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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.

169,051 papers · 148 categories

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48 results for taste groups

TASTE combines static and temporal data for phenotyping EHRs.

problem Phenotyping EHRs with both static and temporal data.
method Jointly models static and temporal tensors using PARAFAC2 and non-negative matrix factorization, alternatingly solving sub-problems.
result TASTE outperforms existing methods in speed and clinical meaningfulness of phenotypes.

Study apple tasting feedback in online binary classification, providing new insights into minimax expected mistakes.

problem Online binary classification with partial feedback (apple tasting).
method Combinatorial analysis, Littlestone dimension, Effective width.
result Established a trichotomy of minimax expected mistakes in the realizable setting.

A deterministic apple tasting learner is developed, confirming a conjecture and providing tight bounds for mistake bounds.

problem Determining the learnability of hypothesis classes in binary online classification with apple tasting feedback.
method Developed a deterministic apple tasting learner and proved tight bounds for mistake bounds.
result Deterministic apple tasting is feasible and provides tight bounds for mistake bounds.

This work aims to separate buying preferences from merchandise commercials in fashion e-retail.

problem Difficult to infer customer preference from sales data due to implicit signals.
method Extends earlier work on explicit signals to implicit signals from user behavior.
result Derives a metric to separate buying preferences from merchandise commercials.

Convolutional autoencoders improve personalized recommendations from image-based data.

problem Lack of personalized recommendations in gastronomic platforms using image data.
method Used convolutional autoencoders to extract features from images and improve personalized recommendations.
result Convolutional autoencoders outperform standard deep features in image-based personalized recommendation systems.

This study examines how fashion consumption affects self-confidence and buying behavior in Iranian consumers.

problem Understanding the role of self-confidence in fashion buying behavior.
method A questionnaire was used to collect data from 400 consumers in Tehran's clothing market. Structural equations and factor analysis were employed to test the model.
result Interest in fashion, personal taste, utilitarianism, and new products positively impact self-confidence, and self-confidence positively impacts fashion buying behavior.

The aim of this short lecture series is to expose the students to the beautiful theory of lattices by, on one hand, demonstrating various basic ideas that appear in this theory and, on the other hand, formulating some of the celebrated results which, in particular, shows some connections to other fields of mathematics.…

2014-02-05abs ↗pdf ↗

Social interactions and personal tastes shape our consumption behavior of cultural products. In this study, we present a computational model of a cultural market and we aim to analyze the behavior of the consumer population as an emergent phenomena. Our results suggest that the final market shares of cultural products …

2007-07-16abs ↗pdf ↗

Bounded cohomology of groups was first defined by Johnson and Trauber during the seventies in the context of Banach algebras. As an independent and very active research field, however, bounded cohomology started to develop in 1982, thanks to the pioneering paper "Volume and Bounded Cohomology" by M. Gromov, where the d…

2016-10-26abs ↗pdf ↗

We introduce negative binomial matrix factorization (NBMF), a matrix factorization technique specially designed for analyzing over-dispersed count data. It can be viewed as an extension of Poisson matrix factorization (PF) perturbed by a multiplicative term which models exposure. This term brings a degree of freedom fo…

2018-01-05abs ↗pdf ↗

The need for diversification of recommendation lists manifests in a number of recommender systems use cases. However, an increase in diversity may undermine the utility of the recommendations, as relevant items in the list may be replaced by more diverse ones. In this work we propose a novel method for maximizing the u…

2014-11-13abs ↗pdf ↗

An evolutionary game model analyzes e-commerce and traditional retail trends during the pandemic.

problem Understanding the dynamics between e-commerce and traditional retail during the pandemic.
method Developed an evolutionary game model to study consumer-producer interactions on e-commerce platforms.
result Investment in logistics and warehouses in e-commerce led to faster delivery and consumer trends.

Item cold-start is a classical issue in recommender systems that affects anime and manga recommendations as well. This problem can be framed as follows: how to predict whether a user will like a manga that received few ratings from the community? Content-based techniques can alleviate this issue but require extra infor…

2017-09-03abs ↗pdf ↗

A model for learning customer preferences in a dynamic product launch setting.

problem Learning customer preferences in a setting with new product launches.
method Proposes a sequential multinomial logit (SMNL) model and a learning algorithm with a regret bound.
result Demonstrates the tier structure can mitigate risks associated with learning new products.

This paper enhances privacy-preserving randomized power method for large datasets.

problem Privacy issues in applying randomized power method to large datasets containing personal information.
method Proposes enhanced privacy-preserving variants of the randomized power method, including a variant with reduced noise and a decentralized framework.
result Tighter convergence bounds and empirical comparisons with previous work in real recommendation datasets.

Many machine learning applications are based on data collected from people, such as their tastes and behaviour as well as biological traits and genetic data. Regardless of how important the application might be, one has to make sure individuals' identities or the privacy of the data are not compromised in the analysis.…

2016-10-27abs ↗pdf ↗

Study on tracking preference shifts in dueling bandits problems.

problem Tracking significant preference shifts in dueling bandits problems.
method Analysis of dueling bandits with distribution shifts, focusing on significant shifts (Suk and Kpotufe, 2022).
result Design of adaptive algorithms with O(KildeLT)O(\sqrt{K ilde{L}T}) dynamic regret for certain preference distribution classes.

