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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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48 results for conference selection

The paper proposes a framework to recommend suitable conferences for authors.

problem Helping authors choose appropriate conferences for their research papers.
method Three approaches using social network and paper content, applying Correspondence Analysis (CA).
result Models show better performance than existing methods.

These notes gather recent results on robust statistical learning theory. The goal is to stress the main principles underlying the construction and theoretical analysis of these estimators rather than provide an exhaustive account on this rapidly growing field. The notes are the basis of lectures given at the conference…

2019-08-28abs ↗pdf ↗

This survey was compiled from lectures and problem sessions at the International Conference on Geometric Topology at the Mathematical Research and Conference Center in Bedlewo, Poland in July 2005.

2005-07-27abs ↗pdf ↗

New tool uses computer vision to assess FOMC press conference complexity and its impact on equity returns.

problem Understanding the impact of FOMC press conferences on financial markets.
method Developed a measure of discussion complexity using video images and deep learning algorithms.
result Complex discussions during press conferences are associated with higher equity returns and lower volatility.

We consider peer review in a conference setting where there is typically an overlap between the set of reviewers and the set of authors. This overlap can incentivize strategic reviews to influence the final ranking of one's own papers. In this work, we address this problem through the lens of social choice, and present…

2018-06-16abs ↗pdf ↗

Neural Information Processing Systems (NIPS) is a top-tier annual conference in machine learning. The 2016 edition of the conference comprised more than 2,400 paper submissions, 3,000 reviewers, and 8,000 attendees. This represents a growth of nearly 40% in terms of submissions, 96% in terms of reviewers, and over 100%…

2017-08-31abs ↗pdf ↗

Machine learning conferences face ethical issues in review process.

problem Ethical issues in the review process of machine learning conferences.
method Study of recruitment issues, double-blind process infringements, fraudulent behaviors, biases, and appendix phenomenon.
result Highlighting the need for awareness in the machine learning community.

Class selectivity affects robustness to corruptions but not to adversarial attacks.

problem Understanding the relationship between class selectivity and robustness in neural networks.
method Investigated the impact of class selectivity on robustness to natural corruptions and adversarial attacks using Tiny ImageNetC and CIFAR10C datasets.
result Decreasing class selectivity increases robustness to both natural corruptions and adversarial attacks.

Architecture optimization, which is a technique for finding an efficient neural network that meets certain requirements, generally reduces to a set of multiple-choice selection problems among alternative sub-structures or parameters. The discrete nature of the selection problem, however, makes this optimization difficu…

2019-04-24abs ↗pdf ↗

In May 2015, a conference entitled "Groups, Geometry, and 3-manifolds" was held at the University of California, Berkeley. The organizers asked participants to suggest problems and open questions, related in some way to the subject of the conference. These have been collected here, roughly divided by topic. The name (o…

2015-12-15abs ↗pdf ↗

In the present paper we prove Liouville-type theorems: non-existence theorems for conformal mappings of complete Riemannian manifolds. In addition, we give an application of these results to the theory of conharmonic transformations. A part of these results was announced in our reports on the conferences "Differential …

2016-08-04abs ↗pdf ↗

SAE-FiRE extracts key financial info from long documents, improving earnings surprise predictions.

problem Predicting earnings surprises from long, redundant financial documents.
method Sparse Autoencoder feature selection to filter out noise and identify key dimensions.
result SAE-FiRE significantly outperforms baseline approaches in financial datasets.

Lower class selectivity makes networks more robust to natural perturbations but more vulnerable to adversarial attacks.

problem Understanding how class selectivity affects robustness to different types of perturbations in neural networks.
method Investigated the relationship between class selectivity and robustness to natural and adversarial perturbations in neural networks.
result Lower class selectivity increases robustness to natural perturbations but decreases robustness to adversarial attacks.

A brief survey of real algebraic structures on topological spaces is given. This article is written for the Gokova Gemetry/Topology Conference proceedings.

