Study on online CF with occasional positive ratings, finds p_f impacts sample complexity.
problem Online CF with limited positive feedback.
method Probabilistic user model, online user-based CF algorithm analysis.
result Sample complexity reduced by 1/p_f for initial exploration.
Proposes tau-FPL for efficient false-positive rate control in linear time.
problem Learning classifiers with strict false-positive rate constraints.
method Scoring-thresholding approach with linear time efficiency.
result Superior performance over existing approaches in false-positive rate control.
Two kernel Stein tests control decision errors in non-parametric model comparison.
problem Non-parametric multiple model comparison.
method Two statistical tests controlling false positive and false discovery rates.
result The first test has a higher true positive rate than the second under appropriate conditions.
Alternative method preserves positivity in interest rate interpolation.
problem Positivity issue in interest rate interpolation.
method Alternative method preserving Markovian properties and positivity.
result Guaranteed positivity of all interpolated rates.
Maximum principle proves positivity of forward rates in stochastic models.
problem Proving positivity of forward rates in stochastic models.
method Maximum principle for mild solutions to SPDEs with Lipschitz coefficients and Wiener noise.
result Sufficient conditions for positivity of forward rates in the Heath-Jarrow-Morton model.
The paper ensures positivity of solutions to stochastic equations with positive initial data.
problem Ensuring positivity of solutions to stochastic equations with positive initial data.
method Providing sufficient conditions on coefficients for positivity of mild solutions.
result Sufficient conditions for positivity of solutions to stochastic equations.
SVAR-LiNGAM reveals causal order in crypto-asset markets.
problem Understanding the causal relationships between spot rates and crypto-assets.
method Applied SVAR-LiNGAM to analyze spot exchange rates and crypto-asset exchange rates.
result Causal order found: EUR_USD spot rate -> Bitcoin -> Ethereum -> Ripple.
Paper identifies resting positions using EGG, ECG, respiration rate, and SpO2.
problem Identifying the resting position for health monitoring.
method Hybrid stacked ensemble machine learning model combining Decision tree, Random Forest, and Xgboost.
result 100% accurate prediction of resting positions.
Exponential rate of convergence for harmonic heat flow maps.
problem Analyzing the convergence rate of harmonic heat flow maps.
method Proving exponential convergence rate for harmonic heat flow maps.
result Exponential convergence rate of the harmonic heat flow.
Polynomial models ensure positive rates for life insurance pricing.
problem Pricing and hedging life insurance products under a benchmark model.
method Modeling a state variable with a polynomial diffusion on a compact space.
result Explicit formulas for pricing and hedging are possible.
Study controls error rates of binary classifiers using hypothesis testing.
problem Traditional binary classifiers have uncontrolled error rates.
method Combines binary classification with statistical hypothesis testing.
result Trained classifiers can be made to meet target error rate thresholds.
The Dirichlet random walk on manifolds has a positive escape rate if the cover is non-amenable.
problem Analyzing the stochastic behavior of Dirichlet random walks on manifolds.
method Defining a recursive process on Galoisian covers and proving a theorem about the escape rate.
result The escape rate is positive if and only if the cover is non-amenable.
For environmental problems such as global warming future costs must be balanced against present costs. This is traditionally done using an exponential function with a constant discount rate, which reduces the present value of future costs. The result is highly sensitive to the choice of discount rate and has generated …
The study shows interest rates impact investment and funding negatively but positively on dividend decisions.
problem The effect of interest rates on financial decisions like investment, funding, and dividend.
method Correlation coefficient analysis and descriptive methods.
result Interest rates have a negatively insignificant effect on investment and funding decisions, but positively moderate effect on dividend decisions.
The geometric Lévy model (GLM) is a natural generalisation of the geometric Brownian motion model (GBM) used in the derivation of the Black-Scholes formula. The theory of such models simplifies considerably if one takes a pricing kernel approach. In one dimension, once the underlying Lévy process has been specified, th…
New method improves false-/true-positive-rate estimation in fraud detection with noisy labels.
problem Estimating FPR/TPR in fraud detection with class-conditional label noise.
method Directly cleaning model's validation data to de-correlate cleaning error with model scores.
result Improves accuracy of FPR/TPR estimates, especially in asymmetric label noise scenarios.
