Research
On-device research index

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.

168,932 papers · 148 categories

Trend · papers per month

15314661 · Jun 202019922001200920172026
48 results for query radius

Gradient descent is efficient for solving feasibility problems with minimal memory and queries.

problem Finding a point in a given set using a memory-constrained algorithm with a separation oracle.
method Oracle complexity lower bounds for gradient descent and other algorithms.
result Gradient descent is Pareto-optimal in the oracle complexity/memory tradeoff for feasibility problems.

Proposes LRR and LRLR for improving stock prediction accuracy.

problem Improving stock prediction accuracy through nonparametric classification.
method Local radial regression and logistic regression variant.
result LRLR outperforms LPoR and MS-kk-NN in real-world stock datasets.

The paper investigates learning conditional distributions on multi-dimensional spaces using clustering and neural networks.

problem Learning conditional distributions on multi-dimensional spaces with varying dimensions.
method The approach involves clustering data near varying query points in the feature space to create empirical measures in the target space using two clustering schemes: fixed-radius ball and nearest neighbors. The convergence rates of both methods are analyzed, and the nearest neighbors method is incorporated into neural network training.
result The empirical analysis shows that the nearest neighbors method has better performance in practice and can adapt to a suitable level of Lipschitz continuity locally.

A new hashing framework learns multiple hash codes for each image to improve hash bucket search efficiency.

problem Existing hashing methods fail to handle complex image retrieval scenarios efficiently.
method Multiple Code Hashing (MCH) framework with deep reinforcement learning.
result Significant improvement in hash bucket search performance compared to single-code methods.

New study shows acceleration in hyperbolic spaces is impossible for strongly geodesically convex functions.

problem Acceleration in hyperbolic spaces for strongly geodesically convex functions is impossible.
method Perturbing hard functions with sums of bump functions chosen by a resisting oracle.
result Acceleration is unachievable for any deterministic algorithm in hyperbolic spaces for strongly geodesically convex functions.

Many nonparametric regressors were recently shown to converge at rates that depend only on the intrinsic dimension of data. These regressors thus escape the curse of dimension when high-dimensional data has low intrinsic dimension (e.g. a manifold). We show that k-NN regression is also adaptive to intrinsic dimension. …

2011-10-19abs ↗pdf ↗

The ratio of convexity radius over injectivity radius may be made arbitrarily small within the class of compact Riemannian manifolds of any fixed dimension at least two. This is proved using Gulliver's method of constructing manifolds with focal points but no conjugate points. The approach is suggested by a characteriz…

2014-12-01abs ↗pdf ↗

Uniform curvature bounds for regularized metrics with bounds on Ricci tensor and injectivity radius.

problem Bounding curvature of regularized metrics with constraints on Ricci tensor and injectivity radius.
method Mollification of riemannian metrics, uniform W2,pW^{2,p}-harmonic radius bounds, Ricci tensor bounds, injectivity radius bounds.
result Uniform estimate on the change of sectional curvature for regularized metrics.

Upper bound for conjugate radius in open manifolds with scalar curvature and spectrum constraints.

problem Bounding the conjugate radius of open manifolds with specific curvature and spectrum conditions.
method Established an upper bound using scalar curvature and bottom-of-spectrum constraints.
result For certain conditions, the conjugate radius is no more than π.

The paper bounds bandwidth and focal radius for manifolds with positive isotropic curvature.

problem Bounding bandwidth and focal radius for manifolds with positive isotropic curvature.
method Using spectral properties of a twisted de Rham-Hodge operator.
result Upper bounds on bandwidth and focal radius are derived for hypersurfaces in PIC manifolds.

Upper bound on Stiefel manifold's injectivity radius found.

problem Finding the maximum distance within which the Stiefel manifold remains injective.
method Exhibited conjugate points and calculated the minimum of geodesic lengths.
result Upper bound on Stiefel manifold's injectivity radius is conjectured to be equal to the injectivity radius.

