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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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24497397 · May 202619922001200920172026
48 results for threshold compatibility

Geometric framework for signed multivariate tail-dependence compatibility at various thresholds.

problem Modeling and analyzing signed multivariate tail-dependence across different thresholds.
method Developed a geometric witness framework to represent and invert signed tail families, identifying nonnegative weights and normalized masses.
result Characterization and synthesis of signed multivariate tail-dependence at finite thresholds, preserving the complete signed tail family throughout.

New method improves compatibility of risk stratification models without sacrificing accuracy.

problem Compatibility issues arise when updating clinical machine learning models.
method Proposes rank-based compatibility measure and new loss function.
result Increased compatibility of models by 0.019 with no loss in discriminative performance.

Framework controls uncertainty in LLMs without labels or probabilities.

problem Managing uncertainty in black-box LLMs without token-level probability or true labels.
method Integrates generative models, UCP, and conformal alignment to control uncertainty.
result Achieves close-to-nominal coverage and tighter thresholds than split UCP.

Defines compatibility between Jacobi structures and pseudo-Riemannian metrics on Jacobi algebroids.

problem Generalizing compatibility between Poisson and pseudo-Riemannian metrics to Jacobi structures.
method Introduces and studies compatibility conditions for Jacobi structures and pseudo-Riemannian metrics on Jacobi algebroids.
result Compatibility conditions are preserved under Poissonization and equivalent to Sasakian structures for contact pseudo-metrics.

The paper characterizes compatible linear connections on 3D Finsler manifolds.

problem Characterizing compatible linear connections on Finsler manifolds of dimension three.
method Intrinsic method to characterize compatible linear connections, focusing on indicatrices and Euclidean symmetries.
result If a compatible linear connection is not unique, indicatrices must be Euclidean surfaces of revolution.

The paper proposes reusable network components by making them compatible across tasks.

problem Training networks for different tasks independently leads to incompatible components.
method The paper splits a network into a features extractor and a target task head, and proposes various approaches to make them compatible.
result The proposed methods produce components that are directly compatible without compromising accuracy on original tasks.

The paper studies properties of group relations induced by compatible coarse structures.

problem Properties of asymptotic resemblance relations on groups.
method Generalization of asymptotic dimension and introduction of set theoretic coupling.
result Groups with compatible coarse structures that admit a set theoretic coupling are asymptotic equivalent.

Derdzinski and Shen's theorem on the restrictions posed by a Codazzi tensor on the Riemann tensor holds more generally when a Riemann-compatible tensor exists. Several properties are shown to remain valid in this broader setting. Riemann compatibility is equivalent to the Bianchi identity of the new "Codazzi deviation …

2012-04-05abs ↗pdf ↗

We disprove the generalized Chern-Hamilton conjecture on the existence of critical compatible metrics on contact 33-manifolds. More precisely, we show that a contact 33-manifold (M,α)(M,α) admits a critical compatible metric for the Chern-Hamilton energy functional if and only if it is Sasakian or its associated Reeb fl…

2023-11-27abs ↗pdf ↗

A linear connection on a Finsler manifold is called compatible to the metric if its parallel transports preserve the Finslerian length of tangent vectors. Generalized Berwald manifolds are Finsler manifolds equipped with a compatible linear connection. Since the compatibility to the Finslerian metric does not imply the…

2020-01-13abs ↗pdf ↗

Some general properties of compatible Poisson brackets of hydrodynamic type are discussed, in particular: (1) an invariant differential-geometric criterion of the compatibility based on the Nijenhuis tensor; (2) the Lax pair with a spectral parameter governing compatible Poisson brackets in the diagonalizable case; (3)…

2000-05-23abs ↗pdf ↗

The construction of gauge theories beyond the realm of Lie groups and algebras leads one to consider Lie groupoids and algebroids equipped with additional geometrical structures which, for gauge invariance of the construction, need to satisfy particular compatibility conditions. This paper analyzes these compatibilitie…

2016-03-14abs ↗pdf ↗

New proof for unique semi-symmetric compatible linear connection on Finsler manifolds.

problem Existence and uniqueness of semi-symmetric compatible linear connections on Finsler manifolds.
method New linear algebra proof without integration, using convex body properties and intrinsic equations.
result Uniqueness of semi-symmetric compatible linear connection proved.