AdaDetectGPT improves text authorship detection with statistical guarantees.
problem Determining if text is authored by a human or an LLM.
method Adaptive learning of a witness function from training data to enhance logits-based detectors.
result AdaDetectGPT nearly uniformly improves text authorship detection, with up to 37% improvement.
We introduce a multiple curve framework that combines tractable dynamics and semi-analytic pricing formulas with positive interest rates and basis spreads. Negatives rates and positive spreads can also be accommodated in this framework. The dynamics of OIS and LIBOR rates are specified following the methodology of the …
New method calibrates false detection rates in sequential change detection.
problem Challenges in setting time-invariant thresholds for false positives.
method Simulation-based approach to time-varying thresholds.
result Accurately targets desired expected runtime while keeping false positive rate constant.
Method to decompose portfolio performance into FX, interest rate, carry, and residual market risks.
problem Understanding the sources of portfolio performance.
method Decomposition of portfolio PnL into four components.
result Demonstrated usefulness of the method through fund performance analysis.
Study finds polynomial convergence rate for Farey sequences linked to Riemann hypothesis.
problem Understanding convergence rates of maximum mean discrepancies for Farey sequences.
method Identifying positive-semidefinite kernels and their polynomial convergence rates.
result Polynomial convergence rate of maximum mean discrepancies of Farey sequences is equivalent to the Riemann hypothesis.
SFS-DA method statistically tests FS reliability under domain adaptation.
problem Feature selection reliability under domain adaptation with limited target data.
method Selective Inference framework to control false positive rate and enhance true positive rate.
result SFS-DA method controls FPR below a pre-specified level α (e.g., 0.05) while maximizing true positive rate. New neural network outperforms existing methods in scene matching.
problem Automated scene matching with high accuracy and low false positives.
method Convolutional hashing using a new loss function and training scheme.
result Significantly higher true positive rate and 100-fold reduction in false positives.
Study on optimal capital injection for insurance companies under negative interest rates.
problem Optimal capital injection behavior of insurance companies under negative interest rates.
method Modelled the surplus process as a Brownian motion with drift and interest rate changes as a Markov-switching process. Established an algorithm for finding the value function and optimal strategy.
result Optimal strategy involves holding a positive reserve when interest rate is negative, unlike when positive.
We construct a no-arbitrage model of bond prices where the long bond is used as a numeraire. We develop bond prices and their dynamics without developing any model for the spot rate or forward rates. The model is arbitrage free and all nominal interest rates remain positive in the model. We give examples where our mode…
Enhanced attacks quantify machine learning data leakage.
problem Quantifying how much machine learning models reveal about their training data.
method Hypothesis testing framework for membership inference attacks.
result New attacks achieve higher true positive rates with lower false positive rates.
We consider a short rate model, driven by a stochastic process on the cone of positive semidefinite matrices. We derive sufficient conditions ensuring that the model replicates normal, inverse or humped yield curves.
Approximations to utility indifference prices are provided for a contingent claim in the large position size limit. Results are valid for general utility functions on the real line and semi-martingale models. It is shown that as the position size approaches infinity, the utility function's decay rate for large negative…
This paper, focusing on the growth rate of the measure, gives pointwise bounds of solutions of eigenvalue equations of the Laplace-Beltrami operator on noncompact Riemannian manifolds.
Paper estimates FPR of Bayes classifier using soft labels.
problem Determining optimal classifier performance.
method Uses soft labels and denoising technique.
result Consistent and unbiased FPR estimator developed.
We discuss a simple extension of the Ho and Lee model with generic time-dependent drift in which: 1) we compute bond prices analytically; 2) the yield curve is sensible and the asymptotic yield is positive; and 3) our analytical solution provides a clean and simple way of separating volatility from the drift in the sho…
Study finds relevance of exchange and inflation rates to economic factors.
problem Determining the relevance of exchange and inflation rates to economic factors.
method Introduced concept of adequacy, established positive relation between exchange and inflation rates and other economic factors.
result Close positive relation found between exchange and inflation rates and other economic factors.
The study classifies term structure shapes in the two-factor Vasicek model using total positivity.
problem Classifying all possible term structure shapes in the two-factor Vasicek model of interest rates.
method Total positivity theory pioneered by Samuel Karlin.
result Four additional shapes can be produced in certain parameter regimes.