2006-01-05abs ↗pdf ↗

As researchers and practitioners of applied machine learning, we are given a set of requirements on the problem to be solved, the plausibly obtainable data, and the computational resources available. We aim to find (within those bounds) reliably useful combinations of problem, data, and algorithm. An emphasis on algori…

2018-12-04abs ↗pdf ↗

These are notes based on a series of talks that the author gave at the "Interactions between hyperbolic geometry and quantum groups" conference held at Columbia University in June of 2009.

2010-03-05abs ↗pdf ↗

We give an overview of issues surrounding computer-verified theorem proving in the standard pure-mathematical context. This is based on my talk at the PQR conference (Brussels, June 2003).

2003-11-16abs ↗pdf ↗

The paper examines Adaptive Lasso and Transfer Lasso, highlighting their differences and proposing a new method.

problem Comparing and contrasting Adaptive Lasso and Transfer Lasso.
method Theoretical analysis of asymptotic properties and introduction of a new method.
result The Transfer Lasso method reduces non-asymptotic estimation errors compared to Adaptive Lasso.

The paper develops a decision support system for hierarchical text classification of conference proceedings.

problem Classifying documents with a fixed hierarchical structure of topics.
method Developed a weighted hierarchical similarity function to calculate topic relevance, using entropy of words to estimate weights.
result The weighted hierarchical similarity function improves ranking accuracy compared to other methods.

These notes are an expanded version of an introductory lecture on contact geometry given at the 2001 Georgia Topology Conference. They are intended to present some of the "topological" aspects of three dimensional contact geometry.

2001-11-09abs ↗pdf ↗

This note summarizes in an informal way some geometric properties of Anosov representations into the symplectic group, which were presented in a talk at the conference What is Next. The mathematical legacy of Bill Thurston, held in June 2014 in Cornell.

2016-02-10abs ↗pdf ↗

These lecture notes give an introduction to the Kahler-Ricci flow. They are based on lectures given by the authors at the conference "Analytic Aspects of Complex Algebraic Geometry", held at the Centre International de Rencontres Mathematiques in Luminy, in February 2011.

2012-12-15abs ↗pdf ↗

The NIPS 2018 Adversarial Vision Challenge is a competition to facilitate measurable progress towards robust machine vision models and more generally applicable adversarial attacks. This document is an updated version of our competition proposal that was accepted in the competition track of 32nd Conference on Neural In…

2018-08-06abs ↗pdf ↗

This is a survey of results on surfaces in noncommutative three-dimensional Lie groups obtained by using the Weierstrass (spinor) representation of surfaces. It is based on the talk given at the conference "Geometry related to the theory of integrable systems" (RIMS, Kyoto, September 2007).

2007-12-26abs ↗pdf ↗

Computer generated academic papers have been used to expose a lack of thorough human review at several computer science conferences. We assess the problem of classifying such documents. After identifying and evaluating several quantifiable features of academic papers, we apply methods from machine learning to build a b…

2010-08-04abs ↗pdf ↗

We survey some of the recent progress on complete gradient shrinking Ricci solitons, including the classifications in dimension three and asymptotic behavior of potential functions as well as volume growths of geodesic balls in higher dimensions. This article is written for the conference proceedings dedicated to Yau's…

2009-03-23abs ↗pdf ↗

This short note serves as a historical introduction to the Hopf problem: "Does there exist a complex structure on S6S^6?" This unsolved mathematical question was the subject of the Conference "MAM 1 - (Non-)Existence of Complex Structures on S6S^6", which took place at Philipps-Universität Marburg, Germany, between M…

2017-08-03abs ↗pdf ↗

Study finds incorporating fairness in healthcare models doesn't improve performance or net benefit.

problem Addressing health inequities in healthcare through algorithmic fairness.
method Empirical case study using models to estimate atherosclerotic cardiovascular disease risk.
result Incorporating fairness considerations into model training objective does not improve model performance or net benefit.