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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.

168,742 papers · 148 categories

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4692138184 · Jun 202019922001200920172026
48 results for Stäckel transform

In this paper, we introduce an equivalence relation on the set of local moves and classify local moves, called the extended STST-moves, up to the equivalence. Moreover, by inducing a binary relation on the set of equivalence classes of local moves, we show that an extended STST-move realizes the crossing change or the …

2016-04-26abs ↗pdf ↗

ST-BCP narrows the coverage gap in BCP by transforming nonconformity scores.

problem The looseness in BCP's coverage guarantee due to Markov's inequality.
method Introduces a data-dependent transformation of nonconformity scores.
result Reduces the average coverage gap from 4.20% to 1.12% on benchmarks.

A major challenge in computed tomography (CT) is to reduce X-ray dose to a low or even ultra-low level while maintaining the high quality of reconstructed images. We propose a new method for CT reconstruction that combines penalized weighted-least squares reconstruction (PWLS) with regularization based on a sparsifying…

2017-07-10abs ↗pdf ↗

NAST generalizes scattering transform for non-stationary time series analysis.

problem Analyzing non-stationary time series data.
method Neural activation of scattering transform with various activation functions and high pass filters.
result Central and non-central limit theorems for NAST of Gaussian processes.

This study improves sentence embeddings from BERT models.

problem Capturing the underlying meaning of sentences using BERT models.
method Comprehensive review and testing of various sentence embedding extraction and refinement methods.
result Representation-shaping techniques significantly improve sentence embeddings from BERT-based and simple baseline models.

Self-training improves generalization by fitting to reliable pseudo-labels or gradually improving the classification plane.

problem Understanding how self-training improves generalization in high-dimensional Gaussian mixtures.
method Analyzing iterative self-training on binary Gaussian mixtures in the asymptotic limit.
result ST improves generalization by fitting to reliable pseudo-labels or gradually improving the classification plane.

Spatio-temporal (ST) data for urban applications, such as taxi demand, traffic flow, regional rainfall is inherently stochastic and unpredictable. Recently, deep learning based ST prediction models are proposed to learn the ST characteristics of data. However, it is still very challenging (1) to adequately learn the co…

2019-07-19abs ↗pdf ↗

We show that two Alexander biquandles M and M' are isomorphic iff there is an isomorphism of Z[s,1/s,t,1/t]-modules h:(1-st)M --> (1-st)M' and a bijection g:O_s(A) --> O_s(A') between the s-orbits of sets of coset representatives of M/(1-st)M and M'/(1-st)M' respectively satisfying certain compatibility conditions.

2006-11-28abs ↗pdf ↗

We study the problem of subspace tracking in the presence of missing data (ST-miss). In recent work, we studied a related problem called robust ST. In this work, we show that a simple modification of our robust ST solution also provably solves ST-miss and robust ST-miss. To our knowledge, our result is the first `compl…

2018-10-06abs ↗pdf ↗

In this paper, we investigate the action of pseudogroup of all point transformations on the natural bundle of equations y=u0(x,y)+u1(x,y)y+u2(x,y)(y)2+u3(x,y)(y)3y'' = u^0(x,y) + u^1(x,y)y' + u^2(x,y)(y')^2 + u^3(x,y)(y')^3. We calculate the 1-st nontrivial differential invariant of this action. It is a horizontal differential 2-form with values in some alge…

2008-04-02abs ↗pdf ↗

Let GG be a connected complex semisimple Lie group, equipped with a standard multiplicative Poisson structure πstπ_{\rm st} determined by a pair of opposite Borel subgroups (B,B)(B, B_-). We prove that for each vv in the Weyl group WW of GG, the double Bruhat cell Gv,v=BvBBvBG^{v,v} = BvB \cap B_-vB_- in GG, together with the …

2016-07-02abs ↗pdf ↗

A new model improves CT image quality from low-dose scans.

problem Improving CT image quality from low-dose scans.
method Multi-layer Residual Sparsifying Transform (MRST) learning model for low-dose CT reconstruction.
result The MRST model outperforms conventional methods in maintaining subtle details.

New method improves traffic forecasting models by adapting to spatial shifts.

problem Improving traffic forecasting models' ability to handle spatial shifts over years.
method Proposes a novel Mixture of Experts (MoE) framework for spatiotemporal models.
result Significant improvement in performance for handling spatial distribution shifts.

ST-STORM separates semantic and appearance features for robust representation learning.

problem Traditional SSL methods fail to capture appearance cues in critical applications.
method Hybrid SSL framework with two latent streams, Content and Style, disentangled through gating mechanisms.
result The Style branch effectively isolates complex appearance phenomena without degrading semantic performance.

ST-MAML tackles task ambiguity in meta-learning by encoding tasks with stochastic representations.

problem Handling tasks from multiple distributions is challenging for meta-learning due to task ambiguity.
method ST-MAML uses a stochastic neural network module to encode tasks and propagate task representations to revise input variable encoding.
result ST-MAML matches or outperforms state-of-the-art methods on various tasks.

Efficient methods for Lévy models using SINH-regular processes.

problem Efficient numerical methods for evaluating Lévy models.
method Defining SL-processes and sSL-processes, deriving properties of characteristic exponent, and showing all popular Lévy processes can be subordinated to Brownian motion.
result All crucial properties of characteristic exponent are consequences of a specific representation, and all popular Lévy processes are SL- or sSL-subordinated Brownian motion.

