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arXiv research

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.

169,051 papers · 148 categories

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48 results for Random simplex

New convex body defined to prove Busemann Random Simplex Inequality.

problem Proving Busemann Random Simplex Inequality for general p.
method Defining NpLN_p L and proving isoperimetric inequality for its dual.
result Equivalent to LpL_p-Busemann-Petty centroid inequality for p=1,2.

Investigates VaR behavior for sums of one-sided random variables, showing impossibilities and conditions for super-additivity.

problem Investigates the behavior of Value-at-Risk (VaR) for sums of one-sided random variables.
method Analyzes the extremal aggregation behavior of VaR, introduces structural conditions for super-additivity.
result Characterizes when VaR is fully super-additive and provides unified framework for various dependence structures.

We show an efficient algorithm for the following problem: Given uniformly random points from an arbitrary n-dimensional simplex, estimate the simplex. The size of the sample and the number of arithmetic operations of our algorithm are polynomial in n. This answers a question of Frieze, Jerrum and Kannan [FJK]. Our resu…

2012-11-09abs ↗pdf ↗

The paper extends Busemann's inequalities to complex and quaternionic spaces.

problem Extending Busemann's inequalities to complex and quaternionic vector spaces.
method Proof leverages a monotonicity property under symmetrization with respect to complex or quaternionic hyperplanes.
result Standard Steiner symmetrization does not exhibit the monotonicity property in complex or quaternionic spaces.

Exact optimality achieved in distributed mean estimation with shared randomness.

problem Achieving optimal communication, privacy, and utility tradeoffs in distributed mean estimation.
method Utilization of a rotationally symmetric shared random codebook and a kk-closest encoding mechanism.
result Proposed mechanism achieves exact optimality for randomly rotated simplex codebook.

A new model clusters multi-faceted data with uncertainty quantification.

problem Uncertainty in multi-view clustering of high-dimensional data.
method Approximate Bayes approach, treating similarity matrices as rough estimates, refining with low-rank matrix.
result Each simplex coordinate encodes cluster assignment uncertainty.

Algorithm learns latent simplex from perturbed points in input-sparsity time.

problem Learning a latent kk-vertex simplex from noisy data.
method Input-sparsity time algorithm using low-rank approximation and adaptive selection.
result Algorithm achieves O(extrmnnz(A))O( extrm{nnz}(A)) time complexity, avoiding kextrmnnz(A)k\cdot extrm{nnz}(A).

The paper triangulates Heisenberg groups with horizontal and straight simplexes.

problem Triangulating Heisenberg groups with specific regularity properties.
method Constructing triangulations with horizontal and straight simplexes on a polyhedral structure and extending to the whole Heisenberg group.
result Explicit examples of grid and triangulations provided.

We describe a Groebner basis of relations among conditional probabilities in a discrete probability space, with any set of conditioned-upon events. They may be specialized to the partially-observed random variable case, the purely conditional case, and other special cases. We also investigate the connection to generali…

2008-08-08abs ↗pdf ↗

Study optimal transport on simplex boundary, proving transport map and potential regularity.

problem Regularity of transport map and potential on simplex boundary.
method Boundary regularity results for optimal transport maps, exploiting simplex symmetries.
result Regularity properties of transport map and its convex potential.

A hyperbolic 3-simplex reflection group is a Coxeter group arising as a lattice in the isometry group of hyperbolic 3-space, with fundamental domain a geodesic simplex (possibly with some ideal vertices). The classification of these groups is known, and there are exactly 9 cocompact examples, and 23 non-cocompact examp…

2007-05-07abs ↗pdf ↗

We introduce the non-pure versions of simplicial balls and spheres with minimum number of vertices. These are a special type of non-homogeneous balls and spheres (NH-balls and NH-spheres) satisfying a minimality condition on the number of maximal simplices. The main result is that minimal NH-balls and NH-spheres are pr…

2014-06-25abs ↗pdf ↗

In 1973, J. Cheeger and J. Simons raised the following question that still remains open and is known as the Rational Simplex Problem: Given a geodesic simplex in the spherical 3-space so that all of its interior dihedral angles are rational multiples of ππ, is it true that its volume is a rational multiple of the volu…

2013-04-28abs ↗pdf ↗

Paper calculates Gromov-Hausdorff distance between simplexes and 2-distance spaces.

problem Calculating Gromov-Hausdorff distance between simplexes and 2-distance spaces.
method Formulas derived for clique covering number and chromatic number of graphs.
result Complete solution to generalized Borsuk problem for 2-distance spaces.

