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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.

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17345168 · May 202619922001200920172026
48 results for FP index

New validity index for fuzzy-possibilistic c-means clustering.

problem Conflicting results in determining the optimal number of clusters due to noisy data points and outliers.
method Introducing a new validity index (FP index) for fuzzy-possibilistic c-means clustering.
result FP index works well in datasets with varying cluster shapes and densities.

If G1,...,GnG_1,...,G_n are limit groups and SG1×...×GnS\subset G_1\times...\times G_n is of type $\FP_n(\mathbb Q)$ then SS contains a subgroup of finite index that is itself a direct product of at most nn limit groups. This settles a question of Sela.

2007-04-30abs ↗pdf ↗

We study the asymptotic growth of homology groups and the cellular volume of classifying spaces as one passes to normal subgroups Gn<GG_n<G of increasing finite index in a fixed finitely generated group GG, assuming nGn=1\bigcap_n G_n =1. We focus in particular on finitely presented residually free groups, calculating thei…

2013-09-07abs ↗pdf ↗

We consider vector fixed point (FP) equations in large dimensional spaces involving random variables, and study their realization-wise solutions. We have an underlying directed random graph, that defines the connections between various components of the FP equations. Existence of an edge between nodes i, j implies the …

2018-09-14abs ↗pdf ↗

Study on homological Dehn functions of groups of type FP2FP_2.

problem Understanding the homological Dehn functions of groups of type FP2FP_2.
method Proved foundational results, studied homological Dehn functions of Leary's groups, and provided methods to obtain groups with specific homological Dehn functions.
result Found groups of type FP2FP_2 with quartic homological Dehn function and unsolvable word problem.

Optimized Franz-Parisi criterion matches SQ lower bounds for various statistical models.

problem Understanding computational hardness in statistical inference.
method Proposed and refined Franz-Parisi criterion, established equivalence with SQ lower bounds.
result Optimized Franz-Parisi criterion is equivalent to Statistical Query (SQ) lower bounds.

We construct uncountably many discrete groups of type FPFP; in particular we construct groups of type FPFP that do not embed in any finitely presented group. We compute the ordinary, 2\ell^2- and compactly-supported cohomology of these groups. For each n4n\geq 4 we construct a closed aspherical nn-manifold that admit…

2015-12-21abs ↗pdf ↗

FP uses random projections to train networks without feedback, achieving comparable performance to backpropagation.

problem Training neural networks without feedback from downstream layers.
method Forward Projection (FP) method that uses randomised nonlinear projections and closed-form regression.
result FP achieves comparable generalisation to backpropagation methods with a single forward pass, offering significant speedup.

GGFPS improves model performance by sampling molecules more efficiently.

problem Improving model performance and reducing data costs in chemistry problems.
method Gradient-Guided Furthest Point Sampling (GGFPS) that leverages molecular force norms.
result GGFPS leads to superior data efficiency and model robustness compared to other sampling methods.

In this paper we create many examples of hyperbolic groups with subgroups satisfying interesting finiteness properties. We give the first examples of subgroups of hyperbolic groups which are of type FP2FP_2 but not finitely presented. We give uncountably many groups of type FP2FP_2 with similar properties to those subgro…

2018-09-27abs ↗pdf ↗

We exploit Zlil Sela's description of the structure of groups having the same elementary theory as free groups: they and their finitely generated subgroups form a prescribed subclass E of the hyperbolic limit groups. We prove that if G1,...,GnG_1,...,G_n are in E then a subgroup ΓG1×...×GnΓ\subset G_1\times...\times G_n is of type $\…

2005-06-23abs ↗pdf ↗

FP-UCB algorithm achieves bounded regret for finitely parameterized multi-armed bandits.

problem Finitely parameterized multi-armed bandits with unknown but known parameter set.
method FP-UCB algorithm using structural information about the parameter set.
result FP-UCB achieves bounded regret under structural condition, logarithmic otherwise.

Formanek and Procesi have demonstrated that Aut(F_n) is not linear for n >2. Their technique is to construct nonlinear groups of a special form, which we call FP-groups, and then to embed a special type of automorphism group, which we call a poison group, in Aut(F_n), from which they build an FP-group. We first prove t…

2001-03-24abs ↗pdf ↗

Previously one of the authors constructed uncountable families of groups of type FPFP and of nn-dimensional Poincaré duality groups for each n4n\geq 4. We strengthen these results by showing that these groups comprise uncountably many quasi-isometry classes. We deduce that for each n4n\geq 4 there are uncountably many…

2017-12-15abs ↗pdf ↗

New work shows FP potential monotonicity equals low-degree polynomial estimators limits.

problem Establishing a precise mathematical relationship between statistical physics and polynomial estimators limits.
method Analyzing Gaussian additive models (GAMs) to show FP potential monotonicity equals low-degree polynomial estimators limits.
result For a broad family of Gaussian additive models, the power of low-degree polynomials is equivalent to the monotonicity of the annealed FP potential.

