A new framework for adaptive behavior using reusable value profiles.
problem Adaptive behavior in changing environments requires switching among value-control regimes, but maintaining separate parameters for each situation is impractical.
method Introduces value profiles: reusable bundles of parameters assigned to hidden states, allowing for state-conditional strategy recruitment without independent parameters for each context.
result Profile-based models outperform simpler alternatives in probabilistic reversal learning, suggesting belief-dependent control of adaptive behavior.
The paper proposes a method to estimate individual behavioral profiles using smart meter data.
problem Estimating individual behavioral profiles with granular temporal data.
method Gaussian Process-based models for segmenting and clustering time series data.
result The method can predict individual behavioral patterns with high accuracy.
Generative profiling improves real-time task timing for varied resource contexts.
problem Inaccurate task timing analysis for complex hardware architectures.
method Nonparametric, conditional multi-marginal Schrödinger Bridge (MSB) formulation for synthesizing context-dependent timing profiles.
result Maximum likelihood accurate execution profiles for unseen resource contexts.
The study characterizes convex bodies with equal isoperimetric profiles to half-spaces and estimates their volume behavior.
problem Characterizing convex bodies with equal isoperimetric profiles to half-spaces.
method Using a new concept of asymptotic dimension, the study characterizes convex bodies and estimates their volume behavior.
result For large volumes, the isoperimetric profile of convex bodies is asymptotic to that of RN. Order submission and cancellation are two constituent actions of stock trading behaviors in order-driven markets. Order submission dynamics has been extensively studied for different markets, while order cancellation dynamics is less understood. There are two positions associated with a cancellation, that is, the price…
This paper reviews statistical and machine learning methods for anti-money laundering.
problem Lack of scientific literature on statistical and machine learning methods for anti-money laundering.
method Client risk profiling and suspicious behavior flagging.
result Client risk profiling involves diagnostics, while suspicious behavior flagging involves non-disclosed features and hand-crafted risk indices.
Kahler-Ricci flow long-time behavior and initial data
problem Relationship between Kahler-Ricci flow and initial data
method Investigate long-time behavior
result Asymptotic profiles and non-trivial breathers
Paper describes profiles of multivariate normal distributions and novel estimators for mutual information.
problem Estimating mutual information for complex distributions.
method Analytical description of profiles, introduction of Bend and Mix Models, Monte Carlo estimation.
result Bend and Mix Models accurately estimate mutual information profiles and provide Bayesian estimates.
New measure quantifies financial erratic behavior.
problem Measuring similarity between erratic financial time series.
method Combining probability distributions and Bayesian change point detection.
result Greater similarity among sectors than countries in erratic behavior.
In this paper we consider the problem of minimizing the relative perimeter under a volume constraint in the interior of a convex body, i.e., a compact convex set in Euclidean space with interior points. We shall not impose any regularity assumption on the boundary of the convex set. Amongst other results, we shall prov…
This work addresses the {\em singularity formation} of complete non-compact solutions to the conformally flat Yamabe flow whose conformal factors have {\em cylindrical behavior at infinity}. Their singularity profiles happen to be {\em Yamabe solitons}, which are {\em self-similar solutions} to the fast diffusion equat…
Study on how technical analysis affects wealth distribution in agent-based model of investors.
problem Understanding wealth distribution and return rates in financial markets.
method Agent-based model with psychological profiles and decision-making strategies.
result Anti-imitation strategy becomes most profitable when applied to investors' hub.
Stable blowup profile identified for wave maps in all dimensions.
problem Stability of blowup solutions for wave maps in supercritical energy.
method Novel stability analysis using similarity variables on the whole space.
result Global nonlinear stability of the corotational self-similar blowup profile.
A new method detects fraud transactions by analyzing user behavior over time.
problem Detecting fraud transactions in online payment platforms.
method A time attention based recurrent layer framework combining static and dynamic user behaviors.
result Our method outperforms state-of-the-art methods, especially in recall at top percent.
This paper poses a few fundamental questions regarding the attributes of the volume profile of a Limit Order Books stochastic structure by taking into consideration aspects of intraday and interday statistical features, the impact of different exchange features and the impact of market participants in different asset s…
apk2vec builds profiles of Android apps using multiple views, outperforming existing methods.
problem Building comprehensive behavior profiles of Android apps for better analytics.
method Semi-supervised multi-view representation learning combining RL and feature hashing.
result apk2vec's profiles significantly outperform state-of-the-art techniques in app analytics tasks.
