We prove that a strictly stable constant-mean-curvature hypersurface in a smooth manifold of dimension less than or equal to 7 is uniquely homologically area minimizing for fixed volume in a small L^1 neighborhood.
The minimal number of critical points is studied for smooth functions on closed manifolds.
problem Determining the minimal number of critical points for smooth functions on closed manifolds.
method Investigates cylindrical ball neighborhoods and exotic critical points, proving the conjecture for certain types of critical points.
result The minimal number of critical points is the same for smooth functions without exotic critical points on closed manifolds of dimension at least 6.
This paper studies the structure of a specific neighborhood in minimal 2-crossing charts.
problem Understanding the structure of a minimal 2-crossing chart with specific neighborhoods.
method Analyzes the neighborhoods of Γα∪Γβ and proposes a normal form for 2-crossing minimal n-charts. result Proposes a normal form for 2-crossing minimal n-charts. The study proves properties of geodesics and tubular neighborhoods on Finsler manifolds.
problem Existence and properties of geodesics and tubular neighborhoods on Finsler manifolds.
method Analytical proof of properties of geodesics and tubular neighborhoods.
result Existence of tubular neighborhoods and minimization of orthogonal geodesics.
The study proves local rigidity of minimal 2-spheres in electrovacuum spacetimes.
problem Proving local rigidity of minimal 2-spheres in electrovacuum spacetimes under certain conditions.
method Analyzing electrovacuum spacetimes and using constraints on charged Hawking mass and area minimization.
result Local rigidity of minimal 2-spheres in electrovacuum spacetimes, with isometric neighborhoods to specific spacetimes.
In this paper, we show that a complete embedded minimal surface in $\Real^3$ with finite topology and one end is conformal to a once-punctured compact Riemann surface. Moreover, using the conformality and embeddedness, we examine the Weierstrass data and conclude that every such surface has Weierstrass data asymptotic …
Study shows TAP free energy minimization provides better posterior inference in high-dimensional linear models.
problem Deviation from true posterior mean and underestimation of posterior uncertainty in variational inference.
method Minimization of TAP free energy in a high-dimensional asymptotic framework, showing geometric and statistical properties.
result Local minimizer of TAP free energy provides consistent estimate of posterior marginals and correctly calibrated posterior inference.
We use the minimal coupling procedure of Sternberg and Weinstein and our pseudo-symplectic capacity theory to prove that every closed symplectic submanifold in any symplectic manifold has an open neighborhood with finite (π1-sensitive) Hofer-Zehnder symplectic capacity. Consequently, the Weinstein conjecture holds n…
WSFN overcomes saddle points for non-convex functionals in Wasserstein space.
problem Minimizing non-convex functionals over the Wasserstein space with saddle point avoidance.
method WSFN is a second-order method that preconditions the Wasserstein gradient to avoid saddle points.
result WSFN escapes saddle regions and reaches a global minimizer in polynomial time.
Minimal surfaces' boundary points are always smooth.
problem Boundary regularity of minimal surfaces.
method Proving all boundary points are regular submanifolds.
result Boundary points of minimal surfaces are regular.
Minimal hypersurfaces with cylindrical tangent cones constructed and analyzed.
problem Constructing minimal hypersurfaces with specific geometric properties.
method Constructing minimal hypersurfaces with cylindrical tangent cones and proving unique continuation results.
result Existence and properties of minimal hypersurfaces with cylindrical tangent cones.
Local minimality proven for stable free-boundary minimal hypersurfaces.
problem Proving local minimality for stable free-boundary minimal hypersurfaces.
method Using relative current setting and strict stability, proving local minimality among relative cycles.
result Local minimality of stable free-boundary minimal hypersurfaces in a small tubular neighborhood.
We prove a descriptive theorem on the extrinsic geometry of an embedded minimal surface of injectivity radius zero in a homogeneously regular Riemannian three-manifold, in a certain small intrinsic neighborhood of a point of almost-minimal injectivity radius. This structure theorem includes a limit object which we call…
We construct a branched center manifold in a neighborhood of a singular point of a 2-dimensional integral current which is almost minimizing in a suitable sense. Our construction is the first half of an argument which shows the discreteness of the singular set for the following three classes of 2-dimensional curren…
Proves minimal Heegaard surfaces properties in 3-manifolds.
problem Existence and properties of minimal Heegaard surfaces.
method Analyzes strongly irreducible Heegaard surfaces in 3-manifolds.
result Confirms conjecture about minimal surfaces' isotopy.
