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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.

168,742 papers · 148 categories

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4181122162 · May 202619922001200920172026
48 results for hF_β scores

This work proposes optimal decision rules for hierarchical classifiers to better align with evaluation metrics.

problem Heuristic decision rules in hierarchical classification do not align with evaluation metrics.
method Derives optimal decision rules for various prediction settings, focusing on hierarchical hFβhF_β scores.
result Optimal decision rules enhance the performance and reliability of hierarchical classifiers.

We give a bordered extension of involutive HF-hat and use it to give an algorithm to compute involutive HF-hat for general 3-manifolds. We also explain how the mapping class group action on HF-hat can be computed using bordered Floer homology. As applications, we prove that involutive HF-hat satisfies a surgery exact t…

2017-06-20abs ↗pdf ↗

Hessian-free (HF) optimization has been successfully used for training deep autoencoders and recurrent networks. HF uses the conjugate gradient algorithm to construct update directions through curvature-vector products that can be computed on the same order of time as gradients. In this paper we exploit this property a…

2013-01-16abs ↗pdf ↗

The paper investigates causal relationships in heart failure prediction using machine learning.

problem Understanding the causal relationships between clinical variables and heart failure.
method Proposes a new computational framework for causal structure discovery (CSD) of mixed-type clinical variables for binary disease outcomes.
result Feature importance from nonlinear classifiers strongly correlates with causal strength of variables, but not differentiating cause and effect.

Neural network fusion reduces data acquisition costs for multi-fidelity sources.

problem Reducing cost in acquiring information from multiple data sources with varying fidelity.
method Employing a novel neural network architecture for nonlinear manifold learning of multi-fidelity data.
result Our approach provides high predictive power and quantifies various sources uncertainties.

New method improves multi-fidelity Bayesian optimization by accounting for local correlations and varying noise.

problem Existing multi-fidelity Bayesian optimization methods assume global correlation and constant noise, which limits performance.
method Proposes an MF emulation method that learns noise models for each data source and leverages locally correlated LF sources.
result Improves performance of multi-fidelity Bayesian optimization by accounting for local correlations and varying noise.

Generative AI improves surrogate models by blending LF and HF data.

problem Data scarcity between high-fidelity and low-fidelity simulations.
method Probabilistic multi-fidelity surrogate framework using generative transfer learning.
result The model achieves HF accuracy with fewer HF evaluations.

The symplectic Floer homology HF_*(f) of a symplectomorphism f:S->S encodes data about the fixed points of f using counts of holomorphic cylinders in R x M_f, where M_f is the mapping torus of f. We give an algorithm to compute HF_*(f) for f a surface symplectomorphism in a pseudo-Anosov or reducible mapping class, com…

2008-07-16abs ↗pdf ↗

In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In our method, we construct on each iteration a Krylov subspace formed by the gradient and an approximation to the Hessian matrix, and then use a …

2011-11-18abs ↗pdf ↗

Proposes a method to estimate conditional quantiles using both high-fidelity and low-fidelity data.

problem Difficulty in estimating conditional quantiles with scarce high-fidelity data.
method Two-stage, model-agnostic method using local quantile link and level function estimation.
result The method yields more accurate quantile estimates and tighter prediction intervals.

Computational simulations with different fidelity have been widely used in engineering design. A high-fidelity (HF) model is generally more accurate but also more time-consuming than an low-fidelity (LF) model. To take advantages of both HF and LF models, multi-fidelity surrogate models that aim to integrate informatio…

2019-06-22abs ↗pdf ↗

We define a Floer-homology invariant for knots in an oriented three-manifold, closely related to the holomorphic disk Floer homologies for three-manifolds defined in an earlier paper. We set up basic properties of these invariants, including an Euler characteristic calculation, behaviour under connected sums. Then, we …

2002-09-06abs ↗pdf ↗

We give a construction of a version of the Gromov-Witten classes, Q: H_*(J) -> HF_*(M) otimes ... otimes HF^*(M), within the context of symplectic Floer (co)homology. In particular, this gives a functorial approach to products and relations in symplectic Floer (co)homology.

