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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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12.5%25.0%37.5%50.0% · Nov 199319922001200920172026
48 results for flat labels

Paper investigates methods to improve classification by inducing a hierarchy from flat labels.

problem Improving classification performance on datasets lacking a natural hierarchy.
method The approach involves clustering conditional distributions and using a hierarchical classifier with the induced hierarchy.
result The methods can discover latent hierarchies and improve accuracy in various applications.

Multiple conventions have been adopted for denoting Interval Exchange Transformations (IETs). The "non-labeled" convention was the original, while the "labeled" convention has proven convenient when investigating Flat Surfaces as described by IETs. We establish the relationship between Extended Rauzy Classes, an equiva…

2014-08-03abs ↗pdf ↗

This paper describes a polynomial invariant of virtual knots that is defined in terms of an integer labeling of the virtual knot diagram. This labeling is seen to derive from an essentially unique structure of affine flat biquandle for flat virtual diagrams. The invariant is discussed in detail with many examples,inclu…

2012-11-07abs ↗pdf ↗

Study finds only first and second eigenvalues are Courant-sharp for flat Klein bottle and cylinders.

problem Determining Courant-sharp eigenvalues for compact flat surfaces.
method Analyzing flat Klein bottle and cylinders, proving only first and second eigenvalues are Courant-sharp.
result Only first and second eigenvalues are Courant-sharp for flat Klein bottle and cylinders.

HCC extends conformal prediction to handle class hierarchies, improving prediction reliability.

problem Uncertainty quantification in classification models with class hierarchy considerations.
method Formulates HCC as a constrained optimization problem, ensuring coverage guarantees with a smaller subset of candidate solutions.
result HCC produces more reliable prediction sets by leveraging class hierarchy information.

The paper connects flatness to generalization in learning multi-index models with neural networks.

problem Understanding the generalization of non-convex neural networks using flatness measures.
method Analyzes 2-layer non-convex homogeneous neural networks and their connection to multi-index models.
result Flattest interpolators achieve small population loss and generalize well, establishing a direct link between flatness and generalization.

Proposes a hierarchical curriculum loss to improve model accuracy and interpretability.

problem Flat label spaces in classification algorithms fail to capture dependencies in real-world data.
method Introduces hierarchical curriculum loss with two properties: satisfying hierarchical constraints and providing non-uniform label weights.
result The proposed loss function significantly outperforms multiple baselines on real-world image datasets.

New research shows flat minima in robust loss landscapes correlate with good adversarial robustness.

problem Adversarial training leads to robust overfitting, poor robust generalization.
method Average- and worst-case metrics to measure flatness in robust loss landscapes.
result Flatness in robust loss landscapes correlates with good adversarial robustness.

In many machine learning problems, labeled training data is limited but unlabeled data is ample. Some of these problems have instances that can be factored into multiple views, each of which is nearly sufficent in determining the correct labels. In this paper we present a new algorithm for probabilistic multi-view lear…

2012-06-13abs ↗pdf ↗

We provide a new topological interpretation of the symplectic properties of gluing equations for triangulations of hyperbolic 3-manifolds, first discovered by Neumann and Zagier. We also extend the symplectic properties to more general gluings of PGL(2,C) flat connections on the boundaries of 3-manifolds with topologic…

2014-03-20abs ↗pdf ↗

We provide an explicit resolution of the existence problem for extremal Kaehler metrics on toric 4-orbifolds M with second Betti number b2(M)=2. More precisely we show that M admits such a metric if and only if its rational Delzant polytope (which is a labelled quadrilateral) is K-polystable in the relative, toric sens…

2013-02-27abs ↗pdf ↗

We provide a physical definition of new homological invariants Ha(M3)\mathcal{H}_a (M_3) of 3-manifolds (possibly, with knots) labeled by abelian flat connections. The physical system in question involves a 6d fivebrane theory on M3M_3 times a 2-disk, D2D^2, whose Hilbert space of BPS states plays the role of a basic build…

2017-01-23abs ↗pdf ↗

CNNs identify stock market trend endpoints based on expert opinion.

problem Finding optimal entry and exit points for stock market trends.
method Three CNN submodels sequentially identify changepoints, locate them, and classify trends as upward, downward, or flat.
result CNNs can identify long-term trends based on expert opinion, offering a new approach to stock market analysis.