The paper analyzes ridge regression with random features for non-identically distributed data.
problem Analyzing ridge regression performance for data with heterogeneous variance profiles.
method Combining linear-plus-chaos approximation and operator-valued free probability.
result Derives asymptotic equivalents for training and test risks under non-identically distributed data.
Study examines how balancing methods affect model behavior in imbalanced classification problems.
problem Impact of balancing methods on model behavior in imbalanced classification problems.
method Used Explainable Artificial Intelligence tools (variable importance method, partial dependence profile, accumulated local effects) to compare model behavior before and after balancing.
result Significant changes in model behavior due to balancing methods, leading to biased models.
Paper models MOOC users behavior using MDP for easier classification.
problem Difficulty in defining and classifying MOOC users based on their behavior.
method Uses Markov Decision Process (MDP) to model user behavior from log data.
result Classifies users based on their intentions inferred from MDP rewards.
We investigate the trading behavior of Finnish individual investors trading the stocks selected to compute the OMXH25 index in 2003 by tracking the individual daily investment decisions. We verify that the set of investors is a highly heterogeneous system under many aspects. We introduce a correlation based method that…
Study on minimizing perimeter in unbounded convex bodies without boundary regularity.
problem Minimizing perimeter under volume constraint in unbounded convex bodies.
method Introducing uniform geometry, asymptotic cylinders, approximation, and approximation argument.
result Existence of isoperimetric regions in generalized sense and strict concavity of isoperimetric profile.
Robo-advisor improves investment advice through client interaction.
problem Offering personalized financial advice to clients.
method Adaptive mean-variance portfolio optimization with client interaction.
result Optimal investment strategy includes both myopic and intertemporal hedging terms.
New statistic κ-profile helps monitor weather, soundscapes, and dynamical systems.
problem Monitoring intrinsic dimensionality of large data sets.
method Optimization problem to find κ-profile, which is the norm of the shortest projected secant. result The κ-profile provides a useful statistic for understanding and monitoring large data sets. Expanding on techniques of concentration of measure, we develop a quantitative framework for modeling liquidity risk using convex risk measures. The fundamental objects of study are curves of the form (ρ(λX))λ≥0, where ρ is a convex risk measure and X a random variable, and we call such a curve a \emph{liqu…
This paper optimizes cybersecurity resource allocation in networks with heterogeneous attacker and defender valuations.
problem Optimizing cybersecurity resource allocation in networks with heterogeneous attacker and defender valuations.
method Combining strategic behavior of players with contagion dynamics, a method is extended to determine optimal resource allocation based on simple network metrics weighted by risk profiles.
result The asymmetry between attacker and defender valuations drives optimal attack and defense strategies, shaping system resilience.
Paper uses CVAE to simulate tariff impacts on electricity consumption.
problem Simulating tariff impacts on household electricity consumption.
method CVAE-based clustering and generation of consumption profiles.
result CVAE method can reproduce rebound and side effects in consumption profiles.
Data-driven method clusters and analyzes heat load patterns in district heating networks.
problem Lack of knowledge about customers' heat load behaviors in district heating networks.
method Data-driven approach that clusters customer profiles and detects unusual patterns.
result High potential for deploying the method to analyze customers' heat-use habits in practice.
We give a stochastic microscopic modelling of stock markets driven by continuous double auction. If we take into account the mimetic behavior of traders, when they place limit order, our virtual markets shows the power-law tail of the distribution of returns with the exponent outside the Levy stable region, the short m…
Study analyzes player churn and purchasing behavior in games.
problem Retaining players and predicting churn in video games.
method Deep behavioral analysis and ensemble learning models.
result Discarding certain churners improves prediction models.
Paper examines vulnerabilities in data-driven pricing schemes.
problem Vulnerability of clustering-oriented pricing schemes to malicious user behavior.
method Defined a notion of disguising to identify strategic behaviors of malicious users, characterized sensitivity zones to evaluate malicious user percentages, conducted cost benefit analysis.
result Concluded with a vulnerability analysis of data-driven pricing schemes.
SYNTHONY selects tabular synthesizers based on stress profiling and user intent.
problem Non-uniform performance of tabular generative models across datasets.
method Stress profiling and intent-conditioned tabular synthesis selection.
result Meta-features predict synthesizer performance, improving selection accuracy.
