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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% · Sep 199319922001200920172026
48 results for even points

Paper defines the payback period for nonconventional cash flows using axioms.

problem Defining the payback period for nonconventional cash flows is challenging.
method Used axiomatic approach to define the payback period.
result The last break-even point of the project balance is the only definition consistent with axioms.

Study circle actions on manifolds with 3 fixed points, finding dimension constraints and unique structures.

problem Characterize circle actions on oriented manifolds with exactly 3 fixed points.
method Analyzes manifold dimensions, isotropy submanifolds, and uses quaternionic projective space as a reference.
result For a manifold with three fixed points, its dimension must be a multiple of 4, and specific weights are unique.

Early SGD hyperparameters affect deep neural network training, showing a break-even point.

problem Understanding how early SGD hyperparameters influence deep neural network training.
method Analysis of stochastic gradient descent (SGD) hyperparameters and their effects on the optimization trajectory.
result A break-even point exists where SGD implicitly regularizes the loss surface and improves gradient conditioning.

Poor (even random) starting points for learning/training/optimization are common in machine learning. In many settings, the method of Robbins and Monro (online stochastic gradient descent) is known to be optimal for good starting points, but may not be optimal for poor starting points -- indeed, for poor starting point…

2016-02-09abs ↗pdf ↗

For each link L in S^3 and every quantum grading j, we construct a stable homotopy type X^j_o(L) whose cohomology recovers Ozsvath-Rasmussen-Szabo's odd Khovanov homology, H_i(X^j_o(L)) = Kh^{i,j}_o(L), following a construction of Lawson-Lipshitz-Sarkar of the even Khovanov stable homotopy type. Furthermore, the odd Kh…

2018-01-19abs ↗pdf ↗

Over-parameterization makes optimization easier for simple neural networks, even with minor extra neurons.

problem Understanding the impact of over-parameterization on optimization landscapes of shallow neural networks.
method Analyzing a simple ReLU neural network with Gaussian inputs, focusing on optimization properties and landscape changes.
result Over-parameterization makes the objective function one-point strongly convex in most directions, aiding optimization.

This paper extends homological stability results for configuration spaces of manifolds.

problem Homological stability of configuration spaces of manifolds.
method Analyzing the cohomology of configuration spaces of manifolds, focusing on stability in odd and even degrees.
result The stable range for homology groups of configuration spaces depends on the dimension of the manifold and the number of configuration points.

We construct, for m6m\geq 6 and 2nm2n\leq m, closed manifolds MmM^{m} with finite nonzero φ(Mm,Sn\varphi(M^{m},S^{n}), where φ(M,N)\varphi(M,N) denotes the minimum number of critical points of a smooth map MNM\to N. We also give some explicit families of examples for even m6,n=3m\geq 6, n=3, taking advantage of the Lie group structu…

2016-11-14abs ↗pdf ↗

A geometrical structure on even-dimensional manifolds is defined which generalizes the notion of a Calabi-Yau manifold and also a symplectic manifold. Such structures are of either odd or even type and can be transformed by the action of both diffeomorphisms and closed 2-forms. In the special case of six dimensions we …

2002-09-10abs ↗pdf ↗

This paper refines previous work by the first author. We study the question of which links in the 3-sphere can be obtained as closures of a given 1-manifold in an unknotted solid torus in the 3-sphere (or genus-1 tangle) by adjoining another 1-manifold in the complementary solid torus. We distinguish between even and o…

2014-07-30abs ↗pdf ↗

We consider compact convex hypersurfaces contracting by functions of their curvature. Under the mean curvature flow, uniformly convex smooth initial hypersurfaces evolve to remain smooth and uniformly convex, and contract to points after finite time. The same holds if the initial data is only weakly convex or non-smoot…

2011-04-05abs ↗pdf ↗

New findings show Bregman proximal algorithms can get stuck near non-stationary points.

problem Bregman proximal algorithms can get stuck near non-stationary points, misleadingly suggesting convergence.
method Analysis of Bregman proximal algorithms and their behavior near non-stationary points.
result Bregman proximal algorithms can get stuck near spurious stationary points, even in convex problems.

A limit point p of a discrete group of Mobius transformations acting on S^n is called a concentration point if for any sufficiently small connected open neighborhood U of p, the set of translates of U contains a local basis for the topology of S^n at p. For the case of Fuchsian groups (n = 1), every concentration point…

1998-06-23abs ↗pdf ↗

The problem of clustering noisy and incompletely observed high-dimensional data points into a union of low-dimensional subspaces and a set of outliers is considered. The number of subspaces, their dimensions, and their orientations are assumed unknown. We propose a simple low-complexity subspace clustering algorithm, w…

2013-07-18abs ↗pdf ↗

The paper disproves a conjecture about 3D manifolds using even lattice points.

problem Thurston's Euler class one conjecture for fillable contact structures.
method Analyzing finite covers of hyperbolic 3-manifolds and properties of their dual Thurston norm unit balls.
result Found counter-examples to the conjecture using even lattice points on boundary.

New algorithm finds approximate stationary points in non-convex optimization.

problem Finding approximate stationary points in non-convex stochastic optimization.
method Design of an algorithm using O(ε3)O(ε^{-3}) stochastic gradient and Hessian-vector products.
result Optimal rate of O(ε3)O(ε^{-3}) for finding εε-approximate stationary points, matching lower bounds.