The Straight-Through (ST) estimator is a widely used technique for back-propagating gradients through discrete random variables. However, this effective method lacks theoretical justification. In this paper, we show that ST can be interpreted as the simulation of the projected Wasserstein gradient flow (pWGF). Based on…

2019-10-05abs ↗pdf ↗

This paper addresses the problem of rank aggregation, which aims to find a consensus ranking among multiple ranking inputs. Traditional rank aggregation methods are deterministic, and can be categorized into explicit and implicit methods depending on whether rank information is explicitly or implicitly utilized. Surpri…

2013-09-26abs ↗pdf ↗

Karl Menger's 1934 paper on the St. Petersburg paradox contains mathematical errors that invalidate his conclusion that unbounded utility functions, specifically Bernoulli's logarithmic utility, fail to resolve modified versions of the St. Petersburg paradox.

2011-10-07abs ↗pdf ↗

We introduce and study a notion of `Sasaki with torsion structure' (ST) as an odd-dimensional analogue of Kähler with torsion geometry (KT). These are normal almost contact metric manifolds that admit a unique compatible connection with 3-form torsion. Any odd-dimensional compact Lie group is shown to admit such a stru…

2012-07-12abs ↗pdf ↗

In this paper we work toward the Homflypt skein module of the lens spaces L(p,1)L(p,1), S(L(p,1))\mathcal{S}(L(p,1)), using braids. In particular, we establish the connection between S(ST)\mathcal{S}({\rm ST}), the Homflypt skein module of the solid torus ST, and S(L(p,1))\mathcal{S}(L(p,1)) and arrive at an infinite system, whose solution…

2016-04-21abs ↗pdf ↗

Explicitly found generators of cohomology for SL_n(Z) using sharbly cycles and cosharbly cocycles.

problem Finding explicit generators for the cohomology of SL_n(Z).
method Using sharbly cycles and cosharbly cocycles, and applying Borel-Serre duality.
result Explicitly found generators of H_t(SL_n(Z),St) in terms of sharbly cycles and cosharbly cocycles.

The paper studies pseudo and singular links in a solid torus, developing invariants and algebraic structures.

problem Understanding and classifying links with missing crossing information in a solid torus.
method Introducing pseudo and singular links, constructing invariants, and developing algebraic structures.
result Formulated and proved the Alexander and Markov theorems for pseudo and singular links in a solid torus.

We prove a Chekanov-type theorem for the spherization of the cotangent bundle STBST^*B of a closed manifold BB. It claims that for Legendrian submanifolds in STBST^*B the property "to be given by a generating family quadratic at infinity" persists under Legendrian isotopies.

2016-02-28abs ↗pdf ↗

The structure set $\ST^{TOP}(M)$ of an nn-dimensional topological manifold MM for n5n \geqslant 5 has a homotopy invariant functorial abelian group structure, by the algebraic version of the Browder-Novikov-Sullivan-Wall surgery theory. An element $(N,f) \in \ST^{TOP}(M)$ is an equivalence class of nn-dimensional ma…

2006-08-29abs ↗pdf ↗

StreamEnsemble dynamically selects ML models for ST data streams to improve predictive accuracy.

problem Predictive queries over spatiotemporal data streams are challenging due to varying distributions and patterns.
method Dynamic selection and allocation of ML models based on time series distributions and characteristics.
result Significantly outperforms traditional ensemble and single model approaches, reducing prediction error by over 10 times.

Contact round surgeries on (S3,ξst)(\mathbb{S}^3,ξ_{st}) help in constructing and understanding contact 3-manifolds.

problem Constructing contact 3-manifolds using Legendrian surgeries.
method Introducing contact round surgeries of indices 1 and 2, and associating them with surgery diagrams.
result Every closed connected contact 3-manifold can be obtained by a sequence of contact round surgeries on Legendrian knots in (S3,ξst)(\mathbb{S}^3,ξ_{st}).

ST-MTM models complex time series by decomposing and masking seasonal and trend components.

problem Forecasting complex time series with intricate temporal variations.
method Seasonal-Trend Decomposition with Masking and Contrastive Learning.
result ST-MTM achieves superior forecasting performance compared to existing methods.

Improved Thompson Sampling outperforms existing Bayesian optimization methods.

problem Thompson Sampling's performance in Bayesian optimization is suboptimal compared to other methods.
method Developed Stagger Thompson Sampler (STS), which more precisely samples the optimal arm with less computation.
result STS outperforms TS, PSS, and other acquisition methods in various optimization tasks.

Reintroduces straight-through estimators for binary neural networks.

problem Training neural networks with binary weights and activations is challenging due to gradient issues and discrete weight optimization.
method Derives ST methods as estimators in the SBN model, analyzes properties and estimation accuracy, explains latent weights and mirror descent method.
result Reintroduces ST methods as sound approximations and provides clearer application and improvements.

Researchers develop a new basis to simplify solving infinite systems for HOMFLYPT skein module of lens spaces.

problem Computing the HOMFLYPT skein module of lens spaces L(p,1)L(p, 1) via braids.
method Using a new basis ΛΛ of the HOMFLYPT skein module of the solid torus, relating infinite systems of equations obtained by performing braid band moves on elements in Λ+Λ^+ and ΛΛ^- via a map II.
result Reduced complexity in solving the infinite system of equations for L(p,1)L(p, 1) using braids.

For an (m+1)(m+1)-dimensional space-time (Xm+1,g),(X^{m+1}, g), define a mapped null hypersurface to be a smooth map ν:NmXm+1ν:N^{m}\to X^{m+1} (that is not necessarily an immersion) such that there exists a smooth field of null lines along νν that are both tangent and gg-orthogonal to ν.ν. We study relations between mapped null hyp…

2007-02-11abs ↗pdf ↗