Minimal hypersurfaces in Euclidean space are restricted to planes if their Gauss maps avoid a half-equator.
problem Characterizing minimal hypersurfaces in Euclidean space.
method Using the Gauss map to restrict the image of minimal hypersurfaces.
result Minimal hypersurfaces must be planes if their Gauss maps avoid a half-equator.
We show that there exists a metric with positive scalar curvature on S2xS1 and a sequence of embedded minimal cylinders that converges to a minimal lamination that, in a neighborhood of a strictly stable 2-sphere, is smooth except at two helicoid-like singularities on the 2-sphere. The construction is inspired by a rec…
In this paper Hamiltonian system of time dependent periodic Newton equations is studied. It is shown that for dimensions 3 and higher the following rigidity results holds true: If all the orbits in a neighborhood of infinity are action minimizing then the potential must be constant. This gives a generalization of the…
The paper characterizes neural network landscapes for gradient dominance and regularity.
problem Understanding the landscape of neural network loss functions.
method Characterization of gradient dominance and regularity conditions for neural networks.
result Explicit characterization of global minimizers and landscape properties for different neural network types.
In this paper we prove the existence of rational homology balls smoothly embedded in regular neighborhoods of certain linear chains of smooth 2-spheres by using techniques from minimal model program for 3-dimensional complex algebraic variety.
Proves unique continuation for area minimizing currents.
problem Ensuring area minimizing currents match minimal surfaces.
method Analyzes infinite order contact between currents and minimal surfaces.
result Currents and minimal surfaces coincide in a neighborhood.
Miyaoka-Yau inequality proven for smooth minimal models.
problem Proving the Miyaoka-Yau inequality for smooth minimal models.
method Existence of cscK metrics in a neighborhood of the canonical class.
result Miyaoka-Yau inequality holds for compact Kähler manifolds with nef canonical bundle.
Study rigidity of minimal disks in specific 3-manifolds.
problem Rigidity of free boundary minimal disks in mean convex three-manifolds.
method Assuming strict stability, prove isometric neighborhoods using modified Hawking mass.
result Prove rigidity of minimal disks in specific 3-manifolds.
SAM minimizes loss sharpness, improving adversarial transferability.
problem Improving adversarial transferability of deep neural networks.
method Evaluating surrogate models trained with seven minimizers, focusing on loss sharpness and flat neighborhoods.
result SAM minimizes loss sharpness, leading to better adversarial transferability.
Constructs cmc doublings of minimal surfaces via min-max theory.
problem Construct cmc doublings of minimal surfaces.
method Uses min-max theory and catenoid estimate.
result Constructs ε-cmc doublings of Σ for small ε > 0.
New proof shows minimal submanifolds of sphere are totally geodesic.
problem Characterize minimal submanifolds of spheres.
method Develops a new proof strategy.
result Obtains analogous result for codimension 2 minimal submanifolds.
Given a compact closed subset M of a line segment in R3, we construct a sequence of minimal surfaces Σk embedded in a neighborhood C of the line segment that converge smoothly to a limit lamination of C away from M. Moreover, the curvature of this sequence blows up precisely on M, and the limit…
Study confirms conjecture about Kähler metrics on smooth minimal models.
problem Behavior of constant scalar curvature Kähler metrics on smooth minimal models.
method Analysis of metrics in a neighborhood of the canonical class.
result Convergence to singular Kähler Einstein metric in the canonical class.
Uniqueness and stability of minimal submanifolds proved.
problem Uniqueness and stability of minimal submanifolds.
method Proved a strong stability condition on minimal submanifolds.
result Existence and convergence of mean curvature flow for minimal submanifolds.
Survey on minimal rational curves and their geometric structures.
problem Germ-equivalence problem of minimal rational curves on uniruled projective manifolds.
method Analysis of isotrivial families of projective varieties and G-structures.
result Natural G-structure on Zariski-open subset of uniruled projective manifolds.
We show the regularity of, and derive a-priori estimates for (weakly) harmonic maps from a Riemannian manifold into a Euclidean sphere under the assumption that the image avoids some neighborhood of a half-equator. The proofs combine constructions of strictly convex functions and the regularity theory of quasi-linear e…
Proposes NRS to find flat minima in deep neural networks.
problem Finding optimal solutions in deep neural networks with overparameterization.
method NRS leverages the concept of flat minima and uses Kullback-Leibler divergence to regularize the neighborhood region in weight space.
result NRS drives optimizers towards flat minima, improving generalization ability across various model architectures.
