Visual analytics systems combine machine learning or other analytic techniques with interactive data visualization to promote sensemaking and analytical reasoning. It is through such techniques that people can make sense of large, complex data. While progress has been made, the tactful combination of machine learning a…
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48 results for “analytic techniques”
This paper explores how to interpret machine learning models in business process analytics.
problem The lack of interpretability in machine learning models used for predictive process analytics.
method Derives explanations using interpretable machine learning techniques to compare and contrast predictive models.
result Highlights scenarios where accuracy alone may not be sufficient in assessing the suitability of techniques used to encode event log data.
This article is written for the Proceedings of the Conference on Current Developments in Mathematics in Harvard University, November 16-17, 2007. It is an exposition of the analytic proof of the finite generation of the canonical ring for a compact complex algebraic manifold of general type. It lists and discusses the …
This paper proposes a web-based visual graph analytics platform for interactive graph mining, visualization, and real-time exploration of networks. GraphVis is fast, intuitive, and flexible, combining interactive visualizations with analytic techniques to reveal important patterns and insights for sense making, reasoni…
Analytical, free of time consuming Monte Carlo simulations, framework for credit portfolio systematic risk metrics calculations is presented. Techniques are described that allow calculation of portfolio-level systematic risk measures (standard deviation, VaR and Expected Shortfall) as well as allocation of risk down to…
Analytical, free of time consuming Monte Carlo simulations, framework for credit portfolio systematic risk metrics calculations is presented. Techniques are described that allow calculation of portfolio-level systematic risk measures (standard deviation, VaR and Expected Shortfall) as well as allocation of risk down to…
Survey visual analytics methods for detecting anomalous user behaviors.
problem Understanding and detecting anomalous user behaviors in various domains.
method Survey and classification of visual analytics methods in four categories.
result Discussion of findings and potential research directions.
Paper proves all Lagrangians unobstructed if one is, using non-archimedean analytic structure.
problem Proving the existence of bounding cochains for unobstructed Lagrangians.
method Introducing non-archimedean analytic structure and using family Floer techniques.
result All Lagrangians in a connected family are unobstructed if one is.
Semi-analytic pricing of double barrier options with time-dependent barriers and rebates at hitq-fin.CP
Efficient semi-analytic methods for pricing double barrier options with time-dependent parameters.
problem Pricing and calibration of double barrier options with time-dependent parameters.
method Two approaches: General Integral transform method and Heat Potential method.
result Semi-analytic techniques are more efficient for pricing double barrier options than traditional numerical methods.
Validation of the Replica Trick for Simple Modelscond-mat.dis-nn
We discuss replica analytic continuation using several simple models in order to prove mathematically the validity of replica analysis, which is used in a wide range of fields related to large scale complex systems. While replica analysis consists of two analytical techniques, the replica trick (or replica analytic con…
New method calculates eta invariant without analytic continuation.
problem Spectral asymmetry of non-semibounded systems.
method Direct pseudodifferential technique for curl operator.
result Eta invariant can be traced as spectral projection difference.
Leveraging Big Data Analytics in Healthcare Enhancement: Trends, Challenges and Opportunitiesstat.OT
Big data analytics improves healthcare through early detection and quality life.
problem Limited access to healthcare data hinders evidence-based decision-making.
method Analysis of healthcare data using various tools and techniques.
result Big data analytics enhances healthcare quality and patient outcomes.
Surveying pluriclosed flow on complex surfaces, suggesting a geometrization conjecture.
problem Understanding the long-term behavior of pluriclosed flow on complex surfaces.
method Analytic techniques to establish existence and convergence results.
result A geometrization conjecture for complex surfaces.
Geometric analysis on real analytic manifolds using seminorms.
problem Characterizing operations on real analytic manifolds and vector bundles.
method Using seminorms and geometric decompositions of jet bundles.
result New characterizations of real analytic mappings and operations.
Intelligent transportation systems (ITSs) will be a major component of tomorrow's smart cities. However, realizing the true potential of ITSs requires ultra-low latency and reliable data analytics solutions that can combine, in real-time, a heterogeneous mix of data stemming from the ITS network and its environment. Su…
We use neural networks as control variates with geometric integration techniques.
problem Analytic integration of neural network approximations for variance reduction.
method Integration domain subdivision using computational geometry for MLPs with continuous piecewise linear activation functions.
result Neural networks can be used as control variates with geometric integration methods.
