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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.

169,181 papers · 148 categories

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48 results for complete minors

Paper determines Assouad-Nagata dimension for all minor-closed metrics.

problem Understanding the Assouad-Nagata dimension of minor-closed metrics.
method Using edge-weighted graphs and edge-deletion/contraction to model minor-closed metrics, determining their Assouad-Nagata dimension.
result Determined the Assouad-Nagata dimension for every minor-closed metric.

The complement of a non-separating planar graph contains a K_n minor.

problem Characterizing the structure of complements of planar graphs.
method Analyzing the structure of complements of non-separating planar graphs and using examples to illustrate hypotheses.
result The order 2n-3 is the lowest possible for a non-separating planar graph whose complement contains a K_n minor.

We show that the 14 graphs obtained by Y\nabla\mathrm{Y} moves on K_7 constitute a complete list of the minor minimal intrinsically knotted graphs on 21 edges. We also present evidence in support of a conjecture that the 20 graph Heawood family, obtained by a combination of Y\nabla\mathrm{Y} and Y\mathrm{Y}\nabla mo…

2013-03-27abs ↗pdf ↗

We say that a graph is intrinsically knotted or completely 3-linked if every embedding of the graph into the 3-sphere contains a nontrivial knot or a 3-component link any of whose 2-component sublink is nonsplittable. We show that a graph obtained from the complete graph on seven vertices by a finite sequence of $\tria…

2010-06-03abs ↗pdf ↗

We construct a new type of geometric knot theory, plumbers' knots, and solve the problems of distinguishing and enumerating such knots at a fixed level of complexity. (v2) Minor edits, added theorem 3.18. (v3) Substantial revisions, essentially completely rewritten in places.

2008-11-13abs ↗pdf ↗

Paper studies asymptotic dimension and Assouad-Nagata dimension of graphs and surfaces.

problem Understanding the asymptotic dimension and Assouad-Nagata dimension of graphs and surfaces.
method Analyzes asymptotic dimension of graph metrics and applies to surfaces, proving dimension bounds.
result Proves that complete Riemannian surfaces have Assouad-Nagata dimension at most 2.

A graph is intrinsically knotted if every embedding contains a knotted cycle. It is known that intrinsically knotted graphs have at least 21 edges and that the KS graphs, K7K_7 and the 13 graphs obtained from K7K_7 by Y\nabla Y moves, are the only minor minimal intrinsically knotted graphs with 21 edges. This set incl…

2014-11-07abs ↗pdf ↗

In this paper we consider minors of ribbon graphs (or, equivalently, cellularly embedded graphs). The theory of minors of ribbon graphs differs from that of graphs in that contracting loops is necessary and doing this can create additional vertices and components. Thus the ribbon graph minor relation is incompatible wi…

2013-11-09abs ↗pdf ↗

We prove two results on the classification of trivial Legendrian embeddings g:G(S3,ξstd)g: G \rightarrow (S^3,ξ_{std}) of planar graphs. First, the oriented Legendrian ribbon RgR_g and rotation invariant rotg\text{rot}_g are a complete set of invariants. Second, if GG is 3-connected or contains K4K_4 as a minor, then the unique t…

2016-04-04abs ↗pdf ↗

A new oversampling framework generates minority samples by perturbing majority classes.

problem Oversampling in imbalanced classification often neglects majority classes, leading to samples spread across the minority space.
method Introduces a counterfactual objective to generate new minority samples by perturbing majority samples.
result Generated minority samples are near the decision boundary and significantly outperform state-of-the-art methods.

Every infinitely edge-connected graph has a minor of Farey graph or T0tT_{\aleph_0}\ast t.

problem Characterizing edge-connected graphs with specific minor properties.
method Analyzing the minor structure of infinitely edge-connected graphs.
result Infinitely edge-connected graphs contain Farey graph or T0tT_{\aleph_0}\ast t as a minor.

Boost-and-Skip generates minority samples without guidance, faster and more effectively.

problem Generating minority samples in low-density regions of a data manifold.
method Boost-and-Skip approach with variance-boosted initialization and timestep skipping.
result Boost-and-Skip effectively promotes the emergence of underrepresented minority features.