Smooths metrics on manifolds with curvature bounds and injectivity radius constraints.

problem Smooth metrics on manifolds with curvature and injectivity constraints.
method Bi-Lipschitz smoothing with controlled smoothing and volume lower bounds.
result Proves existence of smooth metrics with curvature bounds and injectivity radius constraints.

A translation structure equips a Riemann surface with a singular flat metric. Not much is known about the shape of a random translation surface. We compute an upper bound on the expected value of the covering radius of a translation surface in any stratum H_1(kappa). The covering radius of a translation surface is the …

2018-09-27abs ↗pdf ↗

This paper considers metric balls B(p,R)B(p,R) in two dimensional Riemannian manifolds when RR is less than half the convexity radius. We prove that Area(B(p,R))8πR2Area(B(p,R)) \geq \frac{8}πR^2. This inequality has long been conjectured for RR less than half the injectivity radius. This result also yields the upper bound $μ_2(B(p,R)…

2017-01-23abs ↗pdf ↗

The paper optimizes querying schemes for crowdsourced classification using XOR queries.

problem Optimizing querying schemes for crowdsourced classification.
method Modeling crowdsourced labeling/classification as source coding problem, leveraging connections to channel coding.
result Provides querying schemes with almost optimal number of queries, each involving a constant number of labels.

Study finds shortest geodesic loops on Stiefel manifold and calculates its injectivity radius.

problem Determining the shortest geodesic loops and injectivity radius on Stiefel manifold.
method Combining bounds on sectional curvature with existing metrics.
result Exact value of the injectivity radius for a wide range of metrics.

Study compares eigenvalues on spherically symmetric manifolds to Euclidean balls.

problem Comparing eigenvalues on spherically symmetric manifolds to Euclidean balls.
method Examines Dirichlet Laplace eigenvalues on balls of spherically symmetric manifolds and Euclidean space.
result Eigenvalues on spherically symmetric manifolds are smaller for small radii, but larger for hyperbolic spaces.

The paper improves bounds on injectivity radius for manifolds with positive scalar curvature.

problem Finding tighter bounds on the injectivity radius for manifolds with positive scalar curvature.
method Utilizing Green's inequality and topological assumptions on manifolds, including specific 3-manifolds and products.
result Stronger upper bounds on injectivity radius for certain manifolds, including products and 3-manifolds with positive scalar curvature.

Efficiently classifies binary labels with XOR queries, even under noisy conditions.

problem Binary classification with unknown labels using XOR queries.
method Effective query type and an efficient inference algorithm for noisy conditions.
result Achieves information-theoretic limit on optimal number of queries.

In this note we relate the geometric notion of fill radius with the fundamental group of the manifold. We prove: ''Suppose that a closed Riemannian manifold M satisfies the property that its universal cover has bounded fill radius. Then the fundamental group of M is virtually free.'' We explain the relevance of this th…

2009-06-24abs ↗pdf ↗

Characterizes submanifolds with minimum ratio of diameter to focal radius.

problem Finding submanifolds with the minimum ratio of extrinsic diameter to focal radius.
method Combining K. Sakamoto's classification of submanifolds with planar geodesics and A. Schur's Bow Lemma for space curves.
result Essentially round spheres or Veronese embeddings of projective spaces achieve the minimum ratio.

We define a capacity which measures the size of Weinstein tubular neighbourhoods of Lagrangian submanifolds. In symplectic vector spaces this leads to bounds on the codisc radius for any closed Lagrangian submanifold in terms of Viterbo's isoperimetric inequality. Moreover, we prove a generalization of Gromov's packing…

2012-10-08abs ↗pdf ↗

We discuss inverse resonance scattering for the Laplacian on a rotationally symmetric manifold M=(0,)×YM = (0,\infty) \times Y whose rotation radius is constant outside some compact interval. The Laplacian on MM is unitarily equivalent to a direct sum of one-dimensional Schrödinger operators with compactly supported potenti…

2019-04-18abs ↗pdf ↗