An explicit solution found for maximizing/minimizing agreement in a 2x2 table.
problem Maximizing or minimizing agreement between clusterings with given marginals.
method Formal framework for several agreement measures, explicit solution for 2x2 table.
result An explicit solution for the 2x2 case.
New test identifies dependency in multivariate data without resampling.
problem Identifying dependency in large multivariate datasets.
method Sequential coarse-to-fine discretization and 2x2 contingency tables.
result Strong control of family-wise error rate without resampling.
Improved method for encoding contingency tables reduces mutual information bias.
problem Mutual information bias in measuring label similarity.
method Improved method for encoding contingency tables to reduce information cost.
result Better bound on reduced mutual information in typical use cases.
Taxicab correspondence analysis visualizes sparse text data sets.
problem Visualization of extremely sparse contingency tables.
method Robust variant of correspondence analysis for sparse data.
result Visualized an 8265-dimensional textual data set.
The study refines contingency matrices for complex stratification and braid group cohomology.
problem Combinatorics of contingency matrices and their applications.
method Refinement of complex stratification and study of braid group cohomology.
result Totally positive meta-matrix formed by contingency matrix sizes.
The study models insurance dependence using Bernstein copulas.
problem Modeling dependence structures in nonlife insurance data.
method Review and suggest fitting Bernstein copulas to empirical data.
result Monte Carlo simulation and PML estimation for aggregate losses.
Solves a 60-year-old question on agreement measures in statistics.
problem The challenge of measuring agreement between two raters or measures.
method Developed a new algorithm to minimize diagonals in contingency tables, formulated the minimum feasible agreement, and studied the lower limit of maximum feasible agreement.
result Formulated the lower limit of Cohen's kappa and two statistics for agreement analysis.
New algorithms for private data synthesis using heuristics.
problem Private data synthesis for complex functions.
method Developed algorithms using non-private oracles and certifiable heuristics.
result Efficient private data synthesis for broad classes of functions.
We present a 2x2 Lax representation for discrete circular nets of constant negative Gauß curvature. It is tightly linked to the 4D consistency of the Lax representation of discrete K-nets (in asymptotic line parametrization). The description gives rise to Bäcklund transformations and an associated family. All the membe…
We propose a categorical data synthesizer with a quantifiable disclosure risk. Our algorithm, named Perturbed Gibbs Sampler, can handle high-dimensional categorical data that are often intractable to represent as contingency tables. The algorithm extends a multiple imputation strategy for fully synthetic data by utiliz…
Extends co-clustering to mixed numerical and binary data.
problem Co-clustering of mixed data types (numerical and binary).
method Latent block models for mixed data types.
result Effectiveness of the proposed approach on simulated data.
Assessing the performance of a learned model is a crucial part of machine learning. However, in some domains only positive and unlabeled examples are available, which prohibits the use of most standard evaluation metrics. We propose an approach to estimate any metric based on contingency tables, including ROC and PR cu…
In this paper, we explore and detail our experiments in a high-dimensionality, multi-class image classification problem often found in the automatic recognition of Sign Languages. Here, our efforts are directed towards comparing the characteristics, advantages and drawbacks of creating and training Support Vector Machi…
Improved neural network model for predicting latent budgets in compositional data.
problem Predicting response variables in compositional data with non-negativity constraints.
method LBA-NN, a feed forward neural network model that incorporates K-means clustering for interpretation.
result LBA-NN outperforms traditional LBA in prediction accuracy, specificity, recall, and mean square error.
The paper argues that normalized mutual information is biased in clustering and community detection.
problem Bias in normalized mutual information for clustering and community detection.
method Introducing a modified version of mutual information to correct for information content and spurious dependence.
result The modified mutual information leads to different conclusions about which algorithms are best for community detection.
In this paper we show how generalized quaternions, including 2X2 matrices, can be used to find solutions of a non-commuting equation intimately connected with braid groups. These solutions can then be used to find polynomial invariants of virtual knots and links.
We introduce a new integrable system hierarchy which is a restriction of the AKNS nxn hierarchy coming from an unusual splitting of the loop algebra. This splitting comes from an automorphism of the loop algebra instead of an automorphism of SL(n,C). It is known that the 2x2 KdV is the standard KdV hierarchy.