In ensemble methods, the outputs of a collection of diverse classifiers are combined in the expectation that the global prediction be more accurate than the individual ones. Heterogeneous ensembles consist of predictors of different types, which are likely to have different biases. If these biases are complementary, th…

2018-02-21abs ↗pdf ↗

Subgradient algorithm achieves optimal regret for both adversarial and i.i.d. costs on the simplex.

problem Achieving optimal regret for both adversarial and i.i.d. costs on the simplex.
method Demonstrates the universality of the Subgradient algorithm for online learning on the simplex.
result Shows simultaneous O(N)O(\sqrt N) regret for adversarial costs and O(1)O(1) pseudo-regret for i.i.d. costs.

A faster Wasserstein k-means algorithm for histogram data reduces computation and maintains clustering quality.

problem Efficiently clustering histogram data with reduced computation time.
method Sparse simplex projection to reduce data samples, centroids, and ground cost matrix, dynamically removing lower-valued samples.
result Significant reduction in computational complexity without compromising clustering quality.

Proposes an accuracy-preserving calibration method for DNNs.

problem Calibration of deep neural networks (DNNs) to measure prediction reliability.
method Uses Concrete distribution on the probability simplex to calibrate DNNs without accuracy loss.
result The proposed method outperforms previous methods in accuracy-preserving calibration tasks.

On the probability simplex, we can consider the standard information geometric structure with the e- and m-affine connections mutually dual with respect to the Fisher metric. The geometry naturally defines submanifolds simultaneously autoparallel for the both affine connections, which we call {\em doubly autoparallel s…

2017-11-30abs ↗pdf ↗

Proposes Dirichlet Simplex Nest for probabilistic modeling of various data types.

problem Modeling and inference for diverse data types.
method Probabilistic models based on Dirichlet distribution and Voronoi tessellation, with fast and accurate inference algorithms exploiting convex geometry and simplicial structure.
result Inference algorithms achieve consistency and strong error bounds across various settings and data distributions.

The paper is devoted to modeling optimal exercise strategies of the behavior of investors and issuers working with convertible bonds. This implies solution of the problems of stock price modeling, payoff computation and min-max optimization. Stock prices (underlying asset) were modeled under the assumption of the geome…

2007-10-01abs ↗pdf ↗

CAST predicts distribution-valued time series by stabilizing and transporting simplex-supported successors.

problem Forecasting distribution-valued time series with structural failure modes.
method CAST (Causal Anchored Simplex Transport) uses successors retrieved from causal context, stabilized with a persistence anchor, and locally transported on ordered supports.
result CAST outperforms baselines on eleven public and simulated benchmarks, achieving best average rank on both one-step KL and autoregressive rollout JSD.

New framework estimates staged tree models using hierarchical clustering on the probability simplex.

problem Estimating staged tree models with context-specific dependencies.
method Hierarchical clustering on the probability simplex, using simplex-based divergences and linkage methods.
result Total Variation divergence with Ward.D2 linkage produces staged trees with better model fit, structure recovery, and computational efficiency.

We compare two statistical models of three binary random variables. One is a mixture model and the other is a product of mixtures model called a restricted Boltzmann machine. Although the two models we study look different from their parametrizations, we show that they represent the same set of distributions on the int…

2017-09-15abs ↗pdf ↗

We study a natural intrinsic definition of geometric simplices in Riemannian manifolds of arbitrary dimension nn, and exploit these simplices to obtain criteria for triangulating compact Riemannian manifolds. These geometric simplices are defined using Karcher means. Given a finite set of vertices in a convex set on t…

2014-06-14abs ↗pdf ↗

Paper studies weighted Fermat-Frechet problem for simplex edge lengths.

problem Finding optimal edge lengths for simplex deformations.
method Isometric embedding techniques for KK-Space.
result New variational method to solve weighted Fermat-Frechet problem.