Deep neural network predicts product returns before purchase.

problem High costs of handling returned fashion products.
method Bayesian Personalized Ranking (BPR) embeddings and skip-gram model for user and product features.
result Reduced overall returns through real-time return probability prediction.

Unified neural framework for multi-relational recommender systems.

problem Accurately capturing users' fine-grained preferences from diverse feedback types.
method Multi-Relational Memory Network (MRMN) framework that models fine-grained user-item relations and discriminates between feedback types.
result The proposed MRMN model outperforms state-of-the-art algorithms in various recommender scenarios.

We present a mixed multinomial logit (MNL) model, which leverages the truncated stick-breaking process representation of the Dirichlet process as a flexible nonparametric mixing distribution. The proposed model is a Dirichlet process mixture model and accommodates discrete representations of heterogeneity, like a laten…

2018-01-19abs ↗pdf ↗

Machine learning and topological data analysis identify unique geometric and topological features of human papillae.

problem Identifying unique features of human papillae across individuals.
method 3D microscopic scans, machine learning, discrete differential geometry, computational topology, persistent homology.
result Persistent homology features of papillae shape predict papillae type with high accuracy and can identify individuals with high accuracy.

This paper solves optimal consumption-investment problems with time-varying preferences.

problem Optimal consumption-investment problems under time-varying incomplete preferences.
method Develops a martingale-type solution in a topological vector space, using stochastic processes and scalarization methods.
result Optimal investment policies are set-valued, with selectors decomposed into four components.

VB methods improve MMNL estimation speed and accuracy.

problem Scalable Bayesian estimation of MMNL models.
method Extending VB methods to include both fixed and random utility parameters, and conducting extensive simulations.
result VB methods, especially VB-NCVMP-Delta, are up to 16 times faster than MCMC and MSLE while maintaining similar accuracy.

Paper uses machine learning to model travel mode switching under a new transit system.

problem Modeling individual travel mode preferences and response to new mobility options.
method Interpretable machine learning approach to predict and interpret mode-switching behavior.
result Machine learning captures individual heterogeneity in travel mode choice.

New link groups are derived from torus necklaces, connecting braid groups to reflection groups.

problem Understanding the relationship between braid groups and reflection groups.
method Constructing torus necklaces and linking them to braid groups of JJ-reflection groups.
result Link groups of torus necklaces are precisely braid groups of JJ-reflection groups, with meridians as braid reflections.

Computes cohomology groups for NEC groups, focusing on Fuchsian groups.

problem Understanding the cohomology of non-Euclidean crystallographic groups.
method Computes cohomology groups for geometrically finite NEC groups, and determines the ring structure for Fuchsian groups.
result Determination of cohomology groups and ring structures for Fuchsian groups.

The study proves super-rigidity of Gromov's random monster group for various types of groups.

problem Super-rigidity of Gromov's random monster group in various group types.
method Proof of morphisms having finite image and introduction of hereditary super-rigidity.
result Gromov's random monster group has super-rigidity and hereditary super-rigidity with respect to certain groups.

We study the structure of the virtual braid group. It is shown that the virtual braid group is a semi--direct product of the virtual pure braid group and the symmetric group. Also, it is shown that the virtual pure braid group is a semi--direct product of free groups. From these results we obtain a normal form of words…

2004-07-23abs ↗pdf ↗

Virtual twin groups map to symmetric groups, revealing automorphism structure.

problem Understanding homomorphisms between virtual twin groups and symmetric groups.
method Using irreducible right-angled Coxeter groups and right-angled Artin groups.
result A complete description of homomorphisms between virtual twin groups and symmetric groups, including the structure of the automorphism group of VTnVT_n.

The study restricts groups in graph of groups structures.

problem Realizing groups as fundamental groups of graph of groups with restricted vertex groups.
method Analyzes restrictions on groups that can be realized and applies to manifold construction.
result Places constraints on groups that can be realized in graph of groups structures.

New Garside structures found for torus knot groups and related braid groups.

problem Finding Garside structures for torus knot groups and related braid groups.
method Introducing a new Garside monoid M(n,m)\mathcal{M}(n,m) for (n,m)(n,m)-torus knot groups and other braid groups.
result New Garside structures for (n,m)(n,m)-torus knot groups and related braid groups are constructed.

Logarithmic separation profile in hyperbolic groups shows hierarchical structure.

problem Understanding hierarchical structure in hyperbolic groups with logarithmic separation.
method Proving groups with logarithmic separation split over cyclic groups and providing counterexamples.
result Not all groups with hierarchical structure have logarithmic separation profile.

We describe a procedure for constructing a generalized Thompson group out of a family of groups that is equipped with what we call a cloning system. The previously known Thompson groups F, V, Vbr and Fbr arise from this procedure using, respectively, the systems of trivial groups, symmetric groups, braid groups and pur…

2014-05-21abs ↗pdf ↗

The study restricts normal subgroups of Kähler groups, proving specific cases and general restrictions.

problem Characterizing normal subgroups of Kähler groups.
method Analyzing embeddings and conjugation actions of surface groups and one-ended hyperbolic groups.
result Restrictions on normal subgroups of Kähler groups, including virtual direct products and surface group properties.