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.
RELARM uses relative PCA attributes and k-means clustering for object rating.
The paper introduces relative objects and proves a transversality theorem.
OGRePy simplifies tensor calculations in general relativity.
Proposes a new objective function to learn robust deep features.
The outlying property detection problem is the problem of discovering the properties distinguishing a given object, known in advance to be an outlier in a database, from the other database objects. In this paper, we analyze the problem within a context where numerical attributes are taken into account, which represents…
Proposes a multi-objective Q-network for dynamic weights in deep RL.
OGRe simplifies tensor calculations in general relativity.
New perspective on Sinkhorn algorithm using stochastic mirror descent.
Adapts GRPO for off-policy RL, improving reward.
New algorithms optimize without knowing problem parameters.
The alignment of a set of objects by means of transformations plays an important role in computer vision. Whilst the case for only two objects can be solved globally, when multiple objects are considered usually iterative methods are used. In practice the iterative methods perform well if the relative transformations b…
MO-CBO optimizes multiple outcomes in causal systems with minimal data.
The concept of an objective spatial direction in special relativity is investigated and theories assuming light-speed isotropy while accepting the existence of a privileged spatial direction are classified. A natural generalization of the proper time principle is introduced which makes it possible to devise experimenta…
Paper tackles object detection in limited data scenarios.
The paper extends trisection theory to 4-manifolds with multiple boundary components.
Using the language and terminology of relative homological algebra, in particular that of derived functors, we introduce equivariant cohomology over a general Lie-Rinehart algebra and equivariant de Rham cohomology over a locally trivial Lie groupoid in terms of suitably defined monads (also known as triples) and the a…
Simple object representations improve model-free RL performance.
Extends specific relative entropy to multidimensional continuous martingales.
An estimate on the number of distinct relative periodic orbits around a stable relative equilibrium in a Hamiltonian system with continuous symmetry is given. This result constitutes a generalization to the Hamiltonian symmetric framework of a classical result by Weinstein and Moser on the existence of periodic orbits …
In this paper, we have tried to apply the concepts of fuzzy sets to Lie groups and its relative concepts. First, we define a fuzzy submanifold after reviewing fuzzy manifold definition. In main section, we defined the Lie group and some its relative concepts such as fuzzy transformation group,…
Study equivariant vector fields near relative equilibria using isomorphic categories.
The algebra of transactions as fundamental measurements is constructed on the basis of the analysis of their properties and represents an expansion of the Boolean algebra. The notion of the generalized economic measurements of the economic quantity and quality of objects of transactions is introduced. It has been shown…
Improved object classification with voxel-based models.
Simplified approach to Galois theories in category theory.
Survey on a nonlinear d'Alembertian from general relativity.
MPO optimizes policies using relative entropy, outperforming existing methods in reinforcement learning.
A refined form of the `Folk Theorem' that a smooth action by a compact Lie group can be (canonically) resolved, by iterated blow up, to have unique isotropy type was established by the authors in the context of manifolds with corners; the canonical construction induces fibrations on the boundary faces of the resolution…
Two entropy measures quantify suboptimal portfolio performance.
The `Folk Theorem' that a smooth action by a compact Lie group can be (canonically) resolved, by iterated blow up, to have unique isotropy type is proved in the context of manifolds with corners. This procedure is shown to capture the simultaneous resolution of all isotropy types in a `resolution tower' which projects …
Generative model learns to compose images of objects from different distributions.
This document contains a description of physics entirely based on a geometric presentation: all of the theory is described giving only a pseudo-riemannian manifold (M, g) of dimension n > 5 for which the g tensor is, in studied domains, almost everywhere of signature (-, -, +, ..., +). No object is added to this space-…
Develops a new method to improve performance in multi-objective learning problems.
This paper presents a simple but effective density-based outlier detection approach with the local kernel density estimation (KDE). A Relative Density-based Outlier Score (RDOS) is introduced to measure the local outlierness of objects, in which the density distribution at the location of an object is estimated with a …
Generative model generates images with multiple object classes.
The objective of change-point detection is to discover abrupt property changes lying behind time-series data. In this paper, we present a novel statistical change-point detection algorithm based on non-parametric divergence estimation between time-series samples from two retrospective segments. Our method uses the rela…
The approximation of nonlinear kernels via linear feature maps has recently gained interest due to their applications in reducing the training and testing time of kernel-based learning algorithms. Current random projection methods avoid the curse of dimensionality by embedding the nonlinear feature space into a low dim…
Rigidity theorem shows massless hyperboloidal data embeds into Minkowski space.
We define an order relation among oriented -complexes. We show that with respect to this relation, two -complexes over the same complex are homotopy equivalent if and only if there is an isometry between the second homology groups. We also consider minimal objects of this relation.
This paper optimizes trading strategies to minimize risk and maximize profit while accounting for market uncertainty.
Paper proposes energy objective for training normalizing flows without determinants.
KeypointNet learns 3D keypoints for object pose estimation without ground-truth.
Study finds RVIs unreliable for SP selection in clustering.
We propose an extension of the concept of Expected Improvement criterion commonly used in Kriging based optimization. We extend it for more complex Kriging models, e.g. models using derivatives. The target field of application are CFD problems, where objective function are extremely expensive to evaluate, but the theor…
Spin networks are at the core of quantum gravity. Our aim is to plug the mathematical community at large into the procedures turn to create a finite quantum theory of general relativity. For this, because of the different cultural backgraund, we would like to change the tack: to relate discrete (combinatorial) objects …
The paper proposes a method to learn 3D object pose manifolds using GANs and elasticae.
A novel UNet detector detects sheep in UAV imagery.
Machine learning classifies object code for target architecture and endianess.
VBTA learns across domains using triplet information.