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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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145290434579 · Jun 202019922001200920172026
48 results for effective version

New method estimates causal effects of multiple versions of treatment.

problem Ignoring multiple versions of treatment leads to biased causal effect estimates.
method Mixture-of-Experts framework for estimating version-specific causal effects.
result Effective method for estimating causal effects of latent versions.

New method reduces version space for CNNs, improving active learning performance.

problem Sampling bias in active learning hinders optimal hypothesis finding in neural networks.
method Version space reduction through prior mass reduction and diameter reduction, proposing a new Gibbs-vote disagreement method.
result Diameter-based querying method reduces version space more effectively than prior mass reduction and other methods.

The purpose of this article is to produce effective versions of some rigidity results in algebra and geometry. On the geometric side, we focus on the spectrum of primitive geodesic lengths (resp., complex lengths) for arithmetic hyperbolic 2-manifolds (resp., 3-manifolds). By work of Reid, this spectrum determines the …

2014-07-08abs ↗pdf ↗

New causal versions of MaxEnt and PIR avoid paradoxical probability updates.

problem Paradoxical probability updates in causal MaxEnt and PIR.
method Separate constraints into cause-specific and mechanism-specific restrictions.
result Causal MaxEnt avoids paradoxical updates and aligns with Information Geometric Causal Inference.

The main results of the paper are Proposition 3 and 4 which provide an effective way to construct minimal hypersurfaces in a Euclidean space. We demonstrate our technique by several new examples. This note is English translation of an earlier draft version written (in Russian) in September 1999. The final version of th…

2016-06-28abs ↗pdf ↗

The study of stable minimal surfaces in Riemannian 33-manifolds (M,g)(M, g) with non-negative scalar curvature has a rich history. In this paper, we prove rigidity of such surfaces when (M,g)(M, g) is asymptotically flat and has horizon boundary. As a consequence, we obtain an effective version of the positive mass theorem …

2015-03-19abs ↗pdf ↗

New method disentangles high-order effects in feature importance.

problem Quantifying cooperative effects in feature importance.
method Adaptive Leave One Covariate Out (LOCO) method to decompose LOCO into two-body and higher-order components.
result Decomposes LOCO into two-body and higher-order components, highlighting synergistic and redundant effects.

We correct a mistake in the published version of our paper. Our new conclusion is that the "implied leverage effect" for single stocks is underestimated by option markets for short maturities and overestimated for long maturities, while it is always overestimated for OEX options, except for the shortest maturities wher…

2011-05-25abs ↗pdf ↗

A constructive version of the Frobenius integrability theorem -- that can be programmed effectively -- is given. This is used in computing invariants of groups of low ranks and recover examples from a recent paper of Boyko, Patera and Popoyvich \cite{BPP}.

2014-11-01abs ↗pdf ↗

RS-PINN uses randomized smoothing to speed up high-dimensional PDE simulations without sacrificing accuracy.

problem High computational cost and bias in PINNs for high-dimensional PDEs.
method Introduces Gaussian noise for stochastic smoothing of PINNs, enabling Monte Carlo derivative approximation.
result Proposes bias correction techniques and a hybrid method to optimize the bias-variance trade-off.

Proposes a new method to estimate variable importance in black box models, mitigating correlation effects.

problem Correlation between covariates affects the interpretation of variable importance parameters.
method Develops a modified LOCO (Leave Out COvariates) method and uses semiparametric models for estimation.
result Shows how to estimate a modified LOCO method that mitigates correlation effects.

We prove an effective version of a theorem relating curve complex distance to electric distance in hyperbolic 3-manifolds, up to errors that are polynomial in the complexity of the underlying surface. We use this to give an effective proof of a result regarding maps between curve complexes of surfaces induced by finite…

2018-10-30abs ↗pdf ↗

Develops a sparsity-inducing Bayesian Causal Forest for estimating heterogeneous treatment effects.

problem Estimating heterogeneous treatment effects using observational data with varying degrees of sparsity.
method Introduces a sparsity-inducing version of Bayesian Causal Forests with additional priors to adjust covariate weights.
result Improves adaptability to sparse data generating processes and uncovering moderating factors driving heterogeneity.

In this work we present a technique to use natural language to help reinforcement learning generalize to unseen environments. This technique uses neural machine translation, specifically the use of encoder-decoder networks, to learn associations between natural language behavior descriptions and state-action informatio…

2017-07-26abs ↗pdf ↗

Causal models communicate our assumptions about causes and effects in real-world phe- nomena. Often the interest lies in the identification of the effect of an action which means deriving an expression from the observed probability distribution for the interventional distribution resulting from the action. In many case…

2018-06-19abs ↗pdf ↗

Cluster-DP improves differential privacy in randomized experiments by clustering data.

problem Reducing variance in causal effect estimation from differentially private data.
method Cluster-DP leverages a given cluster structure to improve the privacy-variance trade-off.
result Selecting higher-quality clusters decreases the variance penalty without compromising privacy guarantees.