Given the Riemann, or the Weyl, or a generalized curvature tensor K, a symmetric tensor bijb_{ij} is named `compatible' with the curvature tensor if bimKjklm+bjmKkilm+bkmKijlm=0b_i{}^m K_{jklm} + b_j{}^m K_{kilm} + b_k{}^m K_{ijlm} = 0. Amongst showing known and new properties, we prove that they form a special Jordan algebra, i.e. the symmetriz…

2019-10-08abs ↗pdf ↗

Paper improves privacy-preserving measurement of advertising incrementality.

problem Privacy degradation in randomized lift tests for advertising measurement.
method Formulates a robust causal decision problem under signal losses, projecting clean worlds onto incrementality.
result Sharp decision frontier shows valid certification or rejection outside the frontier.

The study examines backward compatibility issues in ML systems, especially with noisy data.

problem Backward compatibility challenges in ML systems, especially with noisy data.
method Empirical analysis of ML systems across different architectures and datasets, focusing on data shifts and noise.
result Backward compatibility issues arise even without data shift due to optimization stochasticity and training on large-scale noisy datasets can significantly decrease compatibility.

Generalized Lagrange-Weyl structures and compatible connections are introduced as a natural generalization of similar notions from Riemannian geometry. Exactly as in Riemannian case, the compatible connection is unique if certain symmetry conditions with respect to vertical and horizontal Christoffel symbols are impose…

2006-05-24abs ↗pdf ↗

New auction design uses statistical learning to reduce costs and improve fairness.

problem Designing efficient multi-item auctions with reduced implementation costs and fairness.
method Nonparametric density estimation for credible intervals, two new strategies.
result Strategies consistently outperform alternative methods in revenue maximization and cost reduction.

AI systems are being deployed to support human decision making in high-stakes domains. In many cases, the human and AI form a team, in which the human makes decisions after reviewing the AI's inferences. A successful partnership requires that the human develops insights into the performance of the AI system, including …

2019-06-04abs ↗pdf ↗

New algorithm for reinforcement learning in uncertain environments with unknown thresholds.

problem Safety in reinforcement learning in unknown and uncertain environments.
method Growing-Window estimator sampling and Stochastic Pessimistic-Optimistic Thresholding (SPOT) algorithm.
result Achieves sublinear regret and constraint violation of ildeO(T) ilde{\mathcal{O}}(\sqrt{T}).

A new SSL method uses instance-dependent thresholds to improve accuracy.

problem Improving semi-supervised learning by better selecting confident unlabeled instances.
method Proposes instance-dependent thresholds that vary based on the ambiguity and error rates of pseudo-labels for each unlabeled instance.
result Demonstrates that instance-dependent thresholds provide a probabilistic guarantee for correct pseudo-labels.

Adaptive algorithm for outlier detection by balancing arm exploration and threshold estimation.

problem Identifying outliers in a set of rewards where the threshold is a function of all rewards.
method Adaptively updated confidence interval for the threshold based on previous rounds' estimates, balancing exploration of individual arms and the outlier threshold.
result Efficient algorithm with reduced sample complexity for outlier detection.

The article examines different thresholding methods for improving PAM algorithm in cancer classification.

problem High-dimensional classification with too many features selected by PAM.
method Extends PAM with hard and order thresholding methods and a deep search algorithm.
result Improved cancer status prediction accuracy and smaller number of features.

No-regret learning with strategic experts, incentivized.

problem Online learning with strategic experts who misreport beliefs.
method Building on wagering mechanisms, we provide algorithms for no-regret and incentive compatibility in both full and partial information settings.
result Our algorithms achieve no regret and incentive compatibility for myopic experts, with comparable regret to classic no-regret algorithms and diminishing regret for forward-looking agents.