This work proposes optimal decision rules for hierarchical classifiers to better align with evaluation metrics.
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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…
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…
BF-VAE estimates uncertainty from LF and HF QoI samples.
The paper investigates causal relationships in heart failure prediction using machine learning.
We compute the Ozsvath-Szabo Floer homologies HF^{+-} and HF-hat for three-manifolds obtained by integer surgery on a two-bridge knot.
Neural network fusion reduces data acquisition costs for multi-fidelity sources.
New method improves multi-fidelity Bayesian optimization by accounting for local correlations and varying noise.
Generative AI improves surrogate models by blending LF and HF data.
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…
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 …
Proposes a method to estimate conditional quantiles using both high-fidelity and low-fidelity data.
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…
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 …
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.
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…
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…
Efficiently estimates rare events using multifidelity modeling.
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…
Ozsvath and Szabo construct a spectral sequence with E_2 term Λ^*(H^1(Y;Z))\otimes Z[U,U^{-1}] converging to HF^\infty(Y,s) for a torsion Spin^c structure s. They conjecture that the differentials are completely determined by the integral triple cup product form via a proposed formula. In this paper, we prove that HF^\…
Let denote a knot inside the homology sphere and denote a knot inside a homology sphere -space. Let denote the 3-manifold obtained by splicing the complements of and . We show that .
Multidimensional recurrent neural networks (MDRNNs) have shown a remarkable performance in the area of speech and handwriting recognition. The performance of an MDRNN is improved by further increasing its depth, and the difficulty of learning the deeper network is overcome by using Hessian-free (HF) optimization. Given…
Semi-decentralized federated learning combines device-to-server and device-to-device communications for faster convergence.
HF-opt uses Hamiltonian dynamics to optimize functions, achieving accelerated rates with randomized integration time.
Programs compute Heegaard Floer invariants from open books.
Random shuffle method boosts HF dataset size 10-21 times.
We give an time algorithm to compute the generalized Heegaard Floer complexes 's for a two-bridge link by using nice diagrams. Using the link surgery formula of Manolescu-Ozsváth, we also show that and their -invariants of…
Let be a group with a finite balanced presentation . We associate a Heegaard Floer homology group with the pair based on some extra choices and technical assumptions. We show that is independent from these choices and also is invariant under stable Andrews-Curtis t…
Using bordered Floer theory, we construct an invariant for -orbifolds with singular set a knot that generalizes the hat flavor of Heegaard Floer homology for closed -manifolds . We show that for a large class of -orbifolds,…
The -equivariant Heegaard Floer cohomlogy of a knot in , constructed by Hendricks, Lipshitz, and Sarkar, is an isotopy invariant which is defined using bridge diagrams of drawn on a sphere. We prove that can be co…
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…
Improved surrogate model for field-valued QoIs using LF and HF simulations.
Given a diagram of a link K in S^3, we write down a Heegaard diagram for the branched-double cover Sigma(K). The generators of the associated Heegaard Floer chain complex correspond to Kauffman states of the link diagram. Using this model we make some computations of the homology \hat{HF}(Sigma(K)) as a graded group. W…
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…
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…
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…
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…
Let be an exact symplectic manifold equal to a symplectization near infinity and having stably trivializable tangent bundle, and be an exact symplectomorphism of which, near infinity, is equal to either the identity or the symplectization of a contactomorphism such that neither nor …
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…
Let a contact 3-manifold be the link of a normal surface singularity equipped with its canonical contact structure . We prove a special property of such contact 3-manifolds of "algebraic" origin: the Heegaard Floer invariant cannot lie in the image of the -action on .…
Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease progression and a source of considerable financial burden to the healthcare system. Consequently, the identification of patients at risk for …
New findings restrict Heegaard Floer homology for certain rational homology spheres.
This is the last of five papers that construct an isomorphism between the Seiberg-Witten Floer homology and the Heegaard Floer homology of a given compact, oriented 3-manifold.
Study predicts intraday stock trading volume using ML models.
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.
This paper gives a geometric interpretation of bordered Heegaard Floer homology for manifolds with torus boundary. If is such a manifold, we show that the type D structure may be viewed as a set of immersed curves decorated with local systems in . These curves-with-decoration ar…
The Comment cond-mat/0503325 is built around two core statements, both of which are plainly incorrect.
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…