Paper studies equations for a type of soliton with applications.
problem Analyzing a specific type of soliton structure.
method Analytic techniques to establish elliptic and integral equations.
result Established basic structural equations for almost Ricci-harmonic solitons.
For a lattice of a simply connected solvable Lie group , we describe the analytic germ in the variety of representations of at the trivial representation as an analytic germ which is linearly embedded in the analytic germ associated with the nilpotent Lie algebra determined by . By this description, under…
Totally geodesic submanifolds of the homogeneous nearly Kähler 6-manifolds and their G2-conesmath.DG
Classifies totally geodesic submanifolds in specific geometric spaces.
problem Identifying totally geodesic submanifolds in homogeneous nearly Kähler 6-manifolds and their G2-cones.
method Developed new techniques for studying totally geodesic submanifolds in analytic Riemannian manifolds, homogeneous spaces, and Riemannian cones.
result Obtained a classification of totally geodesic submanifolds in homogeneous nearly Kähler 6-manifolds and their G2-cones.
Analytic sub-Riemannian geodesics in 3D are always C1 and analytic except finitely many points.
problem Regularity of sub-Riemannian minimizing geodesics in 3D analytic manifolds.
method Investigation of totally nonholonomic analytic distributions, proof of Hausdorff dimension, and regularity of minimizing geodesics.
result Minimizing sub-Riemannian geodesics in 3D analytic manifolds are C1 and analytic except finitely many points.
Hybrid approach protects privacy while analyzing smart meter data.
problem Privacy concerns in AMI data analysis under CPUC regulations.
method Anonymization, differential privacy, federated learning, synthetic data, cryptography.
result Comprehensive privacy-preserving analytics framework for AMI data.
Paper presents a method to accurately quantify neural network uncertainty without sampling.
problem Uncertainty quantification in neural networks for reliability and robustness.
method Sample-free moment propagation technique for mean vectors and covariance matrices.
result Analytic solution for covariance of nonlinear activation functions.
Bayesian Dropoutstat.ML
Dropout has recently emerged as a powerful and simple method for training neural networks preventing co-adaptation by stochastically omitting neurons. Dropout is currently not grounded in explicit modelling assumptions which so far has precluded its adoption in Bayesian modelling. Using Bayesian entropic reasoning we s…
In this paper we prove local analytic hypoellipticity for a degenerate sum of squares of complex vector fields generalizing those of Kohn in "Hypoellipticity and Loss of Derivatives". Kohn's article is to appear in the Annals of Mathematics with an appendix by Derridj and Tartakoff proving local analyticity in that cas…
We study subgroups of fundamental groups of real analytic closed 4-manifolds with nonpositive sectional curvature. In particular, we are interested in the following question: if a subgroup of the fundamental group is not virtually free abelian, does it contain a free group of rank two ? The technique involves the theor…
We study the geometry of complete generic Ricci solitons with the aid of some geometric-analytical tools extending techniques of the usual Riemannian setting.
A simple, yet reasonably accurate, analytical technique is proposed for multi-factor structural credit portfolio models. The accuracy of the technique is demonstrated by benchmarking against Monte Carlo simulations. The approach presented here may be of high interest to practitioners looking for transparent, intuitive,…
Improved neural network approximates analytic and L^p functions efficiently.
problem Efficiently approximating analytic and L^p functions using neural networks.
method Three-dimensional ReLU network architecture for sawtooth functions, improving approximation rates.
result Substantially improved exponential approximation rates for analytic functions and general L^p functions.
Paper introduces a new metric for deforming surfaces with parabolics.
problem Deformation spaces of quasifuchsian groups with parabolics.
method Developed a mapping class group invariant pressure metric on QF(S).
result Hausdorff dimension of limit sets varies analytically over QF(S).
Paper proves gluing formula for analytic torsions using Witten deformation for non-Morse functions.
problem Analyzing analytic torsions for non-Morse functions.
method Witten deformation, Mayer-Vietoris sequences, Vishik's theory of moving boundary problems.
result Novel, purely analytic proof of the gluing formula for analytic torsions.
Study uses ML to analyze financial behavior in big data.
problem Challenges in analyzing financial big data.
method Applied machine learning to financial behavioral data.
result ML models can effectively estimate performance in financial markets.
