, multi-armed bandit (MAB) framework has attracted a lot of attention in various applications, from recommender systems and information retrieval to healthcare and finance, due to its stellar performance combined with certain attractive properties, such as learning from less feedback. The multi-armed ban…
Deep neural networks trained over large datasets learn features that are both generic to the whole dataset, and specific to individual classes in the dataset. Learned features tend towards generic in the lower layers and specific in the higher layers of a network. Methods like fine-tuning are made possible because of t…
Paper derives Riccati equation for static spaces and proves its applications.
Noether theorem applied to variational problems on hyperbolic surfaces.
We discuss some applications of an intrinsic multipication in the space of simple loops in a surface.
Study immersions of punctured 4-manifolds for quantum automata applications.
L3Ms fine-tune LLMs with constraints for tailored applications.
We derive gradient and energy estimates for critical points of the full supersymmetric sigma model and discuss several applications.
We look at the semigroup generated by a system of heat equations. Applications to testing normality and option pricing are addressed.
Survey of de Casteljau's algorithm's applications in geometric data analysis.
VAEs help in learning latent variables for cryo-EM applications.