Revisit Fenn's table theorem from a differential-topological perspective.
problem Prove zero-existence theorem on a cylinder and horizontal square-table theorem under Fenn's boundary conditions.
method Differential-topological approach.
result Prove horizontal square-table theorem under more general boundary conditions.
Using geometrical approach exposed in arXiv:math/0304245 and arXiv:nlin/0511012, we explore the Camassa-Holm equation (both in its initial scalar form, and in the form of 2x2-system). We describe Hamiltonian and symplectic structures, recursion operators and infinite series of symmetries and conservation laws (local an…
Log-linear models are the popular workhorses of analyzing contingency tables. A log-linear parameterization of an interaction model can be more expressive than a direct parameterization based on probabilities, leading to a powerful way of defining restrictions derived from marginal, conditional and context-specific ind…
We propose a new data-augmentation strategy for fully Bayesian inference in models with binomial likelihoods. The approach appeals to a new class of Polya-Gamma distributions, which are constructed in detail. A variety of examples are presented to show the versatility of the method, including logistic regression, negat…
Using the representation of the isometries as 2x2 invertible matrices over the division algebra $\H$ of quaternions, we give an algebraic characterization of the dynamical types of the orientation-preserving isometries of the hyperbolic 5-space. We also determine the conjugacy classes and the conjugacy classes of centr…
Robot learns sensorimotor relationships through exploration.
problem Autonomous acquisition of sensorimotor contingencies by robots.
method Developmental framework encoding predictive models of sensorimotor experience.
result Robot discovers the environment, objects, and visual field through internal encoding of sensorimotor contingencies.
The Kinetic Gas Theory like two-agent money exchange models, recently introduced in the Econophysics of Wealth distributions, are revisited. The emergence of Boltzmann-Gibbs like distribution of individual money to Pareto's law in the tail of the distribution is examined in terms of 2x2 Transition matrix with a general…
Model prices sovereign contingent convertible bonds during crises.
problem Pricing Sovereign Contingent Convertible bonds (S-CoCo) during crises.
method Model CDS spread regime switching as a hidden Markov process, coupled with a mean-reverting stochastic process. Use Longstaff-Schwartz American option pricing framework for simulation.
result Computed future state contingent S-CoCo prices for risk management.
Study detects synthetic tabular data across different tables.
problem Detecting synthetic tabular data in varied tables.
method Four table-agnostic detectors combined with preprocessing schemes.
result Cross-table learning possible with naive preprocessing, but cross-table transfer challenging.
Paper introduces EEMs for pricing contingent claim returns.
problem Computing expected future prices of contingent claims.
method Dynamic change of measure approach to construct EEMs.
result EEMs provide physical and pricing expectations of contingent claim prices.
Contingency Training improves classifier accuracy and robustness against irrelevant variables.
problem Feature selection leaves irrelevant variables in high-dimensional datasets, reducing classifier performance.
method Subsampling and creating constraints to find proper feature importance weights.
result Contingency Training outperforms traditional training methods, especially with irrelevant variables.
Proves a generalized table theorem for odd Euler characteristic surfaces.
problem Proving a generalized table theorem for surfaces with odd Euler characteristic.
method Using the square peg problem for smooth curves, the result is generalized to real valued functions on Riemannian surfaces with odd Euler characteristic.
result Proves the table conjecture for even functions on the two sphere.
Study of SL(2) over octonions using twistor geometry.
problem No invertible 2x2 matrices over octonions, use Spin(9,1) x SL(2,R) orbit.
method Twistor geometry in eight dimensions.
result Interpretation of open orbit in 32D representation space.
CTSyn generates high-quality synthetic tabular data.
problem Challenges in generating high-quality synthetic tabular data.
method Diffusion-based generative foundation model with autoencoder and conditional latent diffusion.
result CTSyn outperforms existing table synthesizers on standard benchmarks.
The paper revisits and applies FTAP to life insurance and annuities pricing.
problem Non-arbitrage pricing of life contingent assets in dynamic markets.
method Revisit FTAP, use martingale theory, apply FTAP to life insurance and annuities, clarify assumptions.
result Valuation formula for life contingent assets including life insurance policies and annuities.