It is commonly believed that increasing the interpretability of a machine learning model may decrease its predictive power. However, inspecting input-output relationships of those models using visual analytics, while treating them as black-box, can help to understand the reasoning behind outcomes without sacrificing pr…
It is the purpose of this article to establish a technical tool to study regularity of solutions to parabolic equations on manifolds. As applications of this technique, we prove that solutions to the Ricci-DeTurck flow, the surface diffusion flow and the mean curvature flow enjoy joint analyticity in time and space, an…
The abstract discusses how humans use visualizations in machine learning.
problem The reliance on human involvement in AI systems and analytics.
method Review of seven steps in the ML process and different visualization techniques.
result Different visualizations are used at various stages of the ML process.
Localization reveals geometric and analytic properties of the Witten genus.
problem Understanding the Witten genus and its modularity properties.
method Equivariant localization techniques and geometric interpretations.
result Identifies the elliptic Bismut-Chern character as a candidate target.
Proposes efficient Bayesian logistic regression for large sparse datasets.
problem Infeasibility of theoretical Bayesian methods for large sparse feature sets.
method Low complexity analytical approximations for sparse online logistic and probit regressions.
result Empirical results show superior performance compared to more complex methods.
In this paper, we prove equivariant Morse inequalities via Bismut-Lebeau's analytic localization techniques. As an application, we obtain Morse inequalities on compact manifold with nonempty boundary by applying equivariant Morse inequalities to the doubling manifold.
This paper investigates analytic properties of American option prices under the finite moment log-stable (FMLS) model. Under this model the price of American options is characterised by the free boundary problem of a fractional partial differential equation (FPDE) system. Using the technique of approximation we prove t…
Marketing analytics is a diverse field, with both academic researchers and practitioners coming from a range of backgrounds including marketing, expert systems, statistics, and operations research. This paper provides an integrative review at the boundary of these areas. The aim is to give researchers in the intelligen…
Sparse modeling approach to analytical continuation of imaginary-time quantum Monte Carlo datacond-mat.str-el
A new approach of solving the ill-conditioned inverse problem for analytical continuation is proposed. The root of the problem lies in the fact that even tiny noise of imaginary-time input data has a serious impact on the inferred real-frequency spectra. By means of a modern regularization technique, we eliminate redun…
Study compares traditional and machine learning methods for handling missing data in longitudinal studies.
problem Handling missing Not at Random (MNAR) and nonnormal data in longitudinal research.
method Monte Carlo simulations to assess six missing data techniques.
result FIML is most effective for MNAR data, while TSRE excels for MAR data.
UQE uses LLMs to analyze unstructured data efficiently.
problem Efficient analytics on unstructured data.
method Proposes UQE, a query engine that uses LLMs to interpret UQL queries.
result Demonstrates efficient analytics on various unstructured data types.
We consider an infinite dimensional optimization problem motivated by mathematical economics. Within the celebrated "Arbitrage Pricing Model", we use probabilistic and functional analytic techniques to show the existence of optimal strategies for investors who maximize their expected utility.
Currently, the world is witnessing a mounting avalanche of data due to the increasing number of mobile network subscribers, Internet websites, and online services. This trend is continuing to develop in a quick and diverse manner in the form of big data. Big data analytics can process large amounts of raw data and extr…
Machine learning and statistical modeling complement each other in healthcare analytics.
problem Choosing between machine learning and statistical modeling for analytics challenges.
method Choosing based on problem, data, and desired outcomes.
result Machine learning and statistical modeling are complementary, using similar principles but different tools.
Machine learning aids in clinical prediction tasks.
problem Improving accuracy in clinical predictions.
method Introduction to machine learning concepts and algorithms, followed by practical application to clinical datasets.
result Demonstrated the application of machine learning models to clinical prediction problems.
Equilibrium distributions and relaxation times in gas-like economic models: an analytical derivationq-fin.GN
A step by step procedure to derive analytically the exact dynamical evolution equations of the probability density functions (PDF) of well known kinetic wealth exchange economic models is shown. This technique gives a dynamical insight into the evolution of the PDF, e.g., allowing the calculation of its relaxation time…
This paper proposes a new method to learn integration schemes for complex ODEs.
problem Learning efficient integration schemes for non-linear ODEs and their identification.
method A novel framework to learn integration schemes that minimize an integration-related cost function.
result The proposed learning-based approach provides integration schemes close to analytical solutions.