Given a principal bundle PMP\to M over a Riemannian manifold with compact structure group GG, let us consider a stationary Yang-Mills connection AA with energy MFA2Λ\int_M |F_A|^2\le Λ. If we consider a sequence of such connections AiA_i, then it is understood that up to subsequence we can converge AiAA_i\to A to a singu…

2016-10-10abs ↗pdf ↗

Paper tackles estimating individual treatment effects from observational data.

problem Estimating the difference between outcomes with and without treatment from single observation.
method Formulated as inference from hidden variables, uses a model of four causal populations, proposes ECM algorithm.
result ECM algorithm provides better performance compared to baseline methods on synthetic and real-world data.

Paper explains learning property of logistic and softmax losses for balanced and imbalanced class data.

problem Understanding and optimizing loss functions for deep neural networks with class imbalances.
method Analyzing necessary conditions for convergence of logistic and softmax losses in CNNs.
result Proposes a novel reweighted logistic loss function that improves performance over softmax loss.

We consider harmonic sections of a bundle over the complement of a codimension 2 submanifold in a Riemannian manifold, which can be thought of as multivalued harmonic functions. We prove a result to the effect that these are stable under small deformations of the data. The proof is an application of a version of the Na…

2019-12-17abs ↗pdf ↗

This study compares machine learning methods for high-cardinality categorical variables.

problem Machine learning struggles with high-cardinality categorical variables.
method Empirical comparison of tree-boosting, deep neural networks, and linear mixed effects models.
result Tree-boosting with random effects outperforms deep neural networks with random effects.

We analyze the effect of adding, removing, and moving basepoints on link Floer homology. We prove that adding or removing basepoints via a procedure called quasi-stabilization is a natural operation on a certain version of link Floer homology, which we call CFLUVCFL_{UV}^\infty. We consider the effect on the full link Flo…

2016-04-14abs ↗pdf ↗

We establish an effective version of the classical Lie--Kolchin Theorem. Namely, let A,BGLm(C)A,B\in\mathrm{GL}_m(\mathbb{C}) be quasi--unipotent matrices such that the Jordan Canonical Form of BB consists of a single block, and suppose that for all k0k\geq0 the matrix ABkAB^k is also quasi--unipotent. Then AA and BB have a…

2019-04-01abs ↗pdf ↗

Study adds memory effect to Solow-Swan model for more accurate economic growth modeling.

problem Inaccuracies in classical Solow-Swan model in capturing long-term dynamics.
method Introduced fractional calculus with Caputo derivative into Solow-Swan framework.
result Fractional-order model shows significant impact on capital accumulation and stability.

The multi-armed restless bandit problem is studied in the case where the pay-off distributions are stationary φ\varphi-mixing. This version of the problem provides a more realistic model for most real-world applications, but cannot be optimally solved in practice, since it is known to be PSPACE-hard. The objective of …

2017-02-22abs ↗pdf ↗

We compute the effect of concordance surgery, a generalization of knot surgery defined using a self-concordance of a knot, on the Ozsváth-Szabó 4-manifold invariant. The formula involves the graded Lefschetz number of the concordance map on knot Floer homology. The proof uses the sutured Floer TQFT, and a version of su…

2018-04-17abs ↗pdf ↗

Effective drilling and filling bounds for hyperbolic 3-manifolds.

problem Understanding changes in metrics and geodesics during Dehn fillings of hyperbolic 3-manifolds.
method Combining tools from Kleinian group theory to transfer results from finite-volume to infinite-volume manifolds.
result Effective bilipschitz and complex length bounds quantifying filling theorems.

The paper reviews identifiability in linear and nonlinear models, from Gaussian to non-Gaussian.

problem Identifiability issues in latent-variable and structural-equation models, especially in nonlinear cases.
method Review of identifiability theory for linear and nonlinear models, including factor analysis and structural equation models.
result Even nonparametric nonlinear models can be estimated with additional assumptions.

In this paper we study Morse homology and cohomology with local coefficients, i.e. "twisted" Morse homology and cohomology, on closed finite dimensional smooth manifolds. We prove a Morse theoretic version of Eilenberg's Theorem, and we prove isomorphisms between twisted Morse homology, Steenrod's CW-homology with loca…

2019-11-18abs ↗pdf ↗

Study asset price bubbles using random matching and stochastic factors.

problem Understanding and modeling asset price bubbles through investor contagion.
method Developed a stochastic model of liquidity-based asset price bubbles using random matching mechanism.
result Derived conditions for arbitrage-free financial market models.