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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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48 results for University ranking

Using an artificial neural network (ANN), a fixed universe of approximately 1500 equities from the Value Line index are rank-ordered by their predicted price changes over the next quarter. Inputs to the network consist only of the ten prior quarterly percentage changes in price and in earnings for each equity (by quart…

2008-06-16abs ↗pdf ↗

We discuss the rigidity (or lack thereof) imposed by different notions of having an abundance of zero curvature planes on a complete Riemannian 3-manifold. We prove a rank rigidity theorem for complete 3-manifolds, showing that having higher rank is equivalent to having reducible universal covering. We also study 3-man…

2014-07-15abs ↗pdf ↗

The paper shows that for Coxeter groups, the commensurator of outer automorphisms is rigid.

problem The rigidity of commensurator of outer automorphisms of Coxeter groups.
method Study of the abstract commensurator of the outer automorphism group of a universal Coxeter group.
result For n5n \geq 5, the natural map is an isomorphism and every isomorphism between finite index subgroups is conjugation.

We study the spherical cap packing problem with a probabilistic approach. Such probabilistic considerations result in an asymptotic sharp universal uniform bound on the maximal inner product between any set of unit vectors and a stochastically independent uniformly distributed unit vector. When the set of unit vectors …

2015-11-19abs ↗pdf ↗

We generalize the higher rank rigidity theorem to a class of Finsler spaces, i.e. Berwald spaces. More precisely, we prove that a complete connected Berwald space of finite volume and bounded nonpositive flag curvature with rank at least 22 whose universal cover is irreducible, is a locally symmetric space or a locall…

2015-10-15abs ↗pdf ↗

Market sectors play a key role in the efficient flow of capital through the modern Global economy. We analyze existing sectorization heuristics, and observe that the most popular - the GICS (which informs the S&P 500), and the NAICS (published by the U.S. Government) - are not entirely quantitatively driven, but rather…

2019-05-31abs ↗pdf ↗

We prove explicit formulas for Chern classes of tensor products of vector bundles, with coefficients given by certain universal polynomials in the ranks of the two bundles.

2010-11-30abs ↗pdf ↗

We study the problem of reconstructing an unknown matrix M of rank r and dimension d using O(rd poly log d) Pauli measurements. This has applications in quantum state tomography, and is a non-commutative analogue of a well-known problem in compressed sensing: recovering a sparse vector from a few of its Fourier coeffic…

2011-03-14abs ↗pdf ↗

We show that canonical Carnot-Caratheodory spherical and horospherical metrics, which are defined on the boundary at infinity of every rank one symmetric space of non-compact type, are visual, i.e., they are bilipschitz equivalent with universal bilipschitz constants to the inverse exponent of Gromov products based in …

2009-06-04abs ↗pdf ↗

We study Atlas-type models of equity markets with local characteristics that depend on both name and rank, and in ways that induce a stable capital distribution. Ergodic properties and rankings of processes are examined with reference to the theory of reflected Brownian motions in polyhedral domains. In the context of …

2009-09-01abs ↗pdf ↗

We study the LpL^p-spectrum of the Laplace-Beltrami operator on certain complete locally symmetric spaces M=Γ\XM=Γ\backslash X with finite volume and arithmetic fundamental group ΓΓ whose universal covering XX is a symmetric space of non-compact type. We also show, how the obtained results for locally symmetric spaces c…

2007-07-17abs ↗pdf ↗

Let MM be complete nonpositively curved Riemannian manifold of finite volume whose fundamental group ΓΓ does not contain a finite index subgroup which is a product of infinite groups. We show that the universal cover M~\tilde M is a higher rank symmetric space iff Hb2(M;R)H2(M;R)H^2_b(M;\R)\to H^2(M;\R) is injective (and otherwis…

2007-02-09abs ↗pdf ↗

LITE models improve query-document relevance with learnable late interactions.

problem Improving query-document relevance with lower latency and storage.
method Proposes learnable late-interaction models (LITE) that use factorized query and document embeddings followed by a learnable scorer.
result Empirically, LITE outperforms previous late-interaction models in re-ranking tasks.

