Equivalence found between algorithmic regularization and convex penalization for convex losses.
problem Understanding the relationship between algorithmic regularization and convex penalization.
method Introducing a geometric condition and showing equivalence through optimization paths.
result Optimization paths of iterative algorithms on unregularized problems match those of corresponding penalized problems under certain conditions.
To provide a solid analytic foundation for the module approach to conditional risk measures, this paper establishes a complete random convex analysis over random locally convex modules by simultaneously considering the two kinds of topologies (namely the (ε,λ)--topology and the locally L0-- convex topolo…
Generalizes smoothness conditions for optimization methods.
problem Optimization under non-uniform smoothness conditions.
method Develops a new analysis technique for bounding gradients.
result Obtains convergence rates for gradient descent and Nesterov's method.
Paper investigates curvature problems and existence of solutions.
problem Existence of admissible solutions to curvature problems.
method Investigates curvature problems with prescribed Lp quotient type, proving existence under specific conditions. result Proves existence of admissible solutions without additional conditions.
Defines new operations on random sets in Banach spaces.
problem Assessing multivariate risks in mathematical finance.
method Introduces conditional core and convex hull operations for random sets.
result Generalised conditional expectation is sandwiched between conditional core and convex hull.
The purpose of this paper is to give a selective survey on recent progress in random metric theory and its applications to conditional risk measures. This paper includes eight sections. Section 1 is a longer introduction, which gives a brief introduction to random metric theory, risk measures and conditional risk measu…
The null energy condition is characterized via convexity of entropy in Lorentzian manifolds.
problem Characterizing the null energy condition in Lorentzian manifolds.
method Characterization via convexity of the relative entropy along displacement interpolations on null hypersurfaces.
result The null energy condition is characterized in terms of convexity of the relative entropy.
CNR uses convex optimization to estimate conditional distributions.
problem Estimating uncertainty in predictions and posterior conditional distributions.
method Convex optimization of a posterior defined via non-linear transformations on Gaussians.
result CNR can fit arbitrary conditional distributions, including multimodal and non-symmetric ones.
Paper solves Minkowski problem for non-compact convex sets with asymptotic boundary conditions.
problem Solving Minkowski problem for non-compact convex sets with asymptotic boundary conditions.
method Combining covolume, Hadamard variational formula, and geometric interpretation.
result Solved Minkowski problem for non-compact convex sets under asymptotic conditions.
In the article the necessary and sufficient conditions for a representation of Lipschitz function of two variables as a difference of two convex functions are formulated. An algorithm of this representation is given. The outcome of this algorithm is a sequence of pairs of convex functions that converge uniformly to a p…
Proximal splitting methods solve rank-constrained convex problems locally.
problem Solving optimization problems with rank constraints.
method Proximal splitting algorithms with conditions on rank constraint convex envelopes.
result Proximal splitting methods converge locally to solutions under convex relaxation conditions.
New inequalities for convex curves with multiple geometric factors.
problem Establishing inequalities for convex curves with multiple geometric factors.
method Parametric isoperimetric-type inequalities for closed convex curves with parameter conditions and equality conditions.
result Derived new inequalities and improved versions of existing inequalities.
Paper develops a new local convexity condition for non-isolated minima in non-convex optimization.
problem Lack of theory for non-isolated minima in non-convex optimization.
method Formulates a new local convexity condition and studies SGD convergence under this condition.
result Shows SGD can converge locally under the new condition.
Conditions for exponentiating Lie algebras on complete locally convex spaces are established.
problem Conditions for exponentiating Lie algebras of linear operators on complete locally convex spaces.
method Focus on equicontinuous case, establishing necessary conditions for exponentiation to compact Lie groups.
result Necessary conditions for exponentiation to compact Lie groups are established.
We investigate which jump-diffusion models are convexity preserving. The study of convexity preserving models is motivated by monotonicity results for such models in the volatility and in the jump parameters. We give a necessary condition for convexity to be preserved in several-dimensional jump-diffusion models. This …
A theorem of Tits - Vinberg allows to build an action of a Coxeter group Γ on a properly convex open set Ω of the real projective space, thanks to the data P of a polytope and reflection across its facets. We give sufficient conditions for such action to be of finite covolume, convex-cocompact or geometrically fi…
The paper develops a new approach to conditional risk measures using modular convex analysis.
problem Developing a new method for conditional risk measures.
method Random modular approach to conditional certainty equivalents and niveloids in the conditional L∞-space. result Retrieves a conditional variational formula for optimized certainty equivalents and applies it to the conditional entropic risk measure.
