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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.

168,742 papers · 148 categories

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14274154 · Mar 202619922001200920172026
48 results for Colding's volume

Study minimal surfaces in complex hyperbolic space, linking entropy and volume.

problem Characterize minimal submanifolds in complex hyperbolic space.
method Analyze asymptotic regularity and introduce Colding-Minicozzi entropy and CR-volume.
result Establish a connection between Colding-Minicozzi entropy and CR-volume.

Proves effective linear volume growth for 3-manifolds with positive scalar curvature.

problem Volume growth of three-manifolds with positive scalar curvature.
method Utilizes the technique of μ-bubbles and almost-splitting theorem.
result Proves effective linear volume growth for 3-manifolds with non-negative Ricci curvature and uniformly positive scalar curvature.

In this paper, we show an optimal volume growth for self-shrinkers, and estimate a lower bound of the first eigenvalue of L\mathcal{L} operator on self-shrinkers, inspired by the first eigenvalue conjecture on minimal hypersurfaces in the unit sphere by Yau \cite{SY}. By the eigenvalue estimates, we can prove a compac…

2011-01-07abs ↗pdf ↗

Using the monotonicity formulas of Colding and Minicozzi, we prove that on any complete, non-parabolic Riemannian manifold (M3,g)(M^3, g) with non-negative Ricci curvature, the asymptotic weighted scaling invariant integral of scalar curvature has an explicit bound in form of asymptotic volume ratio.

2019-02-24abs ↗pdf ↗

Recently, Sogge-Zelditch and Colding-Minicozzi gave new power law lower bounds on the size of the nodal sets of eigenfunctions. The purpose of this short note is to point out a third method to obtain a power law lower bound on the volume of the nodal sets. Our method is based on the Donnelly-Fefferman growth bound for …

2010-10-21abs ↗pdf ↗

Kahler manifolds with specific curvature properties are close to projective spaces.

problem Understanding the shape of Kahler manifolds with maximal volume.
method Combining results on holomorphic rigidity and structure of almost Einstein manifolds.
result Kahler manifolds with lower Ricci bounds and almost maximal volume are close to projective spaces.

NetDP predicts loan defaults using network data, addressing cold-start issues.

problem Cold-start problem in default prediction for new users.
method Combines unsupervised and supervised network representations, using parameter-server for scalability.
result Effectiveness in cold-start problem, especially for new users.

We study ancient solutions of polynomial growth to heat equations on graphs, and extend Colding and Minicozzi's theorem [CM19] on manifolds to graphs: For a graph of polynomial volume growth, the dimension of the space of ancient solutions of polynomial growth is bounded by the product of the growth degree and the dime…

2019-03-06abs ↗pdf ↗

Sharp gradient estimates for positive Ricci curvature manifolds.

problem Understanding geometric properties of manifolds with positive Ricci curvature.
method Proving sharp gradient estimates and monotonicity formulae.
result Sharp gradient estimates and monotonicity formulae for positive Ricci curvature manifolds.

Uniqueness of asymptotic limits for Ricci-flat manifolds with linear volume growth is proven.

problem Proving uniqueness of asymptotic limits for noncollapsed Ricci flat manifolds with linear volume growth.
method Relating uniqueness to the existence of a harmonic function asymptotic to a Busemann function, proving uniqueness via a monotone quantity.
result Proves uniqueness of the asymptotic limit and establishes a polynomial convergence rate.

Let MM be an nn-dimensional complete Riemannian manifold with Ricci curvature n1\ge n-1. In \cite{colding1, colding2}, Tobias Colding, by developing some new techniques, proved that the following three condtions: 1) dGH(M,Sn)0d_{GH}(M, S^n)\to 0; 2) the volume of MM Vol(M)Vol(Sn){\text{Vol}}(M)\to{\text{Vol}}(S^n); 3) the radius of $M…

2014-01-21abs ↗pdf ↗

Let (M,gˉ,efdμ)(M,\bar{g}, e^{-f}dμ) be a complete metric measure space with Bakry-Émery Ricci curvature bounded below by a positive constant. We prove that, in MM, there is no complete two-sided LfL_f-stable immersed ff-minimal hypersurface with finite weighted volume. Further, if MM is a 3-manifold, we prove a smooth compa…

2012-10-30abs ↗pdf ↗

We prove that a metric measure space equipped with a Dirichlet form admitting an Euclidean heat kernel is necessarily isometric to the Euclidean space. This helps us providing an alternative proof of Colding's celebrated almost rigidity volume theorem via a quantitative version of our main result. We also discuss the c…

2019-12-23abs ↗pdf ↗

We generalize a classification result for self-shrinkers of the mean curvature flow with nonnegative mean curvature, which was obtained by T. Colding and W. Minicozzi, replacing the assumption on polynomial volume growth with a weighted L2L^2 condition on the norm of the second fundamental form. Our approach adopt the …

2012-12-17abs ↗pdf ↗

Under the definition of Ricci curvature bounded below for Alexandrov spaces introduced by Zhang-Zhu, we generalize a result by Colding that an n dimentional manifold with Ricci curvature greater or equal to n minus 1 and volume close to that of the unit n sphere is close (in the Gromov-Hausdorff distance) to the sphere…

2015-03-03abs ↗pdf ↗

Study area-minimizing hypersurfaces in manifolds with controlled curvature.

problem Characterize area-minimizing hypersurfaces in manifolds with Ricci curvature bounds.
method Apply Cheeger-Colding theory and blow-up techniques to analyze hypersurfaces.
result Proves continuity of volume functions and existence of area-minimizing limits.

