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.

168,742 papers · 148 categories

Trend · papers per month

4.2%8.3%12.5%16.7% · Sep 199519922001200920172026
48 results for HSC survey

Deep learning reduces noise in weak lensing mass maps using GANs.

problem Noise reduction in weak lensing mass maps.
method Generative adversarial networks (GANs) applied to Subaru Hyper Suprime-Cam data.
result GANs successfully reproduce non-Gaussian information in denoised maps, showing stronger cosmological dependence.

Positive holomorphic sectional curvature on rational surfaces is characterized by Kähler metrics.

problem Characterizing rational surfaces by the existence of a Kähler metric with positive holomorphic sectional curvature.
method Constructing Kähler metrics on projective manifolds obtained from toric manifolds.
result Every projective manifold obtained from a projective toric manifold by a finite sequence of blow-ups at points admits a Kähler metric with positive holomorphic sectional curvature.

Spectral clustering is a celebrated algorithm that partitions objects based on pairwise similarity information. While this approach has been successfully applied to a variety of domains, it comes with limitations. The reason is that there are many other applications in which only \emph{multi}-way similarity measures ar…

2018-05-23abs ↗pdf ↗

The paper constructs metrics with negative curvature on complex manifolds.

problem Constructing complete Kähler metrics with negative bisectional curvature on hyperbolic complex manifolds.
method Introducing a mechanism for constructing complete Kähler metrics with negative bisectional curvature.
result Realized Chern slopes c12/c2c_1^2/c_2 for surfaces with negative holomorphic sectional curvature.

Study estimates the first eigenvalue on Kähler manifolds with specific curvature conditions.

problem Estimating the first eigenvalue of Laplacian on Kähler manifolds with holomorphic sectional curvature constraints.
method Developed a Bochner-Kodaira type identity for holomorphic sectional curvature to prove eigenvalue estimates.
result First eigenvalue of Laplacian on Kähler manifolds is bounded from below under certain curvature conditions.

FCDD improves image anomaly detection without post-hoc explainers.

problem Image anomaly detection, especially pixel-wise.
method Fully Convolutional Data Description (FCDD) directly addresses anomaly detection without post-hoc methods.
result FCDD achieves state-of-the-art results on pixel-wise AD tasks.

Paper proposes efficient methods for high-order clustering in tensor block models.

problem High-order clustering of multiway datasets in neuroimaging, genomics, etc.
method Tensor block model and computationally efficient algorithms (HLloyd, HSC)
result Achieves high-order exact clustering with statistical optimality and computational efficiency.

Study shows non-systematic bias in customer satisfaction surveys limits data value.

problem Non-systematic bias in customer satisfaction surveys limits data value.
method Used real customer satisfaction survey data of a large retail bank to show the irreducible error and suggest thoughtful survey design methods.
result A thoughtful survey design can reduce non-systematic error in customer satisfaction surveys.

The paper tests the credibility of public and private surveys using linear regression and differential privacy.

problem Ensuring the validity of data analysis results from sample surveys using linear regression.
method Designing an algorithm to test the credibility of surveys and extending it to handle LDP.
result The algorithm achieves optimal estimation error bound for 1\ell_1 linear regression and reduces sample complexity.

New ensemble models classify mouse movement trajectories to assess survey question difficulty.

problem Assessing survey question difficulty based on respondents' interaction data.
method Ensemble models combining semi-metric-based weak learners to classify multivariate functional data.
result Improved survey data quality through better identification of respondent difficulty.

This is a survey of motivations, constructions and applications of higher prequantum geometry. In section 1 we highlight the open problem of prequantizing local field theory in a local and gauge invariant way, and we survey how a solution to this problem exists in higher differential geometry. In section 2 we survey ex…

2016-01-22abs ↗pdf ↗

Digital personas improve survey results for stable attributes but fail for subjective responses.

problem When can digital personas reliably approximate human survey findings?
method Using LISS panel, constructed personas from background variables and survey histories, tested against held-out post-cutoff answers.
result Digital personas improve alignment with human response distributions for stable attributes but fail for subjective responses.

Survey of methods for solving smooth stochastic variational inequalities.

problem Solving smooth (strongly) monotone stochastic variational inequalities.
method Deterministic foundation, general stochastic formulation, finite sum setup, recent advances.
result Review of various methods for solving smooth stochastic variational inequalities.

This survey covers in our opinion the most important results in the theory of continuous selections of multivalued mappings (approximately) from 2002 through 2012. It extends and continues our previous such survey which appeared in Recent Progress in General Topology, II, which was published in 2002. In comparison, our…

2014-01-10abs ↗pdf ↗

SDRF estimates complex survey designs for conditional distributions.

problem Estimating conditional distributions under complex survey designs.
method Survey-calibrated distributional random forest (SDRF) with pseudo-population bootstrap and MMD split criterion.
result Established design consistency and model consistency for survey designs.