Generalizes rigidity of scalar curvature for convex domains.
problem Rigidity of scalar curvature for convex domains.
method Harmonic spinors on convex domains with boundary conditions constructed by Brendle.
result Rigidity results on comparison of scalar curvature and scaled mean curvature on the boundary for any convex domain.
Strict convexity of graphs with constant mean curvature is proven under certain conditions.
problem Proving strict convexity of graphs with constant mean curvature.
method Analyzing the Dirichlet problem for graphs with normalized constant mean curvature and planar boundary.
result The optimal solvability condition for the mean curvature of the boundary suffices to prove the strict convexity of the graph.
The paper proves a Liouville theorem for special Lagrangian equations with convexity conditions.
problem Proving Liouville theorems for special Lagrangian equations with specific conditions.
method Using Neumann-Poincaré inequality, mean value inequality for superharmonic functions, and geometric measure theory.
result Derives global and interior Hessian estimates for solutions of special Lagrangian equations.
The paper defines conditions for groups acting on convex domains to be relatively hyperbolic.
problem Understanding conditions for groups acting on convex domains to be relatively hyperbolic.
method Analyzing the geometry of the convex domain to determine relative hyperbolicity.
result Established necessary and sufficient conditions for groups to be relatively hyperbolic.
Fundamental gap vanishes for convex domains in hyperbolic space.
problem Behavior of fundamental gap in convex domains in hyperbolic space.
method Proof for Laplace operator with Dirichlet boundary conditions.
result Fundamental gap can be arbitrarily small for domains of any diameter.
We study convexity and monotonicity properties for prices of bonds and bond options when the short rate is modeled by a diffusion process. We provide conditions under which convexity of the price in the short rate is guaranteed. Under these conditions the price is decreasing in the drift and increasing in the volatilit…
Proves rigidity for specific initial data sets under the dominant energy condition.
problem Rigidity of initial data sets with boundary and convex polytopes.
method Solution of boundary value problems for Dirac operators and approximations by manifolds with smooth boundary.
result Proves rigidity for compact smooth spin manifolds and convex polytopes under the dominant energy condition.
Locally Accelerated Conditional Gradients improve convergence rates for smooth convex optimization problems.
problem Achieving optimal convergence rates for smooth convex optimization problems over polytopes.
method Locally Accelerated Conditional Gradients, coupling accelerated steps with conditional gradient steps.
result Achieves optimal accelerated local convergence for smooth strongly convex problems.
Paper extends Green-Osher inequality for convex bodies at dilation position.
problem Extending Green-Osher inequality for specific geometric configurations.
method Analyzes strictly convex bodies at dilation position and derives necessary and sufficient conditions.
result Establishes extended Green-Osher inequality with conditions for equality.
The paper generalizes offset Rademacher complexities to convex and non-convex problems.
problem Improper learning and convexity in statistical learning.
method Generalization of offset Rademacher complexities to convex and non-convex problems.
result The offset complexity provides versatile analytic tools for both convex and non-convex learning.
We define in the space of n by m matrices of rank n, n less or equal than m, the condition Riemannian structure as follows: For a given matrix A the tangent space of A is equipped with the Hermitian inner product obtained by multiplying the usual Frobenius inner product by the inverse of the square of the smallest sing…
We study convex risk measures describing the upper and lower bounds of a good deal bound, which is a subinterval of a no-arbitrage pricing bound. We call such a convex risk measure a good deal valuation and give a set of equivalent conditions for its existence in terms of market. A good deal valuation is characterized …
SGD converges to global minimum for structured non-convex functions.
problem Optimizing non-convex functions using SGD with slow convergence rates.
method Convergence theorems for SGD on structured non-convex functions, including Quasar and PL conditions.
result SGD converges to global minimum for specific non-convex functions under certain conditions.
Solves Christoffel-Minkowski problem for capillary convex bodies in Euclidean half-space.
problem Finding capillary convex bodies with prescribed k-th capillary area measure. method Solving a Hessian-type equation with Robin boundary condition.
result Existence and uniqueness of a smooth solution under natural conditions.
Study convex capillary hypersurfaces with prescribed curvature in a spherical cap.
problem Prescribed curvature problem for convex capillary hypersurfaces.
method Reformulated as Hessian quotient equation with Robin boundary condition.
result Existence of strictly convex capillary hypersurface with prescribed curvature.
Study identifies key differences in convex relaxations for combinatorial penalties.
problem Understanding which structures are preserved by convex relaxations for combinatorial penalties.
method Examined homogeneous and non-homogeneous convex relaxations, introduced lower combinatorial envelope, and proposed adaptive estimator.
result Identified new necessary and sufficient conditions for support recovery in convex monotone regularizers.
