Higgs bundles used in new applications.
problem None explicitly stated in the abstract.
method Overview of recent applications.
result Applications of Higgs bundles.
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…
New methods improve autotuning of exascale applications by 1.5x.
problem Finding optimal performance parameters for exascale applications.
method Multitask and transfer learning for autotuning.
result Average 1.5x improvement in application runtime.
Curved flats linked to pairs of Lie applicable surfaces.
problem Understanding curved flats in Lie sphere geometry.
method One-to-one correspondence with pairs of Demoulin families of Lie applicable surfaces via Darboux transformation.
result Curved flats correspond to specific Lie applicable surface pairs.
DeepPlace learns to place applications in clusters using RL.
problem Manual placement rules for scheduling are non-trivial and suboptimal.
method Uses Deep Reinforcement Learning to learn optimal placement rules.
result Reduces resource competition and optimizes cluster utilization.
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.
problem Optimizing traffic signals and autonomous driving using deep RL.
method Comprehensive review of deep RL applications in traffic control and autonomous driving.
result Summarizes existing works in deep RL-based transportation applications.
Adjustment reduces bias in widely applicable Bayesian information criterion.
problem Overestimation of widely applicable Bayesian information criterion.
method Identified and adjusted an overestimating term in the criterion.
result Asymptotically unbiased estimator of log marginal likelihood.
The study proves estimates for transverse nonlinear equations on Sasakian manifolds with applications in geometry.
problem Estimating transverse fully nonlinear equations on Sasakian manifolds.
method Proving a priori estimates for transverse fully nonlinear equations.
result The study proves estimates for transverse fully nonlinear equations on Sasakian manifolds and gives geometric applications.
TUV Austria proposes certification for ML applications to ensure reliability.
problem Ensuring trust in AI applications to meet societal reliance requirements.
method Holistic approach analyzing security, functionality, data quality, ethics, and criticality levels.
result Certification process for low-risk ML applications in supervised learning.
MetaDVFS uses device and application metadata to improve DVFS efficiency.
problem Improving energy efficiency in mobile platforms with diverse applications and hardware.
method Formulates DVFS as a multi-task reinforcement learning problem and introduces MetaDVFS, leveraging metadata for knowledge transfer.
result MetaDVFS achieves up to 26% improvement in Quality of Experience and up to 17% improvement in Performance-Power Ratio.
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.
problem Exploring Douglas curvature in Finsler spaces.
method Historical review, characterizations, generalizations, and applications.
result Significance and applications of Douglas curvature in Finsler geometry.
Survey of statistical queries and their applications.
problem Understanding statistical queries and their applications.
method Exploration of statistical queries model, definitions, and connections to learnability.
result Connections to learnability and applications in optimization, evolvability, and differential privacy.
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…
Survey of multi-armed bandit applications in various fields.
problem Optimizing decisions with limited feedback in diverse contexts.
method Comprehensive review of recent developments and trends.
result Identification of important current trends and future directions.
Survey of LLMs in finance tasks, highlighting progress and challenges.
problem Transforming financial practices with advanced LLMs.
method Exploration of various financial tasks, categorization, and analysis of methodologies.
result Unlocking novel opportunities for financial applications with LLMs.
We give a survey on eta invariants including methods of computation and applications in differential topology.
Novel GLMMNet model tackles high-cardinality categorical features in actuarial applications.
problem Inadequate encoding methods for high-cardinality categorical features in actuarial data.
method Generalised Linear Mixed Model Neural Network (GLMMNet) integrating a generalised linear mixed model in a deep learning framework.
result GLMMNet often outperforms or performs comparably with entity embedded neural networks, providing transparency.
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…
Sep-SpectralNet improves SE for broader applicability and scalability.
problem Three main drawbacks of current SE implementations: generalizability, scalability, and eigenvectors separation.
method Sep-SpectralNet extends SpectralNet with an eigenvector separation post-processing step.
result Sep-SpectralNet achieves consistent SE approximation and generalization, enhancing scalability and applicability.
