Direct method finds Yang-Mills connections for SO(3) bundles.
arXiv research
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For Finsler metrics (no reversibility assumed) on closed orientable surfaces of genus greater than one, we study the dynamics of minimal rays and minimal geodesics in the universal cover. We prove in particular, that for almost all asymptotic directions the minimal rays with these directions laminate the universal cove…
We show that directed minimal cones in (n+1)-dimensional Euclidean space which have at most one singularity are - besides the trivial cases: empty set, whole space - half spaces. Using blow-up techniques, this result can be used to get C^{1,lambda}-regularity for the measure-theoretic boundary of almost minimal Cacciop…
In this paper we consider the problem of reconstructing a curve that is partially hidden or corrupted by minimizing the functional , depending both on length and curvature . We fix starting and ending points as well as initial and final directions. For this functional we discuss the problem o…
Polyak proved that the set is a minimal generating set of oriented Reidemeister moves. One may distinguish between forward and backward moves, obtaining different types of moves, which we call directed oriented Reidemeister moves. In this article we prove that the set of $…
Stochastic gradient descent outperforms traditional force-directed methods.
DLM for BNNs fails to improve over ELBO optimization.
We construct 1-parameter families of non-periodic embedded minimal surfaces of infinite genus in , where denotes a flat 2-tori. Each of our families converges to a foliation of by . These surfaces then lift to minimal surfaces in that are periodic in hori…
Gradient descent implicitly follows regularization for general losses.
We consider any Finsler metric on a closed, orientable surface of genus greater than one. H. M. Morse proved that we can associate an asymptotic direction to minimal rays in the universal cover (in the Poincaré disc: a point on the unit circle). We prove here that, if two minimal rays have a common asymptotic direction…
The Mittag-Leffler theorem is extended to meromorphic curves and minimal surfaces.
This work improves structured prediction by learning the balance between signal and random noise.
We give a simple, direct proof of the easy fact about the Weierstrass Representation, namely, that it always gives a minimal surface. Most presentations include the much harder converse that every simply connected minimal surface is given by the Weierstrass Representation.
A new pruning method finds sparse minimizers in flat regions of deep neural networks.
Reparameterization of variational auto-encoders with continuous random variables is an effective method for reducing the variance of their gradient estimates. In the discrete case, one can perform reparametrization using the Gumbel-Max trick, but the resulting objective relies on an operation and is non-dif…
The paper analyzes discrete approximations to minimize curve length in Euclidean space.
In this note, we focus on smooth nonconvex optimization problems that obey: (1) all local minimizers are also global; and (2) around any saddle point or local maximizer, the objective has a negative directional curvature. Concrete applications such as dictionary learning, generalized phase retrieval, and orthogonal ten…
A new principle minimizes residual and introduces momentum to improve PDE solution dynamics.
The paper improves sparse Gaussian processes by optimizing predictive loss.
Researchers define and prove existence of minimizers for generalized Willmore functionals.
In this paper we investigate the strict convexity and the differentiability properties of the stable norm, which corresponds to the homogenized surface tension for a periodic perimeter homogenization problem (in a regular and uniformly elliptic case). We prove that it is always differentiable in totally irrational dire…
New Teichmüller geodesic rays found with unique foliations.
We prove a new logarithmic epiperimetric inequality for multiplicity-one stationary cones with isolated singularity by flowing in the radial direction any given trace along appropriately chosen directions. In contrast to previous epiperimetric inequalities for minimal surfaces (e.g. those of Reifenberg, Taylor and Whit…
In the present paper we classify all surfaces in $\E^3$ with a canonical principal direction. Examples of these type of surfaces are constructed. We prove that the only minimal surface with a canonical principal direction in the Euclidean space is the catenoid.
Let be an open Riemann surface. In this paper we prove that every continuous function , , defined on a divergent Jordan arc can be approximated in the Carleman sense by conformal minimal immersions; thus providing a new generalization of Carleman's theor…
We propose a graphical model for representing networks of stochastic processes, the minimal generative model graph. It is based on reduced factorizations of the joint distribution over time. We show that under appropriate conditions, it is unique and consistent with another type of graphical model, the directed informa…
In this paper we characterize and classify surfaces in which have a canonical principal direction. Here denotes the hyperbolic plane. We study some geometric properties such as minimality and flatness. Some examples are given to complete the study.
Deep networks converge in direction, with implications for predictions and margins.
Direct proof shows adaptive gradient descent converges near-linearly for convex functions.
Simplified presentation of symplectic fillings of lens spaces.
The study examines biharmonic hypersurfaces in Sasakian space forms.
In this paper we develop a Morse theory for the uniform energy. We use the one-sided directional derivative of the distance function to study the minimizing properties of variations through closed geodesics. This derivative is then used to define a one-sided directional derivative for the uniform energy which allows us…
GD at EoS edge minimizes logistic loss without monotonic convergence.
Given a warped product of the real line with a Riemannian manifold of arbitrary dimension, we classify the hypersurfaces whose tangent spaces make a constant angle with the vector field tangent to the real direction. We show that this is a natural setting in which to extend previous results in this direction made by se…
Optimal flat ribbons can be created from nonplanar curves with minimal energy.
This is a very brief report on recent developments on the Dirichlet problem for the minimal surface system and minimal cones in Euclidean spaces. We shall mainly focus on two directions: (1) Further systematic developments after Lawson-Osserman's paper \cite{l-o} on the Dirichlet problem for minimal graphs of high codi…
A triangulated piecewise-linear minimal surface in Euclidean 3-space defined using a variational characterization is critical for area amongst all continuous piecewise-linear variations with compact support that preserve the simplicial structure. We explicitly construct examples of such surfaces that are embedded and a…
Dimension reduction of multivariate data supervised by auxiliary information is considered. A series of basis for dimension reduction is obtained as minimizers of a novel criterion. The proposed method is akin to continuum regression, and the resulting basis is called continuum directions. With a presence of binary sup…
We prove a version of the classical Runge and Mergelyan uniform approximation theorems for non-orientable minimal surfaces in Euclidean 3-space R3. Then, we obtain some geometric applications. Among them, we emphasize the following ones: 1. A Gunning-Narasimhan type theorem for non-orientable conformal surfaces. 2. An …
Self-directed learners can minimize mistakes in online classification.
Minimal surfaces in spheres are classified based on a Ricci-like condition.
In this paper, we consider the problem of minimizing the sum of two convex functions subject to linear linking constraints. The classical alternating direction type methods usually assume that the two convex functions have relatively easy proximal mappings. However, many problems arising from statistics, image processi…
New stochastic gradient descent with random search directions improves efficiency and convergence.
SAM optimizes deep networks by oscillating between sides of the minimum.
WSFN overcomes saddle points for non-convex functionals in Wasserstein space.
We propose a novel node embedding of directed graphs to statistical manifolds, which is based on a global minimization of pairwise relative entropy and graph geodesics in a non-linear way. Each node is encoded with a probability density function over a measurable space. Furthermore, we analyze the connection between th…
Minimal networks minimize length and mass in certain configurations.
An interesting problem in classical differential geometry is to find methods to prove that two surfaces defined by different charts actually coincide up to position in space. In a previous paper we proposed a method in this direction for minimal surfaces. Here we explain not only how this method works but also how we c…