The study pinches conditions for constant mean curvature surfaces in convex 3-manifolds.
problem Understanding the topology and geometry of constant mean curvature surfaces with free boundaries in convex 3-manifolds.
method Provided pinching conditions on the traceless second fundamental form to guarantee surface topology.
result The surface is either a disk, annulus, spherical cap, or Delaunay surface under certain conditions.
We study solutions of the mean curvature flow which are defined for all negative curvature times, usually called ancient solutions. We give various conditions ensuring that a closed convex ancient solution is a shrinking sphere. Examples of such conditions are: a uniform pinching condition on the curvatures, a suitable…
Constructs obstructions and deformation principles for positive scalar curvature metrics with mean convex boundaries.
problem Obstructing the existence of positive scalar curvature metrics with mean convex boundaries.
method Atiyah-Patodi-Singer index formula, deformation principle, homotopy equivalences, higher homotopy groups.
result Construction of compact manifolds with nontrivial higher homotopy groups for positive scalar curvature metrics with mean convex boundaries.
Improved subgradient method tackles ill-conditioned composite optimization problems.
problem Slow convergence of subgradient method for composite optimization problems.
method Preconditioned subgradient method with Levenberg-Marquardt approach.
result Linear convergence rate for composite optimization problems under mild conditions.
Compactness proven for manifolds with nonnegative Ricci curvature and uniformly convex boundary.
problem Compactness of manifolds with specific curvature and boundary conditions.
method Monotone quantities constructed from positive proper harmonic functions with Neumann condition.
result Proves compactness of manifolds with nonnegative Ricci curvature and uniformly convex boundary.
Entropy convexity characterizes strong energy condition in spacetimes.
problem Characterizing strong energy condition in nonsmooth spacetimes.
method Lifting fractional powers of Lorentz distance to probability measures and showing geodesic convexity of Boltzmann-Shannon entropy.
result Strong energy condition is equivalent to geodesic convexity of Boltzmann-Shannon entropy.
Paper discusses natural quasiconvexity and its relation to decomposable sums in risk measures.
problem Understanding natural quasiconvexity and its implications in risk measures.
method Relates natural quasiconvexity to decomposable sums, proposes a general treatment of convexity index, and proves equivalence for certain spaces.
result Natural quasiconvexity and convexity are equivalent for conditional risk measures on Lp spaces under mild conditions. We study a notion of convex cocompactness for discrete subgroups of the projective general linear group acting (not necessarily irreducibly) on real projective space, and give various characterizations. A convex cocompact group in this sense need not be word hyperbolic, but we show that it still has some of the good pr…
The study finds conditions for certain surfaces to have a specific type of metric.
problem Understanding the geometry of surfaces with specific metrics.
method Analyzes surfaces of revolution and derives conditions for a strongly convex slope metric.
result Necessary and sufficient conditions for surfaces of revolution to admit a strongly convex slope metric are established.
Improved convergence analysis for decentralized non-convex optimization.
problem Minimizing a sum of smooth non-convex functions over a network.
method Gradient tracking in decentralized stochastic gradient descent (GT-DSGD).
result GT-DSGD achieves network-independent performances matching centralized SGD under certain conditions.
Two new methods solve large-scale stochastic convex problems with linear constraints.
problem Solving large-scale stochastic convex optimization problems with many linear constraints.
method Conditional gradient-based methods that process only a subset of constraints at each iteration.
result Rigorous convergence guarantees for the proposed methods.
Study on convex capillary hypersurfaces with Lp curvature in half-space.
problem Prescribed Lp curvature for convex capillary hypersurfaces.
method Reduction to Hessian quotient equation with Robin boundary condition.
result Existence and uniqueness of smooth admissible solutions.
New methods achieve linear convergence on broader convex functions.
problem Optimization on broader convex functions with singular or unbounded second derivatives.
method Discretizations of conformal Hamiltonian dynamics.
result Linear convergence on convex functions with singular or unbounded second derivatives.
Convex program for estimating nonlinear recurrent models with stability conditions.
problem Estimating parameters in nonlinear recurrent models with stability conditions.
method Formulated a convex program for the estimator of nonlinear recurrent models under stability conditions.
result Sample complexity for the convex program estimator under stable dynamics.
New algorithm SFHC achieves near-optimal costs with predictions for non-convex optimization.
problem Online optimization with non-convex hitting costs and movement costs.
method Synchronized Fixed Horizon Control (SFHC) algorithm with conditions on hitting and movement costs.
result Synchronized Fixed Horizon Control (SFHC) achieves a 1+O(1/w) competitive ratio for near-optimal costs.