Explains isometric immersions and their applications.
problem Isometric immersions and their applications in math and physics.
method Historical overview and applications.
result Explains the importance and applications of isometric immersions.
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.
problem Lack of standard process model for machine learning applications.
method Six-phase process model with quality assurance methodology.
result Proposes a new process model for machine learning applications.
Expands Bredon's trick for applications in geometry and topology.
problem Local-to-global extension principles in geometric and topological contexts.
method Novel applications and frameworks for stratified pseudomanifolds, Ricci flow, and persistent homology.
result Establishes Bredon's trick as a unifying framework.
Refined theorem on linear perturbations with applications in singularity theory and optimization.
problem Linear perturbations and their implications in singularity theory and optimization.
method New perspective of Hausdorff measures for refined transversality theorem.
result Applications in singularity theory and optimization.
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.
problem Deriving Riccati equation for static spaces.
method Proving splitting theorem and connectivity of conformal boundary.
result Establishes compactness of universal covering for static triples.
Noether theorem applied to variational problems on hyperbolic surfaces.
problem Variational problems on hyperbolic surfaces.
method Noether's theorem on symmetry and conservation laws.
result Application to geometric 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.
problem Existence of immersions between specific 4-manifolds.
method Analyzing immersions of punctured 4-manifolds to establish a partial order.
result Established a partial order on closed 4-manifolds via immersions.
L3Ms fine-tune LLMs with constraints for tailored applications.
problem Inadequate alignment of LLMs for diverse applications.
method Formulate SFT and alignment as constrained optimization, using logarithmic barriers.
result Versatile and effective in achieving tailored alignments for various applications.
Survey of de Casteljau's algorithm's applications in geometric data analysis.
problem No specific problem stated; focuses on algorithm applications.
method Constructive approach to generalize parametric smooth curves to manifolds.
result Algorithm provides principled way to analyze geometric data.
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.
VAEs help in learning latent variables for cryo-EM applications.
problem Learning latent variables for cryo-EM data.
method Used VAEs for latent variable learning, focusing on the encoder's role.
result The encoder of the VAE in cryo-EM applications resembles traditional latent variable representations.
A method to analyze maps into circles with singularities.
problem Analyzing maps with singularities into circles.
method Renormalization of Dirichlet Lagrangian for S1-harmonic maps. result Applications in Willmore energy and frame energies.
This paper discusses issues in mining user behavioral rules for context-aware mobile apps.
problem Mining contextual behavioral rules from smartphone data.
method Addressing quality of data, relevancy of contexts, discretization, rule discovery, semantic understanding, and dynamic rule updating.
result Potential solutions for mining user behavioral rules for context-aware mobile apps.
In this paper we give three applications of a method to prove h-principles on closed manifolds. Under weaker conditions this method proves a homological h-principle, under stronger conditions it proves a homotopical one. The three applications are as follows: a homotopical version of Vassiliev's h-principle, the contra…
Study n-superharmonic functions and their geometric applications.
problem Asymptotic behavior of n-superharmonic functions at isolated singularities. method Using Wolff potential, n-capacity estimates, and Adams-Moser-Trudinger inequality. result Strong n-capacity lower bound estimate for geometric applications. The paper derives inequalities for Riemannian submersions and their applications.
problem Characterizing Casorati inequalities for Riemannian submersions.
method Algebraic and geometric analysis of Casorati inequalities for normalised scalar and Casorati curvatures.
result Characterization of equality cases for Casorati inequalities in Riemannian submersions.
Graph kernels assess graph similarity for various applications.
problem Assessing similarity between graphs for predictions.
method Review and comparison of existing graph kernels.
result State-of-the-art graph kernels reviewed and compared.
Absolute parallelism geometry is frequently used for physical applications. It has two main defects, from the point of view of applications. The first is the identical vanishing of its curvature tensor. The second is that its autoparallel paths do not represent physical trajectories. The present work shows how these de…
In this short note, we present certain generalized versions of the commutator formulas of some natural operators on manifolds, and give some applications.