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.
In this paper, the concept of balanced manifolds is generalized to reduced complex spaces: the class B and balanced spaces. Compared with the case of Kahlerian, the class B is similar to the Fujiki class C and the balanced space is similar to the Kahler space. Some properties about these complex spaces are obtained, an…
Three elements generate balanced superelliptic mapping class groups.
Finite presentations for mapping class groups of surfaces and surfaces with points/boundaries.
Study of transformations in 3-manifolds with boundary and their equivalence classes.
Proves a minimal generating set for a specific group of mapping classes.
The hyperelliptic mapping class group has been studied in various contexts within topology and algebraic geometry. What makes this study tractable is that there is a surjective map from the hyperelliptic mapping class group to a mapping class group of a punctured sphere. The more general family of superelliptic mapping…
Active learning method balances bias and variance under class imbalance.
TKIL improves class-balanced performance in incremental learning.
The study examines whether a specific type of hyperbolic manifolds remains unchanged under birational transformations.
Paper proposes ARB-Loss to improve classification precision in imbalanced datasets.
New approach tackles class imbalance in long-tailed datasets using domain adaptation techniques.
The paper broadens a mathematical correspondence to include more balanced metrics.
CBDA improves active learning for semantic segmentation, especially with imbalanced classes.
Solutions to Strominger system found for square of Kähler class.
Study reveals class disparities in balanced datasets through spectral imbalance.
Optimizes Metropolis-Hastings algorithms for efficient sampling in high dimensions.
This paper introduces new loss functions for balanced multi-class classification.
Blowing up flat metrics yields balanced ones with constant curvature.
New findings on 3-manifolds using Heegaard Floer theory.
A modified GAN improves thermal comfort classification models by balancing imbalanced datasets.
Random Forest variable importance is improved by class balancing techniques.
Image classification datasets are often imbalanced, characteristic that negatively affects the accuracy of deep-learning classifiers. In this work we propose balancing GAN (BAGAN) as an augmentation tool to restore balance in imbalanced datasets. This is challenging because the few minority-class images may not be enou…
A new sampling method balances imbalanced data using gamma distribution.
Survey on Strominger system and Ricci flow in non-Kähler geometry.
Accuracies of survival models for life expectancy prediction as well as critical-care applications are significantly compromised due to the sparsity of samples and extreme imbalance between the survival (usually, the majority) and mortality class sizes. While a recent random survival forest (RSF) model overcomes the li…
We show that an dimensional Moishezon manifold is uniruled if and only if it supports a balanced metric of positive total scalar Chern curvature. A similar statement also holds true for class manifolds of dimension three.
In real-world classification problems, the class balance in the training dataset does not necessarily reflect that of the test dataset, which can cause significant estimation bias. If the class ratio of the test dataset is known, instance re-weighting or resampling allows systematical bias correction. However, learning…
We study the existence of three classes of Hermitian metrics on certain types of compact complex manifolds. More precisely, we consider balanced, SKT and astheno-Kähler metrics. We prove that the twistor spaces of compact hyperkähler and negative quaternionic-Kähler manifolds do not admit astheno-Kähler metrics. Then w…
We study the quantization of coupled Kähler-Einstein (CKE) metrics, namely we approximate CKE metrics by means of the canonical Bergman metrics, so called the ``balanced metrics''. We prove the existence and weak convergence of balanced metrics for the negative first Chern class, while for the positive first Chern clas…
BOSS learns from one labeled sample per class to match fully supervised performance.
We develop an axiomatic theory of balance functions (future value functions) in the theory of interest that is derived from financial considerations and which applies to general regulated payment streams, including continuous payment streams. Balance functions exist and are unique up to an initial choice of deposit and…
While tasks could come with varying the number of instances and classes in realistic settings, the existing meta-learning approaches for few-shot classification assume that the number of instances per task and class is fixed. Due to such restriction, they learn to equally utilize the meta-knowledge across all the tasks…
The performance of classification algorithms with a massive and highly imbalanced data stream depends upon efficient balancing strategy. Some techniques of balancing strategy have been applied in the past with Batch data to resolve the class imbalance problem. This paper proposes a new incremental data balancing framew…
The paper addresses classification imbalance by framing it as a transfer learning problem.
Kronheimer and Mrowka defined invariants of balanced sutured manifolds using monopole and instanton Floer homology. Their invariants assign isomorphism classes of modules to balanced sutured manifolds. In this paper, we introduce refinements of these invariants which assign much richer algebraic objects called projecti…
In this paper, we consider a natural map from the Kahler cone to the balanced cone of a Kahler manifold. We study its injectivity and surjecticity. We also give an analytic characterization theorem on a nef class being Kahler.
The paper proves conditions for compact complex manifolds to be Kahler outside analytic subsets.
The Synthetic Minority Oversampling TEchnique (SMOTE) is widely-used for the analysis of imbalanced datasets. It is known that SMOTE frequently over-generalizes the minority class, leading to misclassifications for the majority class, and effecting the overall balance of the model. In this article, we present an approa…
AANets balance stability and plasticity in CIL.
Paper simplifies balancing weights by relaxing outcome assumptions.
Study examines how balancing methods affect model behavior in imbalanced classification problems.
It has been recently shown that a large class of balanced graph cuts allows for an exact relaxation into a nonlinear eigenproblem. We review briefly some of these results and propose a family of algorithms to compute nonlinear eigenvectors which encompasses previous work as special cases. We provide a detailed analysis…
We prove a general criterion to establish existence and uniqueness of a short-time solution to an evolution equation involving "closed" sections of a vector bundle, generalizing a method used recently by Bryant and Xu for studying the Laplacian flow in G_2-geometry. We apply this theorem in balanced geometry introducin…
C-VAE improves class representation in long-tailed generative models.
IB-GAN improves multivariate time series classification under imbalance.
The paper analyzes systoles of complex projective spaces under various metrics.
Study on existence of balanced metrics on non-Kähler manifolds.
Motivated from mathematical aspects of the superstring theory, we introduce a new equation on a balanced, hermitian manifold, with zero first Chern class. Solving the equation, one will obtain, in each Bott--Chern cohomology class, a balanced metric which is hermitian Ricci--flat. This can be viewed as a differential f…