Upper bounds for surface-links in the Yoshikawa table are estimated.
problem Estimating Kirby-Thompson invariants of surface-links.
method Using tri-plane diagrams and L-, L*-invariants.
result Upper bounds for surface-links in the Yoshikawa table are obtained.
Study stability of contingent claim solutions under probabilistic perturbations.
problem Stability of solutions to discrete-time contingent-claim problems under uncertainty.
method Use Rockafellian perturbations to analyze stability of solutions.
result Establishes convergence of dual problems and shadow prices.
Paper proposes a method to estimate project cost contingency reserves considering various types of uncertainty.
problem Inaccurate estimation of project cost contingency reserves due to ignoring different types of uncertainty.
method Quantitative determination of project cost contingency reserves using Monte Carlo Simulation considering aleatoric, stochastic, and epistemic uncertainties.
result The proposed method provides more accurate contingency reserves that align with actual project risks.
One-pass private sketch supports various machine learning tasks.
problem Efficiently supporting multiple machine learning tasks with differential privacy.
method Randomized contingency tables indexed with locality-sensitive hashing, constructed in one pass.
result Competitive error bounds for DP kernel density estimation, faster than existing methods.
This paper compiles and calculates triple point numbers for surface-links in Yoshikawa's table.
problem Determining the triple point number of surface-links in Yoshikawa's table.
method Using broken sheet diagrams, the paper compiles known triple point numbers and calculates or bounds the remaining ones.
result Compilation and calculation of triple point numbers for surface-links in Yoshikawa's table.
The paper proves geometric properties of square tables and saddle surfaces.
problem The mathematical table problem from a geometric-topological perspective.
method Geometric-topological proofs on cylinder, saddle surfaces, and level sets of Fenn graphs.
result Zero-existence theorem on a cylinder, proving Fenn's square-table theorem under different boundary conditions.
Machine learning speeds up search procedures for sorted tables.
problem Improving the speed of sorted table search procedures.
method Systematic experimental comparison of efficient implementations with learned counterparts.
result Learned data structures can significantly speed up search procedures.
Closed-form pricing method for multi-asset options.
problem Pricing multi-asset contingent claims in an incomplete market.
method Proving extremal martingale measures and constructing algorithms for bounds and hedging.
result Closed-form formulas for no-arbitrage price intervals and hedging strategies.
DPpack offers R tools for private data analysis and machine learning.
problem Ensuring privacy in statistical analysis and machine learning.
method Differential privacy mechanisms (Laplace, Gaussian, exponential).
result User-friendly implementation of privacy-preserving models.
We price a contingent claim liability using the utility indifference argument. We consider an agent with exponential utility, who invests in a stock and a money market account with the goal of maximizing the utility of his investment at the final time T in the presence of positive proportional transaction cost in two c…
The paper explores how contingency-awareness improves exploration in reinforcement learning.
problem Improving exploration in reinforcement learning environments with sparse rewards.
method Developed an attentive dynamics model (ADM) to discover controllable elements of observations and used it for state representation in exploration.
result Combining actor-critic algorithms with count-based exploration using the ADM representation achieved impressive results on Atari games.
The paper defines and implements risk-indifference pricing for American-style contingent claims.
problem Pricing American-style contingent claims under uncertainty.
method Indifference pricing using convex risk measures and stochastic volatility models, with numerical solutions via deep learning.
result Characterization of indifference prices via Backward Stochastic Differential Equations (BSDEs).
In this paper, we study the pricing of contingent claims under G-expectation. In order to accomodate volatility uncertainty, the price of the risky security is supposed to governed by a general linear stochastic differential equation (SDE) driven by G-Brownian motion. Utilizing the recently developed results of Backwar…
Two ML approaches compare in recognizing tables from historical records.
problem Recognizing rows and columns in hand-written registry books.
method Comparison of Conditional Random Field and Graph Convolutional Network.
result Both ML methods achieve an 89 F1 score for table detection.
Machine learning recreates the periodic table from element properties.
problem Recreating the periodic table using machine learning.
method Unsupervised machine learning with GTM for feature embedding.
result PTG autonomously generates various periodic table layouts.
We propose a new definition for tameness within the model of security prices as Itô processes that is risk-aware. We give a new definition for arbitrage and characterize it. We then prove a theorem that can be seen as an extension of the second fundamental theorem of asset pricing, and a theorem for valuation of contin…