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…
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48 results for “interactive analytics”
Loss Data Analyticsq-fin.RM
Loss Data Analytics is an interactive, online, freely available text. The idea behind the name Loss Data Analytics is to integrate classical loss data models from applied probability with modern analytic tools. In particular, we seek to recognize that big data (including social media and usage based insurance) are here…
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.
We have recently seen many successful applications of recurrent neural networks (RNNs) on electronic medical records (EMRs), which contain histories of patients' diagnoses, medications, and other various events, in order to predict the current and future states of patients. Despite the strong performance of RNNs, it is…
SeqFM models dynamic and sequential features for better predictive analytics.
problem Inadequate handling of sequential dependencies in existing FM-based models.
method Introduces SeqFM, a novel model that incorporates multi-view self-attention to model static, dynamic, and their interactions.
result SeqFM outperforms existing models in ranking, classification, and regression tasks on six large-scale datasets.
Interactive model analysis, the process of understanding, diagnosing, and refining a machine learning model with the help of interactive visualization, is very important for users to efficiently solve real-world artificial intelligence and data mining problems. Dramatic advances in big data analytics has led to a wide …
Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awarenesscs.SI
Interactive learning improves real-time tweet classification for situational awareness.
problem Difficulty in identifying relevant tweets from noisy social media data.
method Interactive learning framework that incorporates user feedback in real-time.
result Our approach outperforms state-of-the-art models in real-time tweet classification.
Content Based Player and Game Interaction Model for Game Recommendation in the Cold Start settingcs.IR
Paper presents content-based models for game recommendation in cold start scenarios.
problem Cold start problem in game recommendation where new games and players have no historical data.
method Uses survey data to develop content-based interaction models that generalize to new games, players, and both.
result Content models outperform collaborative filtering in predicting new interactions.
Analyzes how uncertainty in financial networks affects stability.
problem Understanding how uncertainty in financial networks impacts stability.
method Introduced a minimal stochastic dynamical model of the interbank network with linear interactions. Derived the interaction correction to the stress expectation and studied it on the short-medium timescale.
result Interactions increase the stress expectation on average, highlighting the importance of disclosure.
Method reduces complexity of spatial interaction networks.
problem Complex spatial interaction networks.
method Empirical Bayes approach with tree partitioning and generalized double Pareto prior.
result Compact vectorial representations and interpretable visualizations.
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…
Study on consensus formation in manifolds with curvature constraints.
problem Long-time behavior of solutions to nonlocal PDEs on Riemannian manifolds.
method Analytical and numerical methods applied to self-collective models.
result Sufficient conditions for consensus formation and convergence rates quantified.
Effects of Economic Interactions on Credit Riskphysics.soc-ph
We study a credit risk model which captures effects of economic interactions on a firm's default probability. Economic interactions are represented as a functionally defined graph, and the existence of both cooperative, and competitive, business relations is taken into account. We provide an analytic solution of the mo…
Dropout regularizes against high-order interactions by canceling interaction rates.
problem Overfitting to high-order interactions in neural networks.
method Analyzes Dropout through the lens of interaction effects, showing how it effectively cancels out the probability of surviving interactions of different orders.
result Dropout regularizes against high-order interactions by effectively canceling out the probability of surviving interactions of different orders.
Following the statistical mechanics methodology, firstly introduced in macroeconomics by Aoki [1996,2002], we provide some insights to the well known works of Greenwald and Stiglitz [1990, 1993]. Specifically, we reach analytically a closed form solution of their models overcoming the aggregation problem. The key idea …
We develop a general framework, based on Boltzmann transport theory, to analyze the distribution of wealth in societies. Within this framework we derive the distribution function of wealth by using a two-party trading model for the poor people while for the rich people a new model is proposed where interaction with wea…
VINE visualizes statistical interactions in complex models.
problem Lack of utilities for regional explanations in black box models.
method VINE algorithm to extract and visualize statistical interaction effects.
result VINE provides a novel evaluation metric for visualizations.