1995-01-08abs ↗pdf ↗

In this paper, we present a data-driven model for forecasting the production increase after hydraulic fracturing (HF). We use data from fracturing jobs performed at one of the Siberian oilfields. The data includes features, characterizing the jobs, and geological information. To predict an oil rate after the fracturing…

2019-02-05abs ↗pdf ↗

We make a detailed study of the Heegaard Floer homology of the product of a closed surface Sigma_g of genus g with S^1. We determine HF^+ for this 3-manifold completely for the spin^c structure having trivial first Chern class, which for g>2 was previously unknown. We show that in this case HF^\infty is closely related…

2005-02-15abs ↗pdf ↗

Efficiently estimates rare events using multifidelity modeling.

problem Estimating rare events with computationally expensive models.
method Active learning with multifidelity modeling, adapting the number of high-fidelity simulations based on problem complexity and desired accuracy.
result Significantly reduced the number of high-fidelity model calls while maintaining accuracy.

Lattice cohomology, defined by Némethi in (arXiv:0709.0841), is an invariant of negative definite plumbed 3-manifolds which conjecturally computes the Heegaard Floer homology HF^+. We prove a surgery exact triangle for the lattice cohomology analogous to the one for HF^+. This is a step towards comparing these two inva…

2008-10-05abs ↗pdf ↗

Let KK denote a knot inside the homology sphere YY and KK' denote a knot inside a homology sphere LL-space. Let X=Y(K,K)X=Y(K,K') denote the 3-manifold obtained by splicing the complements of KK and KK'. We show that rank(HF^(X))rank(HF^(Y))\text{rank}(\widehat{HF}(X)) \ge \text{rank}(\widehat{HF}(Y)).

2018-01-17abs ↗pdf ↗

Semi-decentralized federated learning combines device-to-server and device-to-device communications for faster convergence.

problem Faster convergence in federated learning with decentralized model training.
method Two timescale hybrid federated learning (TT-HF) with cooperative D2D model aggregations.
result Achieves sublinear convergence rate of O(1/t) with adaptive control algorithm.

HF-opt uses Hamiltonian dynamics to optimize functions, achieving accelerated rates with randomized integration time.

problem Optimizing functions efficiently and accelerating convergence rates.
method Randomized Hamiltonian flow (RHF) with accelerated convergence rates.
result RHGD achieves accelerated convergence rates similar to Nesterov's AGD.

We give an O(p2)O(p^{2}) time algorithm to compute the generalized Heegaard Floer complexes As1,s2(L)A_{s_{1},s_{2}}^{-}(\overrightarrow{L})'s for a two-bridge link L=b(p,q)\overrightarrow{L}=b(p,q) by using nice diagrams. Using the link surgery formula of Manolescu-Ozsváth, we also show that HF{\bf HF}^{-} and their dd-invariants of…

2014-02-24abs ↗pdf ↗

Let GG be a group with a finite balanced presentation PP. We associate a Heegaard Floer homology group HF^P(G)\widehat{HF}_P(G) with the pair (G,P)(G,P) based on some extra choices and technical assumptions. We show that HF^P(G)\widehat{HF}_P(G) is independent from these choices and also is invariant under stable Andrews-Curtis t…

2018-10-18abs ↗pdf ↗

Using bordered Floer theory, we construct an invariant HFO^(Yorb)\widehat{\mathit{HFO}}(Y^{\text{orb}}) for 33-orbifolds YorbY^{\text{orb}} with singular set a knot that generalizes the hat flavor HF^(Y)\widehat{\mathit{HF}}(Y) of Heegaard Floer homology for closed 33-manifolds YY. We show that for a large class of 33-orbifolds,…

2018-08-27abs ↗pdf ↗

The Z2\mathbb{Z}_{2}-equivariant Heegaard Floer cohomlogy HF^Z2(Σ(K))\widehat{HF}_{\mathbb{Z}_{2}}(Σ(K)) of a knot KK in S3S^{3}, constructed by Hendricks, Lipshitz, and Sarkar, is an isotopy invariant which is defined using bridge diagrams of KK drawn on a sphere. We prove that HF^Z2(Σ(K))\widehat{HF}_{\mathbb{Z}_{2}}(Σ(K)) can be co…