Entangled embedded periodic nets and crystal frameworks are defined, along with their dimension type, homogeneity type, adjacency depth and periodic isotopy type. We obtain periodic isotopy classifications for various families of embedded nets with small quotient graphs. We enumerate the 25 periodic isotopy classes of …

2019-10-17abs ↗pdf ↗

Using the L^2 norm of the Higgs field as a Morse function, we study the moduli spaces of U(p,q)-Higgs bundles over a Riemann surface. We require that the genus of the surface be at least two, but place no constraints on (p,q). A key step is the identification of the function's local minima as moduli spaces of holomorph…

2002-11-27abs ↗pdf ↗

Overparameterization enhances SAM's effectiveness in minimizing sharpness.

problem Improving generalization in deep neural networks.
method Analysis of Sharpness-Aware Minimization (SAM) under varying degrees of overparameterization.
result Overparameterization significantly improves SAM's performance, particularly in noisy and sparse settings.

The step of expert taxa recognition currently slows down the response time of many bioassessments. Shifting to quicker and cheaper state-of-the-art machine learning approaches is still met with expert scepticism towards the ability and logic of machines. In our study, we investigate both the differences in accuracy and…

2017-08-23abs ↗pdf ↗

New homogeneous manifolds with invariant Bismut Ricci flat connections are constructed.

problem Constructing homogeneous manifolds with invariant Bismut Ricci flat connections.
method Classification and construction of homogeneous spaces with specific properties.
result Examples of compact homogeneous Riemannian manifolds with invariant Bismut Ricci flat connections are provided.

This paper deals essentially with affine or projective transformations of Lie groups endowed with a flat left invariant affine or projective structure. These groups are called flat affine or flat projective Lie groups. Our main results determine Lie groups admitting flat bi-invariant affine or projective structures. Th…

2014-08-31abs ↗pdf ↗

Study of symplectically flat connections and their functionals on smooth manifolds.

problem Understanding symplectically flat connections and their functionals on smooth manifolds.
method Extend symplectically flat connections to ζζ-flat connections, introduce functionals with zeroes as symplectically flat connections, study critical points of these functionals, describe characteristic classes of ζζ-flat bundles.
result Novel geometric flows and characteristic classes of ζζ-flat bundles are described.

We call the Lie algebra of a Lie group with a left invariant pseudo-Riemannian flat metric pseudo-Riemannian flat Lie algebra. We give a new proof of a classical result of Milnor on Riemannian flat Lie algebras. We reduce the study of Lorentzian flat Lie algebras to those with trivial center or those with degenerate ce…

2011-03-03abs ↗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.

A Lorentzian flat Lie group is a Lie group GG with a flat left invariant metric μμ with signature (1,n1)=(,+,,+)(1,n-1)=(-,+,\ldots,+). The Lie algebra g=TeG\mathfrak{g}=T_eG of GG endowed with   ,  =μ(e)\langle\;,\;\rangle=μ(e) is called flat Lorentzian Lie algebra. It is known that the metric of a flat Lorentzian Lie group is geodesical…

2014-01-05abs ↗pdf ↗

We provide an algebraic description of the Teichmüller space and moduli space of flat metrics on a closed manifold or orbifold and study its boundary, which consists of (isometry classes of) flat orbifolds to which the original object may collapse. It is also shown that every closed flat orbifold can be obtained by col…

2017-05-23abs ↗pdf ↗

We prove that the normal metric contact pairs with orthogonal characteristic foliations, which are either Bochner flat or locally conformally flat, are locally isometric to the Hopf manifolds. As a corollary we obtain the classification of locally conformally flat and Bochner-flat non-Kähler Vaisman manifolds.

2015-01-26abs ↗pdf ↗