Requirements elicitation can be very challenging in projects that require deep domain knowledge about the system at hand. As analysts have the full control over the elicitation process, their lack of knowledge about the system under study inhibits them from asking related questions and reduces the accuracy of requireme…
Explosive neural networks via higher-order interactions in curved statistical manifoldscond-mat.dis-nn
New neural networks model complex phenomena with fewer parameters.
problem Challenges in studying higher-order interactions in neural networks.
method Introducing curved neural networks using the maximum entropy principle.
result Curved neural networks accelerate memory retrieval and exhibit explosive phase transitions.
Estimates interaction laws from agent trajectories without assuming their form.
problem Inferring interaction laws from observational data in complex systems.
method Non-parametric statistical learning approach from trajectory data.
result Effectiveness demonstrated in various disciplines, including physics, opinion dynamics, and biology.
We propose a class of Markovian agent based models for the time evolution of a share price in an interactive market. The models rely on a microscopic description of a market of buyers and sellers who change their opinion about the stock value in a stochastic way. The actual price is determined in realistic way by match…
regvis.net offers a visual survey of regulatory visualization.
problem Lack of a comprehensive resource for regulatory visualization.
method Collection and manual tagging of 80+ publications, creation of a searchable webpage.
result First publication set tailored for regulatory visualization.
Paper improves neural interaction modeling using nonlinear Hawkes processes.
problem Inability of classic Hawkes process to model inhibitory interactions.
method Augmented auxiliary latent variables and EM algorithm for efficient inference.
result Demonstrates accurate and efficient estimation of neural interaction dynamics.
Many iterative and non-iterative methods have been developed for inverse problems associated with Ising models. Aiming to derive an accurate non-iterative method for the inverse problems, we employ the tree-reweighted approximation. Using the tree-reweighted approximation, we can optimize the rigorous lower bound of th…
Spatial interactions in agent-based modelingphysics.soc-ph
Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or…
Concepts of polymer statistical topologycond-mat.stat-mech
I review few conceptual steps in analytic description of topological interactions, which constitute the basis of a new interdisciplinary branch in mathematical physics, "Statistical Topology", emerged at the edge of topology and statistical physics of fluctuating non-phantom rope-like objects. This new branch is called…
We introduce a stochastic heterogeneous interacting-agent model for the short-time non-equilibrium evolution of excess demand and price in a stylized asset market. We consider a combination of social interaction within peer groups and individually heterogeneous fundamentalist trading decisions which take into account t…
ivhd tool efficiently visualizes large high-dimensional data.
problem Interactive visualization of large high-dimensional datasets.
method Minimal memory and computational time requirements for nearest neighbor visualization.
result Significantly reduces computational and memory loads.
Software helps teach latent variable methods in multivariate data analytics.
problem Challenges in understanding multivariate data analytics for students.
method Interactive software for comparing latent variable methods.
result Builds intuition on choosing methods and interpreting coefficients.
New method quantifies feature interactions in machine learning models.
problem Capturing high-order interactions and feature contributions in predictive models.
method Information-theoretic approach using Conditional Mutual Information (CMI) via k-NN.
result Accurately recovers feature interactions in synthetic and real-world datasets.
Machine learning and geostatistics are powerful mathematical frameworks for modeling spatial data. Both approaches, however, suffer from poor scaling of the required computational resources for large data applications. We present the Stochastic Local Interaction (SLI) model, which employs a local representation to impr…
Unbiased wealth exchanges always lead to inequality.
problem Understanding wealth distribution in unbiased binary exchange systems.
method Analytical demonstration of unbiased binary exchanges leading to perfect inequality.
result Any system driven by unbiased binary exchanges will reach perfect inequality and zero mobility.
GraphAIR improves graph representation learning by capturing non-linear interactions.
problem Challenges in capturing non-linear interactions in graph data.
method Integrates neighborhood aggregation and interaction modeling.
result Demonstrates improved performance on node classification and link prediction tasks.