In this paper we study the continuum time dynamics of a stock in a market where agents behavior is modeled by a Minority Game and a Grand Canonical Minority Game. The dynamics derived is a generalized geometric Brownian motion; from the Black & Scholes formula the calibration of both the Minority Game and the Grand Can…

2012-05-11abs ↗pdf ↗

This paper gives a critical account of the minority game literature. The minority game is a simple congestion game: players need to choose between two options, and those who have selected the option chosen by the minority win. The learning model proposed in this literature seems to differ markedly from the learning mod…

2007-06-29abs ↗pdf ↗

A new method improves fault diagnostics and prognostics for class-imbalanced data.

problem Class imbalance in industrial fault diagnostics and prognostics.
method EWMOTE: EM-based Weighted Minority Oversampling TEchnique.
result EWMOTE achieves better performance on binary and multi-class imbalance learning tasks.

Minor typographical errors fixed. Cochran constructed many links with Alexander module that of the unlink and some nonvanishing Milnor invariants, using as input commutators in a free group and as an invariant the longitudes of the links. We present a different and conjecturally complete construction, that uses element…

2002-06-19abs ↗pdf ↗

The paper is partially withdrawn: in its current form, Lemma 2.3 is false, so that our proof of Theorem A and Proposition B has an important gap. We were unable to fix it yet. Any help is most welcome. We prove that the restriction of surface minority to fiber surfaces of divides is a well-quasi-order. Here surface min…

2012-11-30abs ↗pdf ↗

Overparameterized models can worsen minority group errors even when overall test error improves.

problem Overparameterization exacerbates spurious correlations, harming minority groups.
method Simulations and experiments on image datasets, theoretical analysis of linear models.
result Subsampling the majority group can achieve low minority error in overparameterized models.

We introduce the minority game theory for two kinds of the Korean treasury bond (KTB) in Korean futures exchange markets. Since we discuss numerically the standard deviation and the global efficiency for an arbitrary strategy, our case is found to be approximate to the majority game. Our result presented will be compar…

2005-03-01abs ↗pdf ↗

GenSample uses genetic algorithms to improve minority class classification in imbalanced datasets.

problem Poor classification performance on minority class in imbalanced datasets.
method GenSample uses genetic algorithms to oversample minority class, considering difficulty and performance improvement.
result GenSample achieved the highest F-Score on 8 out of 9 real-world imbalanced datasets.

M2m method improves deep learning performance on class-imbalanced datasets.

problem Class imbalance in labeled training datasets causes deep neural networks to generalize poorly to minority classes.
method Augment less-frequent classes by translating samples from more-frequent classes.
result Significantly improves generalization on minority classes compared to existing methods.

LoRAS improves model performance on imbalanced datasets by better oversampling the minority class.

problem Imbalanced datasets lead to poor model performance, especially for the majority class.
method Localized Random Affine Shadowsampling (LoRAS) to oversample minority class data.
result LoRAS generates better ML models in terms of F1-Score and Balanced accuracy compared to SMOTE and its extensions.

Framework learns to transform majority to minority samples for balanced classification.

problem Imbalanced classification leading to biased predictions.
method Minimizes MMD and uses triplet loss for global alignment and boundary awareness.
result Consistent improvements over classical and generative baselines in AUROC, G-mean, F1-score, and MCC.

Well-quasi-order proved for plane minors; polynomial-time algorithm for link diagrams.

problem Proving the well-quasi-order of plane minors and solving link diagrams.
method Sequence of vertex and edge deletions and contractions to prove well-quasi-order; polynomial-time algorithm for link diagrams.
result Well-quasi-order of plane minors established; polynomial-time algorithm for link diagrams.

Develops a new synthetic minority oversampling technique for imbalanced learning.

problem Imbalanced learning in classification models.
method Generates synthetic samples using Gaussian Mixture Model in high-dimensional space, filters outliers, and optimizes parameters.
result An effective and efficient imbalanced learning framework is developed.

Decision trees can be biased towards minority class, contrary to belief.

problem Bias in decision trees towards minority class in imbalanced datasets.
method Critical evaluation of past literature, specific conditions analysis, tree-fitting adjustments, and post-hoc calibration methods.
result Decision trees can be biased towards minority class under specific conditions, not always towards majority.