Deep transfer learning improves malware classification speed and accuracy.
problem Static malware classification accuracy and speed.
method Transfer learning from computer vision to static malware detection.
result Our method outperforms classical machine learning methods in accuracy, false positive rate, true positive rate, and F1 score.
Study harmonic function growth on curved spaces, proving inequalities.
problem Understanding growth rates of harmonic functions on curved manifolds.
method Applied a double-sided Price inequality to estimate growth rates.
result Effective estimates for harmonic function growth rates on curved manifolds.
The study examines exceptional sets for radial limits of superharmonic functions on curved manifolds.
problem Understanding exceptional sets for radial limits of superharmonic functions on curved manifolds.
method Analysis of radial geodesic rays, Poisson integrals, Green potentials, and Riesz decomposition.
result Sharp bounds on Hausdorff dimensions of exceptional sets for superharmonic functions.
Study on implied certainty equivalent rates in financial markets and electric vehicles.
problem Investment risk in financial markets.
method Mathematical derivation of implied certainty equivalent rate, empirical analysis of stock and option data.
result Positive implied certainty equivalent rates are more suitable for investment than negative ones, but higher values increase risk.
Study combines expert advice to avoid discrimination without violating equalized error rates.
problem Combining expert advice to avoid discrimination without violating equalized error rates.
method Running separate instances of the classical multiplicative weights algorithm for each group.
result Even for equalized error rates, algorithms with stronger performance guarantees than multiplicative weights cannot preserve non-discrimination.
Paper analyzes privacy risks of learning complex models.
problem Privacy leakage from learning high-dimensional graphical models.
method Theoretical analysis of tracing attacks on Bayesian networks.
result Provides a tight upper bound on tracing attack power.
Positive simplicial volume implies virtually positive Seifert volume for 3-manifolds.
problem Understanding the relationship between simplicial and Seifert volumes in 3-manifolds.
method Utilizing recent results on virtual domination and virtual representation volumes of 3-manifolds.
result Closed orientable 3-manifolds with positive simplicial volume have virtually positive Seifert volume.
New optimization method improves AUC for binary classification and changepoint detection.
problem Non-convex AUC and sub-optimal points in ROC curves.
method AUM (Area Under Min(FP, FN)) surrogate loss function based on sorting and summing ROC curve points.
result AUM minimization learning algorithm improves AUC and speeds up compared to previous methods.
Algorithm ensures fairness in online classification with partial feedback.
problem Fairness in online classification with partial feedback.
method Oracle efficient algorithm that satisfies fairness constraints.
result Upper and lower bounds on the cost of fairness constraints.
This research examines anomaly detection metrics under class imbalance.
problem Challenges in interpreting evaluation metrics under class imbalance.
method Analysis of four common anomaly detection metrics (AUROC, AUPR, F1-score, MCC) under varying imbalance ratios.
result Visualisations of metric landscapes provide an intuitive view of metric preferences and stability.
GraphPrints detects anomalies in network flow data by analyzing graphlets.
problem Detecting anomalies in network flow data.
method Representing network flow as graphs, counting graphlets, and detecting outliers.
result Initial testing shows low false positive rates and high true positive rates.
New method reduces unfairness in binary classification.
problem Achieving similar false positive and negative rates across two populations.
method Penalizes unfairness to achieve balanced false positive and negative rates.
result Empirically validated approach improves fairness and accuracy.
Diffusion in a linear potential in the presence of position-dependent killing is used to mimic a default process. Different assumptions regarding transport coefficients, initial conditions, and elasticity of the killing measure lead to diverse models of bankruptcy. One "stylized fact" is fundamental for our considerati…
The study analyzes historical interest rates to predict future discount rates and their implications on climate change.
problem Predicting future discount rates to inform climate change mitigation policies.
method Constructed real interest rates using historical data and a stochastic model (Ornstein-Uhlenbeck).
result Only 4 out of 14 countries have positive long-run discount rates, suggesting urgent action on climate change.
ODIN improves out-of-distribution image detection without altering pre-trained neural networks.
problem Detecting out-of-distribution images in neural networks.
method Temperature scaling and small input perturbations.
result ODIN reduces false positive rate from 34.7% to 4.3% on DenseNet (CIFAR-10) while maintaining high true positive rate.