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.
Study identifies pitfalls in assessing hierarchies for multi-class classification.
We combine geometric data analysis and stochastic modeling to describe the collective dynamics of complex systems. As an example we apply this approach to financial data and focus on the non-stationarity of the market correlation structure. We identify the dominating variable and extract its explicit stochastic model. …
Deep Boltzmann machines are in principle powerful models for extracting the hierarchical structure of data. Unfortunately, attempts to train layers jointly (without greedy layer-wise pretraining) have been largely unsuccessful. We propose a modification of the learning algorithm that initially recenters the output of t…
We introduce a graph-theoretic approach to extract clusters and hierarchies in complex data-sets in an unsupervised and deterministic manner, without the use of any prior information. This is achieved by building topologically embedded networks containing the subset of most significant links and analyzing the network s…
Concept Hierarchies and Formal Concept Analysis are theoretically well grounded and largely experimented methods. They rely on line diagrams called Galois lattices for visualizing and analysing object-attribute sets. Galois lattices are visually seducing and conceptually rich for experts. However they present important…
New method improves blackbox attack transferability by perturbing feature hierarchy.
This study proposes an exercise fatigue detection model based on real-time clinical data which includes time domain analysis, frequency domain analysis, detrended fluctuation analysis, approximate entropy, and sample entropy. Furthermore, this study proposed a feature extraction method which is combined with an analyti…
Generative model reveals hidden interaction preferences in networks.
Proposes a neural network for accurate and reconciled hierarchical time series forecasting.
The study of hierarchy in networks of the human brain has been of significant interest among the researchers as numerous studies have pointed out towards a functional hierarchical organization of the human brain. This paper provides a novel method for the extraction of hierarchical connectivity components in the human …
With the introduction of the variational autoencoder (VAE), probabilistic latent variable models have received renewed attention as powerful generative models. However, their performance in terms of test likelihood and quality of generated samples has been surpassed by autoregressive models without stochastic units. Fu…
We study the structure of inter-industry relationships using networks of money flows between industries in 20 national economies. We find these networks vary around a typical structure characterized by a Weibull link weight distribution, exponential industry size distribution, and a common community structure. The comm…
FOSC-X: An extended framework for extracting multiple optimal flat clusterings from hierarchical cluster trees
Latent variable models for network data extract a summary of the relational structure underlying an observed network. The simplest possible models subdivide nodes of the network into clusters; the probability of a link between any two nodes then depends only on their cluster assignment. Currently available models can b…
This paper presents a novel approach to exploit the distinctive invariant features in convolutional neural network. The proposed CNN model uses Scale Invariant Feature Transform (SIFT) descriptor instead of the max-pooling layer. Max-pooling layer discards the pose, i.e., translational and rotational relationship betwe…
Novel Lie-superalgebraic description of superstring dynamics.
New method calculates Thurston norm for 3-manifolds with toroidal boundaries.
In this paper, we compare various methods to compress a text using a neural model. We find that extracting tokens as latent variables significantly outperforms the state-of-the-art discrete latent variable models such as VQ-VAE. Furthermore, we compare various extractive compression schemes. There are two best-performi…
We propose a hierarchical correlation clustering method that extends the well-known correlation clustering to produce hierarchical clusters applicable to both positive and negative pairwise dissimilarities. Then, in the following, we study unsupervised representation learning with such hierarchical correlation clusteri…
Proposes cone embedding for better graph hierarchical structure representation.
Adversarial MoE learns category-specific models for product search.
Constructs integrable hierarchies for generalized Frobenius manifolds with non-flat unity.
Solves the challenge of retrieving item-specific financial information from Form 10-Q filings.
A new framework for deep matrix factorizations improves model consistency and flexibility.
Paper proposes integrating hierarchical class structure into prototypical network supervision.
Super tau-covers extend bihamiltonian hierarchies' symmetries.
Hydrodynamic hierarchy deformed using conservation laws.
Paper tackles many-class few-shot learning with class hierarchy, improving accuracy.
Legendre transformations link related integrable hierarchies.
Twisted - and twisted -hierarchies are soliton hierarchies introduced by Terng to find higher flows of the generalized sine-Gordon equation. Twisted -hierarchies are among the most important classes of twisted hierarchies. In this paper, interesting first and higher flows of twi…
The bundle approach and n-contextuality reveal quantum model contextuality.
Derive bihamiltonian structure for rational reduction of 2D-Toda hierarchy
We propose a formally completely integrable extension of heat hierarchy based on the space of symmetries isomorphic to the Weyl algebra . The extended heat hierarchy will be the basic model for the analysis of the extension of KP hierarchy, and other integrable equations.
Wise's Quasiconvex Hierarchy Theorem classifying hyperbolic virtually compact special groups in terms of quasiconvex hierarchies played an essential role in Agol's proof of the Virtual Haken Conjecture. Answering a question of Wise, we construct a new virtual quasiconvex hierarchy for relatively hyperbolic virtually co…
New hierarchies derived from KP hierarchy using non-formal operators and Yang-Mills action.
Wikipedia is a huge opportunity for machine learning, being the largest semi-structured base of knowledge available. Because of this, many works examine its contents, and focus on structuring it in order to make it usable in learning tasks, for example by classifying it into an ontology. Beyond its textual contents, Wi…
Symmetry reduction of Painlevé IV to Flaschka-Newell Painlevé II
Scroll structures on solutions of 4D integrable equations are involutive and governed by a dispersionless hierarchy.
A relation between the Goldstein-Petrich hierarchy for plane curves and the Toda lattice hierarchy is investigated. A representation formula for plane curves is given in terms of a special class of -functions of the Toda lattice hierarchy. A representation formula for discretized plane curves is also discussed.
Constructs tri-Hamiltonian structure and Frobenius manifold for asymmetric gAL hierarchy
New integrable deformations for topological hierarchies from Frobenius manifolds.
We introduce two families of soliton hierarchies: the twisted hierarchies associated to symmetric spaces. The Lax pairs of these two hierarchies are Laurent polynomials in the spectral variable. Our constructions gives a hierarchy of commuting flows for the generalized sine-Gordon equation (GSGE), which is the Gauss-Co…
Paper investigates methods to improve classification by inducing a hierarchy from flat labels.
We compute the central invariants of the bihamiltonian structures of the constrained KP hierarchies, and show that these integrable hierarchies are topological deformations of their hydrodynamic limits.
We prove that the extended Toda hierarchy of \cite{CDZ} admits nonabelian Lie algebra of infinitesimal symmetries isomorphic to the half of the Virasoro algebra. The generators , of the Lie algebra act by linear differential operators onto the tau function of the hierarchy. We also prove that the tau fu…
Paper addresses limitations of traditional hierarchical clustering methods.
We present the Lax pair formalism for certain extension of the continuous limit of the classical Toda lattice hierarchy, provide a well defined notion of tau function for its solutions, and give an explicit formulation of the relationship between the topological sigma model and the extended Toda hierarchy. We al…
New diffiety theory leads to a well-posed KP hierarchy.