2018-10-03abs ↗pdf ↗

Bordered Heegaard Floer homology is an invariant for three-manifolds with boundary. In particular, this invariant associates to a handle decomposition of a surface F a differential graded algebra, and to an arc slide between two handle decompositions, a bimodule over the two algebras. In this paper, we describe these b…

2010-10-13abs ↗pdf ↗

Improved surrogate model for field-valued QoIs using LF and HF simulations.

problem Accurate and efficient modeling of field-valued quantities under uncertain inputs.
method Bifidelity Karhunen-Loève expansion with active learning.
result Consistent improvements in predictive accuracy and sample efficiency.

Ozsváth and Szabó gave a combinatorial description for the Heegaard Floer homology of boundaries of certain negative-definite plumbings. Némethi constructed a remarkable algorithm for executing these computations for almost-rational plumbings, and his work gives a formula computing the invariants for the Brieskorn homo…

2012-06-12abs ↗pdf ↗

We show that the knot lattice homology of a knot in an L-space is equivalent to the knot Floer homology of the same knot (viewed these invariants as filtered chain complexes over the polynomial ring Z/2Z [U]). Suppose that G is a negative definite plumbing tree which contains a vertex w such that G-w is a union of rati…

2012-07-17abs ↗pdf ↗

Heegaard Floer homology, first introduced by P. Ozsvath and Z. Szabo, associates to a 3-manifold Y a family of relatively graded Abelian groups HF(Y,t), indexed by Spin^c structures t on Y. In the case that Y is a rational homology sphere, Ozsvath and Szabo lift the relative Z-grading to an absolute Q-grading. This ind…

2006-07-31abs ↗pdf ↗

Hierarchical forecasting (HF) is needed in many situations in the supply chain (SC) because managers often need different levels of forecasts at different levels of SC to make a decision. Top-Down (TD), Bottom-Up (BU) and Optimal Combination (COM) are common HF models. These approaches are static and often ignore the d…

2019-12-01abs ↗pdf ↗

Let (M,w) be a compact symplectic manifold, and L a compact, embedded Lagrangian submanifold in M. Fukaya, Oh, Ohta and Ono construct Lagrangian Floer cohomology for such M,L, yielding groups HF^*(L,b;Λ) for one Lagrangian or HF^*((L,b),(L',b');Λ) for two, where b,b' are choices of bounding cochains, and exist if and o…

2008-03-05abs ↗pdf ↗

Let a contact 3-manifold (Y,ξ0)(Y, ξ_0) be the link of a normal surface singularity equipped with its canonical contact structure ξ0ξ_0. We prove a special property of such contact 3-manifolds of "algebraic" origin: the Heegaard Floer invariant c+(ξ0)HF+(Y)c^+(ξ_0)\in HF^+(-Y) cannot lie in the image of the UU-action on HF+(Y)HF^+(-Y).…

2018-09-28abs ↗pdf ↗

New findings restrict Heegaard Floer homology for certain rational homology spheres.

problem The LL-space conjecture or Heegaard Floer homology geography.
method Verification of a stronger geography restriction for rational homology spheres.
result Heegaard Floer homology satisfies a stronger geography restriction for a wide class of rational homology spheres.

This is a survey of bordered Heegaard Floer homology, an extension of the Heegaard Floer invariant HF-hat to 3-manifolds with boundary. Emphasis is placed on how bordered Heegaard Floer homology can be used for computations.

2012-11-29abs ↗pdf ↗

Deep Neural Network (DNN) acoustic models often use discriminative sequence training that optimises an objective function that better approximates the word error rate (WER) than frame-based training. Sequence training is normally implemented using Stochastic Gradient Descent (SGD) or Hessian Free (HF) training. This pa…

2018-04-06abs ↗pdf ↗