Characterizes minimizing curves in Riemannian manifolds.
problem Finding optimal paths in curved spaces.
method Characterization of prox-regular sets and tangent cones.
result Necessary condition for minimizing curves in prox-regular sets.
Estimates intrinsic dimensionality from minimal neighbor distances.
problem Analyzing high-dimensional datasets with complex manifolds.
method Minimal neighborhood information approach to estimate intrinsic dimensionality.
result The method provides consistent measures of intrinsic dimensionality.
Minimal networks minimize length and mass in certain configurations.
problem Finding minimal networks that minimize length and mass.
method Global and local calibrations to prove minimization properties.
result Minimal networks minimize mass and interfaces in partitions.
Meta-Neighborhoods adapts predictions based on input neighborhoods.
problem Adaptive prediction based on input neighborhoods for AI.
method Semi-parametric method with induced neighborhoods and meta-learning.
result Meta-Neighborhoods more accurately represents predictive distributions.
Mathematical analysis of SNE and t-SNE for dimension reduction.
problem Optimal mapping of high-dimensional data to low dimensions.
method Gradient flow of relative entropy to minimize the distance between points.
result The diameter of the evolving sets remains bounded for SNE but may blow up for t-SNE.
New proof shows how to identify DAGs with weakly increasing errors.
problem Identifying the true DAG in models with weakly increasing error variances.
method Minimum-trace DAG method and hill climbing algorithm with R2R neighborhood.
result Hill climbing algorithm without strict local optima under weakly increasing error variances.
We derive spectral sequences for the intersection homology of stratified fibrations and approximate tubular neighborhoods in manifold stratified spaces. These neighborhoods include regular neighborhoods in PL stratified spaces.
NNK algorithm improves neighborhood and graph construction for machine learning.
problem Ad hoc selection of k and ε parameters in kNN and ε-neighborhood methods.
method NNK algorithm for better sparse signal approximation.
result NNK leads to superior performance in local neighborhood and graph-based machine learning tasks.
In continuing the study of harmonic mapping from 2-dimensional Riemannian simplicial complexes in order to construct minimal surfaces with singularity, we obtain an a-priori regularity result concerning the real analyticity of the free boundary curve. The free boundary is the singular set along which three disk-type mi…
Existence proof for two families of triply periodic minimal surfaces.
problem Proving the existence of two families of minimal surfaces.
method Extending a technique to non-rectangular branched tori.
result Existence of the tG and rGL families of triply periodic minimal surfaces.
Let (M,g) be a compact, connected riemannian manifold that is homogeneous, i.e. each pair of points p,q in M have isometric neighborhoods. This paper is a first step towards an understanding of the extent to which it is true that for each "generic" initial condition f0, the solution to the Heat Equation is such that fo…
Private KL distribution estimation improved with instance-optimality.
problem Minimizing KL divergence between true and estimated distributions.
method Construct minimax optimal private estimators, then focus on instance-optimality.
result Achieved instance-optimality up to constant factors for KL estimation.
This research improves classification performance by learning a distance metric from balanced data.
problem Data imbalance in learning methods.
method Extracts a low-dimensional manifold, learns local neighborhood relationships, and optimizes distance metric.
result The proposed method outperforms other approaches, especially in imbalanced datasets.
Let A be a line arrangement in the complex projective plane CP2. We define and describe the inclusion map of the boundary manifold --the boundary of a close regular neighborhood of A-- in the exterior of the arrangement. We obtain two explicit descriptions of the map induced on the fundamental groups. These computation…
In this paper we prove two theorems. The first one is a structure result that describes the extrinsic geometry of an embedded surface with constant mean curvature (possibly zero) in a homogeneously regular Riemannian three-manifold, in any small neighborhood of a point of large almost-maximal curvature. We next apply t…
Quantized Stochastic Primal-Dual Methods for Distributed Optimization
problem Distributed optimization with stochastic gradients and finite-bit communication
method q-PDGD, a quantized stochastic primal-dual method
result Linear contraction to an explicit neighborhood under RSI, O(1/k) convergence under PL inequality