STRIDE improves explainable AI by efficiently decomposing feature interactions without subset enumeration.
problem Lack of expressive power and high computational cost in existing XAI frameworks.
method STRIDE uses a functional decomposition approach in RKHS, avoiding subset enumeration and focusing on orthogonal components.
result STRIDE achieves a 3.0 times speedup over TreeSHAP and a high R^2 of 0.93 for feature reconstruction.
MFNs parameterize non-local interactions through matrix equivariant functions, improving graph neural network performance.
problem Challenges in modeling non-local interactions in graphs, such as oversmoothing and oversquashing.
method Matrix Function Neural Networks (MFNs) using resolvent expansions for non-local interactions.
result Achieves state-of-the-art performance in graph benchmarks and captures intricate non-local interactions.
Study of interactions between functions on manifolds via submersions.
problem Understanding interactions between convex, subharmonic, and pluri-subharmonic functions on manifolds.
method Application of pluri-potential theory and analysis of Kähler and G2 manifolds.
result Previous results on Lagrangian fibrations can be viewed as applications of this framework.
The Interactive Minority Game: Instructions for Expertscond-mat.dis-nn
The Interactive Minority Game (IMG) is an online version of the traditional Minority Game in which human players can enter into competition with the traditional computer-controlled agents. Through the rich (and, importantly, analytically understood) behaviour of the MG, we can explore humans' behaviour in different kin…
Approximate 3D elastic curves with exact constraints
problem Designing and approximating 3D elastic curves
method Numerically stable method for recovering 11 parameters
result Fast and stable approximation of arbitrary curves
Neural-ANOVA breaks down neural networks into simpler models.
problem Understanding complex neural network decision-making processes.
method Formulates a learning problem to decompose neural networks into lower-order models using ANOVA.
result Demonstrates improved approximation properties compared to other regression methods.
New method bypasses assumptions for unbiased estimation of complex system interactions.
problem Inferring pair-wise and higher-order interactions from observational data.
method Cross-disciplinary approach using Targeted Learning for unbiased estimation.
result Universal estimator of all-order symmetric interactions without parametric assumptions.
Study shows how cryptocurrency market skewness and kurtosis interact during pandemic.
problem Understanding the dynamics of cryptocurrency markets during the pandemic.
method Examined skewness and kurtosis interactions in cryptocurrency market data.
result More observations cluster around extremes during pandemic, indicating volatile behavior.
A simple banking network model is proposed which features multiple waves of bank defaults and is analytically solvable in the limiting case of an infinitely large homogeneous network. The model is a collection of nodes representing individual banks; associated with each node is a balance sheet consisting of assets and …
This paper presents an analytical treatment of economic systems with an arbitrary number of agents that keeps track of the systems' interactions and agents' complexity. This formalism does not seek to aggregate agents. It rather replaces the standard optimization approach by a probabilistic description of both the enti…
Improved estimation of interaction effects in regression models.
problem Estimation of interaction effects in high-dimensional regression models.
method Developed a local shrinkage model linking main effects and interactions.
result Strong improvement in estimation of regression coefficients.
New methods for estimating gradients of expectations using pairwise interactions.
problem Estimating gradients of expectations for complex models.
method Introducing new pairwise stochastic gradient estimators based on the log-derivative trick and reparameterisation.
result New estimators are unbiased and offer variance reduction compared to the log-derivative estimator.
CatGCN improves GCNs by modeling feature interactions for categorical node features.
problem Suboptimal initial node representations in GCNs due to lack of feature interaction modeling.
method Integrates explicit interaction modeling (local and global) into initial node representation learning for categorical node features.
result CatGCN enhances initial node representations through feature interaction modeling, leading to improved model performance.
Three problems in Hermitian geometry for canonical metrics.
problem Identifying and constructing canonical metrics in Hermitian geometry.
method Analytic methods, momentum map, variational methods.
result Different techniques naturally interact in solving these problems.
Optimizes social interactions for profit, people, and planet using mathematical models.
problem Determining the most effective social configurations for mutual objectives.
method Formulated as a mathematical optimization problem, using (meta)relational models theory.
result Identifies the most suitable combination of sociality forms for mutual objectives.