Let f:VnMmf:V^n\looparrowright M^m be a smooth generic immersion. Then the set of points, that have at least kk preimages is an image of a (non-generic) immersion. If the manifolds VnV^n and MmM^m are oriented and mnm-n is even, then the manifold of kk-fold points is also oriented. In this paper we compute the oriented b…

2000-08-07abs ↗pdf ↗

Study bounds and asymptotic behavior of largest purely non-free actions on compact Riemann surfaces.

problem Understanding the largest purely non-free actions on compact Riemann surfaces.
method Analyzing continuous actions of finite groups on closed orientable surfaces, proving bounds and asymptotic behavior.
result The largest order of a purely non-free action on a surface of even genus is bounded below by 8g and sharp for infinitely many even g.

Encoder-decoder GANs architectures (e.g., BiGAN and ALI) seek to add an inference mechanism to the GANs setup, consisting of a small encoder deep net that maps data-points to their succinct encodings. The intuition is that being forced to train an encoder alongside the usual generator forces the system to learn meaning…

2017-11-07abs ↗pdf ↗

The study calculates the growth rate of reciprocal hyperbolic elements in Hecke groups.

problem Counting reciprocal hyperbolic elements in Hecke groups.
method Analyzes conjugacy classes of hyperbolic elements associated with reciprocal geodesics.
result Determines the asymptotic growth rate and limiting constant of primitive conjugacy classes of reciprocal hyperbolic elements.

Proposes a new adversarial model to avoid accuracy vs. adversarial accuracy tradeoff.

problem Inherent tradeoff between accuracy and adversarial accuracy in existing adversarial robustness definitions.
method Introduces Voronoi-epsilon adversary that balances perturbation constraints.
result Voronoi-epsilon adversary avoids accuracy vs. adversarial accuracy tradeoff even with large εε.

This is a survey on the construction of a canonical or "octonionic Kähler" 8-form, representing one of the generators of the cohomology of the four Cayley-Rosenfeld projective planes. The construction, in terms of the associated even Clifford structures, draws a parallel with that of the quaternion Kähler 4-form. We po…

2016-09-22abs ↗pdf ↗

Study on the parity of fold map singular points, showing non-invariance for odd-dimensional manifolds.

problem Parity of connected components of fold map singular points for odd-dimensional manifolds.
method Constructive proofs using open book decompositions, round fold maps, and allowable moves.
result Parity of connected components is not a homotopy invariant for odd-dimensional manifolds.

Paper develops a method to predict spatial point processes with guarantees.

problem Predicting the number of events in space with uncertainty.
method Regularized method to learn spatial models with out-of-sample guarantees.
result Method provides valid prediction intervals even when model is misspecified.

The importance of training robust neural network grows as 3D data is increasingly utilized in deep learning for vision tasks in robotics, drone control, and autonomous driving. One commonly used 3D data type is 3D point clouds, which describe shape information. We examine the problem of creating robust models from the …

2019-08-16abs ↗pdf ↗

The area renormalization procedure gives an invariant of even-dimensional closed submanifolds in a conformal manifold, which we call the Graham-Witten energy, and it is a generalization of the classical Willmore energy. In this paper, we obtain an explicit formula for the second variation of this energy at minimal subm…

2018-07-17abs ↗pdf ↗

A method for estimating the median of gradients in stochastic optimization.

problem Robust gradient estimation in stochastic optimization for various applications.
method Stochastic Proximal Point Method for median gradient estimation.
result The proposed method can converge even under heavy-tailed, state-dependent noise.

The paper tackles finding stationary points in stochastic convex optimization problems.

problem Finding stationary points for stochastic convex optimization problems.
method The approach relies on dimension theory to decompose the graph of the subdifferential of a convex function, showing how stochastic sampling preserves 'pieces' of these graphs, and allowing effective application of proximal-point-like methods.
result The paper provides convergence guarantees for finding stationary points in stochastic convex optimization problems.

Study on critical faces convergence in a Poisson point process.

problem Convergence of point processes associated with critical faces in a Čech filtration.
method Established convergence in M0\mathcal M_0-topology for critical faces above vanishing threshold.
result Obtained limit theorems for positive and negative critical faces.

In this short note, we give a sufficient condition for almost smooth compact metric measure spaces to satisfy the Bakry-Émery condition BE(K,N)BE (K, N). The sufficient condition is satisfied for the glued space of any two (not necessary same dimensional) closed pointed Riemannian manifolds at their base points. This tells …

2018-04-19abs ↗pdf ↗

We introduce the warping crossing polynomial of an oriented knot diagram by using the warping degrees of crossing points of the diagram. Given a closed transversely intersected plane curve, we consider oriented knot diagrams obtained from the plane curve as states to take the sum of the warping crossing polynomials for…

2011-12-08abs ↗pdf ↗

We construct equivariant Khovanov spectra for periodic links, using the Burnside functor construction introduced by Lawson, Lipshitz, and Sarkar. By identifying the fixed-point sets, we obtain rank inequalities for odd and even Khovanov homologies, and their annular filtrations, for prime-periodic links in S3S^3.

2018-10-10abs ↗pdf ↗