Study of asymmetric rank-one tensor models with non-Gaussian noise.

problem Analyzing maximum-likelihood estimators for asymmetric rank-one tensor models.
method Spectrally separated branch analysis, resolvent methods, cumulant expansions, Efron-Stein-type variance bounds.
result Asymptotic singular value and mode-wise alignments are robust to non-Gaussian noise.

We study the problem of learning to rank from multiple information sources. Though multi-view learning and learning to rank have been studied extensively leading to a wide range of applications, multi-view learning to rank as a synergy of both topics has received little attention. The aim of the paper is to propose a c…

2018-01-31abs ↗pdf ↗

The problem of low-rank matrix completion has recently generated a lot of interest leading to several results that offer exact solutions to the problem. However, in order to do so, these methods make assumptions that can be quite restrictive in practice. More specifically, the methods assume that: a) the observed indic…

2014-02-10abs ↗pdf ↗

Paper introduces a new histogram estimator for nonparametric density estimation that improves performance.

problem Smoothness-based nonparametric density estimators are not optimal for all types of data.
method Incorporates a multi-view latent variable model into histogram-style estimators.
result A new histogram estimator converges faster to multi-view models in L1L^1 error.

StochasticRank optimizes ranking metrics efficiently and guarantees global convergence.

problem Optimizing discrete ranking metrics due to their ill-posed nature.
method Stochastic smoothing, gradient estimate, debiasing, and Stochastic Gradient Langevin Boosting.
result Global convergence and superior performance on ranking datasets.

Soft-Radial Projection solves gradient saturation in constrained deep learning.

problem Gradient saturation in deep learning models when integrating hard constraints.
method Introduces Soft-Radial Projection, a differentiable layer that maps predictions onto constraint boundaries without rank-deficient Jacobians.
result Improves convergence and solution quality over state-of-the-art methods.

We discuss Donaldson-Thomas (DT) invariants of torsion sheaves with 2 dimensional support on a smooth projective surface in an ambient non-compact Calabi Yau fourfold given by the total space of a rank 2 bundle on the surface. We prove that in certain cases, when the rank 2 bundle is chosen appropriately, the universal…

2018-10-22abs ↗pdf ↗

Let XX be a compact, geodesically complete, locally CAT(0) space such that the universal cover admits a rank one axis. Assume XX is not homothetic to a metric graph with integer edge lengths. Let PtP_t be the number of parallel classes of oriented closed geodesics of length t\le t; then $\lim\limits_{t \to \infty} P…

2019-03-18abs ↗pdf ↗

There is a well known link between (maximal) polar representations and isotropy representations of symmetric spaces provided by Dadok. Moreover, the theory by Tits and Burns-Spatzier provides a link between irreducible symmetric spaces of non-compact type of rank at least three and irreducible topological spherical bui…

2012-05-28abs ↗pdf ↗

Language models exhibit low-rank structure, which can be used for generation.

problem Understanding the low-dimensional structure of large language models.
method Empirical demonstration and theoretical analysis of the approximate rank of language models' logits.
result Language models can generate responses using linear combinations of unrelated prompts.

This paper improves GNNs' generalization by adding a Low-Rank Global Attention module.

problem Improving the generalization power of Graph Neural Networks (GNNs).
method Incorporating a Low-Rank Global Attention (LRGA) module into GNNs.
result Augmenting GNNs with LRGA aligns them with a powerful graph isomorphism test, 2-Folklore Weisfeiler-Lehman (2-FWL).

This paper considers the problem of estimating a low-rank matrix from the observation of all or a subset of its entries in the presence of Poisson noise. When we observe all entries, this is a problem of matrix denoising; when we observe only a subset of the entries, this is a problem of matrix completion. In both case…

2019-07-11abs ↗pdf ↗

We conjecture a formula for the virtual elliptic genera of moduli spaces of rank 2 sheaves on minimal surfaces SS of general type. We express our conjecture in terms of the Igusa cusp form χ10χ_{10} and Borcherds type lifts of three quasi-Jacobi forms which are all related to the Weierstrass elliptic function. We also …

2018-01-08abs ↗pdf ↗

We consider the problem of identifying universal low-dimensional features from high-dimensional data for inference tasks in settings involving learning. For such problems, we introduce natural notions of universality and we show a local equivalence among them. Our analysis is naturally expressed via information geometr…

2019-11-20abs ↗pdf ↗