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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.

168,695 papers · 148 categories

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19395877 · May 202619922001200920172026
48 results for needle decomposition

The paper provides precise estimates for isoperimetric inequalities on weighted manifolds.

problem Quantitative isoperimetric inequalities on weighted Riemannian manifolds.
method Analyzes L1L^1, LpL^p, and W2W_2 estimates for the push-forward of measures.
result Close approximation of the guiding function's push-forward to Gaussian measure.

Study rigidity of spectral gap on Finsler manifolds with specific curvature bounds.

problem Rigidity of spectral gap on Finsler manifolds with Ricci curvature bound.
method Analysis of spectral gap, splitting phenomena, and needle decomposition.
result Rigidity results for spectral gap, logarithmic Sobolev, and Bakry-Ledoux inequalities.

We establish a quantitative isoperimetric inequality for weighted Riemannian manifolds with Ric1\mathrm{Ric}_{\infty} \ge 1. Precisely, we give an upper bound of the volume of the symmetric difference between a Borel set and a sub-level (or super-level) set of the associated guiding function (arising from the needle deco…

2019-10-30abs ↗pdf ↗

The localization technique from convex geometry is generalized to the setting of Riemannian manifolds whose Ricci curvature is bounded from below. In a nutshell, our method is based on the following observation: When the Ricci curvature is non-negative, log-concave measures are obtained when conditioning the Riemannian…

2014-08-27abs ↗pdf ↗

New findings show different cost functions yield equivalent curvature bounds.

problem Establishing equivalence of curvature bounds under various transport costs.
method Needle decomposition and localization technique for optimal transport.
result All CDp(K,N)\mathrm{CD}_{p}(K,N) conditions are equivalent for p>1p>1.

In this note we prove the Heintze-Karcher inequality in the context of essentially non-branching metric measure spaces satisfying a lower Ricci curvature bound in the sense of Lott-Sturm-Villani. The proof is based on the the needle decomposition technique for metric measure spaces introduced by Cavalletti-Mondino. Mor…

2019-08-16abs ↗pdf ↗

We investigate the rigidity problem for the logarithmic Sobolev inequality on weighted Riemannian manifolds satisfying RicK>0\mathrm{Ric}_{\infty} \ge K>0. Assuming equality holds, we show that the 11-dimensional Gaussian space is necessarily split off, similarly to the rigidity results of Cheng--Zhou on the spectral gap …

2019-04-20abs ↗pdf ↗

In this paper, we study continuous Kakeya line and needle configurations, of both the oriented and unoriented varieties, in connected Lie groups and some associated homogenous spaces. These are the analogs of Kakeya line (needle) sets (subsets of Rn\mathbb{R}^n where it is possible to turn a line (respectively an inter…

2013-03-04abs ↗pdf ↗

Learning to approximate a separable function is hard, requiring many samples even with sparse networks.

problem Learning the separable function xi=1dxi2x \mapsto \sum_{i=1}^d x_i^2 with limited samples.
method Sparse neural networks vs. dense neural networks, explicit regularization.
result The sample complexity for dense networks is O(d2.5)\mathcal{O}(d^{2.5}) with explicit regularization, better than O(d4)\mathcal{O}(d^{4}).

Study uses Bayesian Optimization to analyze noise effects in materials research.

problem Optimizing materials with many variables and experimental noise.
method Batch Bayesian Optimization with synthetic data analysis.
result Noise sensitivity varies by problem landscape, impacting optimization outcomes.

Solves dual imbalance in detecting sparse anomalies in MIL.

problem Detecting scarce and sparse anomalous samples in MIL.
method Reformulates MIL as a fine-grained PU learning problem, addressing imbalance at both macro and micro levels.
result Demonstrates effectiveness of BFGPU framework on synthetic and real-world datasets.

SCORE technique reduces BO's high-dimensional search costs.

problem Bayesian optimization's high computational costs in high-dimensional spaces.
method 1D reparametrization trick to maintain linear time complexity.
result Successfully finds global minimum in high-dimensional optimization.

This paper tackles label-efficient evaluation in extreme class imbalance.

problem Challenges in obtaining a sufficient sample for accurate evaluation in tasks with extreme class imbalance.
method Develops a framework for online evaluation based on adaptive importance sampling.
result Establishes strong consistency and a central limit theorem for performance estimates.

Bayesian method suppresses low-frequency pulses in audio recordings.

problem Suppressing long pulses caused by mechanical defects in audio recordings.
method Bayesian approach using Gaussian Process for pulse location, signal interpolation, and tail estimation.
result Perceptual results similar to previous methods, performs well on naturally degraded signals.