We study ancient solutions of polynomial growth to both continuous-time and discrete-time heat equations on graphs with unbounded Laplacians. We generalize Colding and Minicozzi's theorem [CM19] on manifolds, and the result [Hua19] on graphs with normalized Laplacians to the setting of graphs with unbounded Laplacians:…

2019-10-07abs ↗pdf ↗

It is shown that mm disjoint sets with fixed Gaussian volumes that partition Rn\mathbb{R}^{n} with minimum Gaussian surface area must be (m1)(m-1)-dimensional. This follows from a second variation argument using infinitesimal translations. The special case m=3m=3 proves the Double Bubble problem for the Gaussian measure,…

2018-05-25abs ↗pdf ↗

We show that a complete Riemannian manifold of dimension nn with $\Ric\geq n{-}1$ and its nn-st eigenvalue close to nn is both Gromov-Hausdorff close and diffeomorphic to the standard sphere. This extends, in an optimal way, a result of P. Petersen. We also show that a manifold with $\Ric\geq n{-}1$ and volume close…

2005-05-19abs ↗pdf ↗

Bayesian neural networks with data augmentation show a persistent cold posterior effect.

problem Understanding the cold posterior effect in Bayesian neural networks with data augmentation.
method Developed principled Bayesian neural networks using data augmentation, providing exact likelihoods and tight bounds.
result The cold posterior effect persists even in models incorporating data augmentation, suggesting it's not an artifact.

Playlist recommendation involves producing a set of songs that a user might enjoy. We investigate this problem in three cold-start scenarios: (i) cold playlists, where we recommend songs to form new personalised playlists for an existing user; (ii) cold users, where we recommend songs to form new playlists for a new us…

2019-01-18abs ↗pdf ↗

The paper investigates quantitative rigidity using Colding's monotonicity formulas for Ricci curvature.

problem Quantifying rigidity in manifolds with nonnegative Ricci curvature.
method Investigates pinching of Colding's monotone functionals and constructs kk-splitting functions.
result Quantitative control of splitting functions by pinching at independent points controls the distance to the nearest cone.

Graph neural networks improve cold start for new items in recommender systems.

problem Cold start problem for new items in recommender systems.
method Item hierarchy graphs and bespoke graph neural network architecture.
result Our method achieves better forecasting quality than state-of-the-art with comparable computational time.

The item cold-start problem seriously limits the recommendation performance of Collaborative Filtering (CF) methods when new items have either none or very little interactions. To solve this issue, many modern Internet applications propose to predict a new item's interaction from the possessing contents. However, it is…

2019-09-10abs ↗pdf ↗

Researchers extend monotonicity formulas for harmonic functions in RCD(0,N) spaces.

problem Generalizing monotonicity formulas for harmonic functions in mRCD(0,N){ m RCD}(0,N) spaces.
method New estimates for harmonic functions and a functional version of the outer volume cone theorem.
result Proven rigidity and almost rigidity statements for harmonic functions in mRCD(0,N){ m RCD}(0,N) spaces.

Since Li and Yau obtained the gradient estimate for the heat equation, related estimates have been extensively studied. With additional curvature assumptions, matrix estimates that generalize such estimates have been discovered for various time-dependent settings, including the heat equation on a Kähler manifold, Ricci…

2017-04-25abs ↗pdf ↗

Let XX be the Gromov-Hausdorff limit of a sequence of pointed complete Kähler manifolds (Min,pi)(M^n_i, p_i) satisfying Ric(Mi)(n1)Ric(M_i)\geq -(n-1) and the volume is noncollapsed. We prove that, there exists a Lie group isomorphic to R\mathbb{R}, acting isometrically, on the tangent cone at each point of XX. Moreover, the actio…

2014-09-15abs ↗pdf ↗

The cold posterior effect is explored through PAC-Bayes bounds for small sample sizes.

problem The cold posterior effect in approximate Bayesian inference for small datasets.
method Investigation through PAC-Bayes generalization bounds, focusing on temperature parameter λ.
result The temperature parameter λ in PAC-Bayes bounds captures the cold posterior effect.

Cold posteriors in BNNs harm performance, likely due to incorrect likelihood.

problem Cold posteriors in Bayesian neural networks degrade performance.
method Developed a generative model explaining cold posteriors and matched it to the tempered likelihoods.
result Cold posteriors are a result of using the wrong likelihood for image classification datasets.