Uniform RC-positivity results for direct image bundles.
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The paper extends Schwarz's lemma to RC-positivity and complex manifolds.
In this paper, we prove that if a compact Kähler manifold has a smooth Hermitian metric such that is uniformly RC-positive, then is projective and rationally connected. Conversely, we show that, if a projective manifold is rationally connected, then the tautological line bundle $\mathscr{O}_{T…
In this paper, we introduce a concept of RC-positivity for Hermitian holomorphic vector bundles and prove that, if is an RC-positive vector bundle over a compact complex manifold , then for any vector bundle , there exists a positive integer such that $$H^0(X,\mathrm{Sym}^{\otimes \ell}E^*\otimes…
In this paper, we show that every harmonic map from a compact Kähler manifold with uniformly RC-positive curvature to a Riemannian manifold with non-positive complex sectional curvature is constant. In particular, there is no non-constant harmonic map from a compact Kähler manifold with positive holomorphic sectional c…
Let and be two compact complex manifolds. We show that if the tautological line bundle is not pseudo-effective and is nef, then there is no non-constant holomorphic map from to . In particular, we prove that any holomorphic map from a compact complex mani…
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Tight geodesics were introduced by Masur-Minsky in [17]. They and their hierarchies have been a powerful tool in the study of the curve complex, mapping class groups, Teichmüller spaces, and hyperbolic 3-manifolds. In the same paper, they showed that there are at least one and at most finitely many tight geodesics betw…
In this paper, we pose several conjectures on structures and images of maximal rationally connected fibrations of smooth projective varieties admitting semi-positive holomorphic sectional curvature. Toward these conjectures, we prove that the canonical bundle of images of such fibrations is not big. Our proof gives a g…
Surveying Ricci flow for weak lower scalar curvature bounds.
Uniform bounds for neural network convergence without strong convexity assumptions.
Study sets limits for detecting a subhypergraph in uniform hypergraphs.
We generalize Roe's index theorem for graded generalized Dirac operators on amenable manifolds to multigraded elliptic uniform pseudodifferential operators. This generalization will follow as a corollary from a local index theorem that is valid on any manifold of bounded geometry. This local formula incorporates the un…
Suppose a sequence of Alexandrov spaces collapses to a space with only weak singularities. Yamaguchi constructed a map called an almost Lipschitz submersion for large . We prove that if has a uniform positive lower bound for the volumes of spaces of directions, which is sufficiently la…
In this paper, we introduce a new energy density function on the projective bundle for a smooth map between Riemannian manifolds We get new Hessian estimates to this energy density and obtain various new…
The existence of \emph{weak conical Kähler-Einstein} metrics along smooth hypersurfaces with angle between and is obtained by studying a smooth continuity method and a \emph{local Moser's iteration} technique. In the case of negative and zero Ricci curvature, the estimate is unobstructed; while in the ca…
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We consider Blackwell approachability, a very powerful and geometric tool in game theory, used for example to design strategies of the uninformed player in repeated games with incomplete information. We extend this theory to "generalized quitting games" , a class of repeated stochastic games in which each player may ha…
Let be an infinite Riemann surface equipped with its conformal hyperbolic metric such that the action of the covering group on is of the first kind-i.e., the surface is equal to its convex core. We first prove that any geodesic lamination on is nowhere dense. Given a fixed geodesic pant…
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Uniform deviation bounds limit the difference between a model's expected loss and its loss on an empirical sample uniformly for all models in a learning problem. As such, they are a critical component to empirical risk minimization. In this paper, we provide a novel framework to obtain uniform deviation bounds for loss…
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An approximation theorem for minimal surfaces by complete minimal surfaces of finite total curvature in is obtained. This Mergelyan type result can be extended to the family of complete minimal surfaces of weak finite total curvature, that is to say, having finite total curvature on proper regions of fin…
Random sampling has become a critical tool in solving massive matrix problems. For linear regression, a small, manageable set of data rows can be randomly selected to approximate a tall, skinny data matrix, improving processing time significantly. For theoretical performance guarantees, each row must be sampled with pr…
Uniform convergence of metrics on surfaces with bounded curvature measures proved.
Fix a translation surface , and consider the measures on coming from averaging the uniform measures on all the saddle connections of length at most . Then as , the weak limit of these measures exists and is equal to the Lebesgue measure on . We also show that any weak limit of a subsequence of …
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The small-ball method was introduced as a way of obtaining a high probability, isomorphic lower bound on the quadratic empirical process, under weak assumptions on the indexing class. The key assumption was that class members satisfy a uniform small-ball estimate: that for given const…
We show uniqueness of classical solutions of the normalised two-dimensional Hamilton-Ricci flow on closed, smooth manifolds for smooth data among solutions satisfying (essentially) only a uniform bound for the Liouville energy and a natural space-time -bound for the time derivative of the solution. The result is s…
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Understanding statistical inference under possibly non-sparse high-dimensional models has gained much interest recently. For a given component of the regression coefficient, we show that the difficulty of the problem depends on the sparsity of the corresponding row of the precision matrix of the covariates, not the spa…
The problem of learning from label proportions (LLP) involves training classifiers with weak labels on bags of instances, rather than strong labels on individual instances. The weak labels only contain the label proportion of each bag. The LLP problem is important for many practical applications that only allow label p…
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Compactness results for hypersurfaces with mean curvature prescribed by an ambient function.