In this paper we consider the problem of minimizing the relative perimeter under a volume constraint in the interior of a conically bounded convex set, i.e., an unbounded convex body admitting an \emph{exterior} asymptotic cone. Results concerning existence of isoperimetric regions, the behavior of the isoperimetric pr…
Social, technological and economic time series are divided by events which are usually assumed to be random albeit with some hierarchical structure. It is well known that the interevent statistics observed in these contexts differs from the Poissonian profile by being long-tailed distributed with resting and active per…
Study uses FDA to analyze discount functions of different temperaments.
problem Traditional finance models fail to capture individual differences in investment choices.
method Functional Data Analysis (FDA) to investigate temporal discounting behaviors.
result Heterogeneity within each temperament revealed, suggesting diverse investor profiles.
This paper uses Tsallis relative entropy to optimize stock portfolios, showing better consistency in risk-return profiles.
problem Optimizing stock portfolios with consistent risk-return profiles.
method Constructing portfolios by binning risk values and allocating stocks based on risk values, comparing with four risk measures.
result Tsallis relative entropy yields more consistent risk-excess return profiles compared to other measures.
Study reveals LLM personality patterns but lacks behavioral consistency.
problem Understanding and validating personality traits in LLMs.
method Characterized LLM personality across three dimensions: training dynamics, self-report validity, and intervention effects.
result Self-reported traits do not reliably predict behavior, and instructional alignment affects trait expression but not behavior.
Classifies Tinder dating profiles using facial embeddings.
problem Automatically review and classify online dating profiles.
method Uses FaceNet facial embeddings to extract features and train logistic regression models.
result Simple logistic regression on 20 profiles achieved 65% validation accuracy.
We develop a dynamic point process model of correlated default timing in a portfolio of firms, and analyze typical default profiles in the limit as the size of the pool grows. In our model, a firm defaults at a stochastic intensity that is influenced by an idiosyncratic risk process, a systematic risk process common to…
Paper warns against assuming all unreported compound-target binding profiles are negative.
problem Assumption of all unreported compound-target binding profiles being negative is unreliable.
method Proposes a framework to jointly recover unreported profiles and learn predictive models.
result Explicit recovery of unreported profiles improves prediction performance.
We consider the initial value problem ut=Δlogu, u(x,0)=u0(x)≥0 in R2, corresponding to the Ricci flow, namely conformal evolution of the metric u(dx12+dx22) by Ricci curvature. It is well known that the maximal (complete) solution u vanishes identically after time $T= \frac 1{4π} \int_{\R^…
The paper introduces Poincaré profiles for metric spaces and groups, linking them to conformal dimension.
problem Understanding the properties of metric measure spaces and groups with polynomial growth.
method Introducing and analyzing Poincaré profiles for groups and hyperbolic spaces.
result Connection between Poincaré profiles and conformal dimension, leading to non-existence of coarse embeddings.
Profile entropy measures learnability and compressibility of discrete distributions.
problem Understanding the learnability and compressibility of discrete distributions.
method Investigates profile entropy, showing its role in estimation, inference, and compression.
result Profile entropy is a fundamental measure unifying estimation, inference, and compression.
Models analyze how different levels of tax evasion affect income distribution.
problem Effects of varying levels of tax evasion on income distribution.
method Microscopic models of economic interactions with a tax system and redistribution.
result Gini inequality index increases with higher evasion levels, but evasion spread does not significantly affect it.
A method to describe Riemann surfaces using graph profiles is proposed.
problem Describing Riemann surfaces in a graph-theoretic framework.
method Graph profiles to represent Riemann surfaces, establishing necessary and sufficient conditions for their existence.
result A criterion for the existence of Riemann surfaces with a given signature.
The study creates user personas based on user tenure and behavior for VoD streaming.
problem Understanding evolving user behavior in streaming services without explicit user profiles.
method Construct user personas using tenure timelines and temporal behavioral features.
result Personas provide stable and interpretable insights into user behavior evolution.
Method controls extrapolation in prediction profiles for statistical and machine learning models.
problem Avoiding invalid predictions due to extrapolation in prediction profiles.
method Genetic algorithm optimization over constrained factor regions.
result Optimal factor settings without constraint are often invalid and extrapolated.
Study identifies subphenotypes of pediatric sepsis to improve ML predictive performance.
problem Enhance machine learning predictive performance in pediatric sepsis.
method Latent profile analysis of clinical data to identify subphenotypes, followed by ML experiments.
result Improved predictive performance of ML models targeting specific subphenotypes of pediatric sepsis.
Sharp decay estimates for critical Dirac equations on \(\mathbb{R}^n\).
problem Analyzing decay behavior of critical Dirac equations.
method Proving sharp pointwise decay estimates.
result Explicit asymptotic behavior of excited states in honeycomb structures.