Uncorrelated optical space observation association represents a classic needle in a haystack problem. The objective being to find small groups of observations that are likely of the same resident space objects (RSOs) from amongst the much larger population of all uncorrelated observations. These observations being pote…

2020-01-09abs ↗pdf ↗

Study develops a method to select penalty parameters for sparse neural networks without cross-validation.

problem Selecting optimal penalty parameters for sparse neural networks without cross-validation.
method Established theoretical foundation to bound the infinite norm of the gradient of the loss function at zero.
result Proposed method effectively selects penalty parameters for sparse neural networks.

The paper proposes and discusses semiorthogonal decompositions for moduli spaces of vector bundles.

problem Decompositions of moduli spaces of vector bundles with fixed determinant of odd degree.
method Semiorthogonal decompositions, Grothendieck ring of varieties, mirror symmetry, graph potentials, Fukaya category.
result Evidence for a conjectural semiorthogonal decomposition of moduli spaces of rank 2 bundles with odd determinant.

We combine aspects of the notions of finite decomposition complexity and asymptotic property C into a notion that we call finite APC-decomposition complexity. Any space with finite decomposition complexity has finite APC-decomposition complexity and any space with asymptotic property C has finite APC-decomposition comp…

2017-09-04abs ↗pdf ↗

Study shows OAT decomposition generates unexplained profit and loss, while SU decompositions depend on risk factor order.

problem Understanding profit and loss attribution in financial markets.
method Used financial market data from 2003 to 2022 to compare OAT, SU, and ASU decompositions.
result SU decompositions are sensitive to risk factor order and cannot identify all relevant risk factors.

A double pants decomposition of a 2-dimensional surface is a collection of two pants decomposition of this surface introduced in arXiv:1005.0073v2. There are two natural operations acting on double pants decompositions: flips and handle twists. It is shown in arXiv:1005.0073v2 that the groupoid generated by flips and h…

2010-08-22abs ↗pdf ↗

Let J1\mathcal{J}^1 be the real form of a complex simple Jordan algebra such that the automorphism group is F4(20)\mathrm{F}_{4(-20)}. By using some orbit types of F4(20)\mathrm{F}_{4(-20)} on J1\mathcal{J}^1, for F4(20)\mathrm{F}_{4(-20)}, explicitly, we give the Iwasawa decomposition, the Oshima--Sekiguchi's KεK_ε-Iwasawa decomp…

2011-09-05abs ↗pdf ↗

We study the topological types of pants decompositions of a surface by associating to any pants decomposition P,P, in a natural way its pants decomposition graph, Γ(P).Γ(P). This perspective provides a convenient way to analyze the maximum distance in the pants complex of any pants decomposition to a pants decomposition c…

2011-06-07abs ↗pdf ↗

New method uses random decompositions for high-dimensional Bayesian optimization.

problem Learning accurate decompositions for high-dimensional black-box functions.
method Data-independent random tree-based decomposition sampling.
result Random decomposition upper-confidence bound algorithm (RDUCB) yields significant empirical gains.

Derive new Euler-Ramanujan-type identities and infinite decompositions for zero mean curvature graphs in various spaces.

problem Derive new Euler-Ramanujan-type identities and infinite decompositions for zero mean curvature graphs in various spaces.
method Derive new Euler-Ramanujan-type identities and infinite decompositions for zero mean curvature graphs in various spaces.
result Derive new Euler-Ramanujan-type identities and infinite decompositions for zero mean curvature graphs in various spaces.

Decompositions on manifolds appear in various geometric structures. Necessary and sufficient conditions for quotient spaces of decompositions to be manifolds are widely characterized. We characterize necessary and sufficient conditions to be kk-manifolds (k=1,2)(k = 1, 2), which generalize characterizations in the codimens…

2017-03-15abs ↗pdf ↗

We give an example of two JSJ decompositions of a group that are not related by conjugation, conjugation of edge-inclusions, and slide moves. This answers the question of Rips and Sela stated in "Cyclic splittings of finitely presented groups and the canonical JSJ decomposition," Ann. of Math. 146 (1997), 53-109. On th…

2001-10-17abs ↗pdf ↗

We consider a union of two pants decompositions of the same orientable 2-dimensional surface of any genus g. Each pants decomposition corresponds to some handlebody bounded by this surface, so two pants decompositions correspond to a Heegaard splitting of a 3-manifold. We introduce a groupoid FT acting on double pants …

2010-05-01abs ↗pdf ↗