We extend first-order model agnostic meta-learning algorithms (including FOMAML and Reptile) to image segmentation, present a novel neural network architecture built for fast learning which we call EfficientLab, and leverage a formal definition of the test error of meta-learning algorithms to decrease error on out of d…

2019-12-13abs ↗pdf ↗

This paper extends FP's method to complex hyperbolic branched covers to find Einstein metrics.

problem Finding Einstein metrics on non-locally symmetric manifolds.
method Generalized FP's construction to complex hyperbolic branched covers.
result Yields a negatively curved Einstein metric that asymptotically approaches GH's metric.

The presence of a sparse "truth" has been a constant assumption in the theoretical analysis of sparse PCA and is often implicit in its methodological development. This naturally raises questions about the properties of sparse PCA methods and how they depend on the assumption of sparsity. Under what conditions can the r…

2014-01-27abs ↗pdf ↗

FP-BMA improves generalization by encouraging flat posteriors in Bayesian Model Averaging.

problem Lack of flat posterior in approximate Bayesian inference methods hinders effective Bayesian Model Averaging.
method Proposes Flat Posterior-aware Bayesian Model Averaging (FP-BMA) and Flat Posterior-aware Bayesian Transfer Learning schemes.
result FP-BMA successfully captures flat posteriors, improving generalization performance.

Develops a neural network approach to solve inverse stochastic problems from particle observations.

problem Inference of Fokker-Planck equation coefficients from sparse particle data.
method Physics-informed neural networks (PINNs) with Kullback-Leibler divergence loss.
result Simultaneous inference of Fokker-Planck equation and multi-dimensional PDF from few particle observations.

The paper classifies PD_4-complexes based on their fundamental group properties.

problem Understanding the structure of PD_4-complexes based on their fundamental group properties.
method Analyzing the fundamental group and its modules to classify PD_4-complexes.
result The classification of PD_4-complexes based on their fundamental group properties.

Prognostics and Health Management (PHM) is an emerging engineering discipline which is concerned with the analysis and prediction of equipment health and performance. One of the key challenges in PHM is to accurately predict impending failures in the equipment. In recent years, solutions for failure prediction have evo…

2019-10-04abs ↗pdf ↗

Hougthon's groups H_n is a family of groups where each H_n consists of `translations at infinity' on n rays of discrete points emanating from the origin on the plane. Brown shows H_n has type FP_n-1 but not FP_n by constructing infinite dimensional cell complex on which H_n acts with certain conditions. We modify his i…

2012-12-02abs ↗pdf ↗

A novel score-based method solves high-dimensional Fokker-Planck equations with improved accuracy and speed.

problem High-dimensional Fokker-Planck equations suffer from the curse of dimensionality, leading to numerical errors and slow sampling.
method Score-based Physics-Informed Neural Networks (PINNs) that fit the score function in SDEs, using three methods: Score Matching, Sliced Score Matching, and Score-PINN.
result The score-based method outperforms traditional Monte Carlo and vanilla PINNs in high-dimensional settings, offering faster sampling and reduced errors.

Winograd convolution is widely used in deep neural networks (DNNs). Existing work for DNNs considers only the subset Winograd algorithms that are equivalent to Toom-Cook convolution. We investigate a wider range of Winograd algorithms for DNNs and show that these additional algorithms can significantly improve floating…

2019-05-13abs ↗pdf ↗

We show that the Basilica Thompson group introduced by Belk and Forrest is not finitely presented, and in fact is not of type FP_2. The proof involves developing techniques for proving non-simple connectedness of certain subcomplexes of CAT(0) cube complexes.

2016-03-03abs ↗pdf ↗

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.

The behavior of stock market returns over a period of 1-60 days has been investigated for S&P 500 and Nasdaq within the framework of nonextensive Tsallis statistics. Even for such long terms, the distributions of the returns are non-Gaussian. They have fat tails indicating that the stock returns do not follow a random …

2016-08-28abs ↗pdf ↗

This paper classifies quadratic form parameters over integers and computes their Witt groups.

problem Classifying quadratic form parameters over integers and computing their Witt groups.
method Study of quadratic forms and extended quadratic forms over the integers, defining and comparing different definitions of extended quadratic forms.
result Classification of all quadratic form parameters over the integers and computation of their Witt groups.

We present a stochastic agent-based model for the distribution of personal incomes in a developing economy. We start with the assumption that incomes are determined both by individual labour and by stochastic effects of trading and investment. The income from personal effort alone is distributed about a mean, while the…

2009-05-25abs ↗pdf ↗