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.
The paper calculates asymptotic expansions for specific types of oscillatory integrals.
Approximations to utility indifference prices are provided for a contingent claim in the large position size limit. Results are valid for general utility functions on the real line and semi-martingale models. It is shown that as the position size approaches infinity, the utility function's decay rate for large negative…
Signed graphs encode positive (attractive) and negative (repulsive) relations between nodes. We extend spectral clustering to signed graphs via the one-parameter family of Signed Power Mean Laplacians, defined as the matrix power mean of normalized standard and signless Laplacians of positive and negative edges. We pro…
Neural Power Unit (NPU) learns arbitrary power functions on real numbers.
Study of metrics on positive-definite matrices from power potential, linking to power means.
The study revises GDPpc trends and redistributes economic power among countries.
By combining (i) the economic theory of rational expectation bubbles, (ii) behavioral finance on imitation and herding of investors and traders and (iii) the mathematical and statistical physics of bifurcations and phase transitions, the log-periodic power law (LPPL) model has been developed as a flexible tool to detec…
In this paper, we consider the contracting curvature flow of smooth closed surfaces in -dimensional hyperbolic space and in -dimensional sphere. In the hyperbolic case, we show that if the initial surface has positive scalar curvature, then along the flow by a positive power of the mean curvature , t…
Modeling solar ramping events with spatio-temporal point processes.
We study the evolution of convex complete non-compact graphs by positive powers of Gauss curvature. We show that if the initial complete graph has a local uniform convexity, then the graph evolves by any positive power of Gauss curvature for all time. In particular, the initial graph is not necessarily differentiable.
A new model detects financial bubbles with high accuracy.
This paper explores GNN functions on random graphs, highlighting the importance of node Positional Encodings.
Fast algorithm recovers principal eigenvector from noisy matrices.
Study asymptotics of extension and orthogonal Bergman kernels for high tensor powers of positive line bundles.
A neural network for online NP classification with reduced complexity.
The paper counts conjugacy classes of loxodromic elements in Anosov subgroups with a power saving error term.
We study convex entire graphs evolving with normal velocity equal to a positive power of the mean curvature. Under mild assumptions we prove longtime existence.
In this paper, we study the power of Gaussian curvature flow of a compact convex hypersurface and establish its Harnack inequality when the power is negative. In the Harnack inequality, we require that the absolute value of the power is strictly positive and strictly less than the inverse of the dimension of the hypers…
We generalize the results of Montgomery for the Bochner Laplacian on high tensor powers of a line bundle. When specialized to Riemann surfaces, this leads to the Bergman kernel expansion and geometric quantization results for semi-positive line bundles whose curvature vanishes at finite order. The proof exploits the re…
In this work, we consider the task of classifying binary positive-unlabeled (PU) data. The existing discriminative learning based PU models attempt to seek an optimal reweighting strategy for U data, so that a decent decision boundary can be found. However, given limited P data, the conventional PU models tend to suffe…
We use Nathanson's -adic representation of integers to relate metric properties of Cayley graphs of the integers with respect to various infinite generating sets to problems in additive number theory. If consists of all powers of a fixed integer , we find explicit formulas for the smallest positive intege…
Prove top wedge power of Ricci form has finite integral for Kähler manifolds with positive sectional curvature
Theory of Θ-positive representations for real closed fields.
Refining one's hypotheses in the light of data is a common scientific practice; however, the dependency on the data introduces selection bias and can lead to specious statistical analysis. An approach for addressing this is via conditioning on the selection procedure to account for how we have used the data to generate…
Like most learning algorithms, the multilayer perceptrons (MLP) is designed to learn a vector of parameters from data. However, in certain scenarios we are interested in learning structured parameters (predictions) in the form of symmetric positive definite matrices. Here, we introduce a variant of the MLP, referred to…
Robust CD method for real-world time series with power-law distributions.
The problem of multiple hypothesis testing arises when there are more than one hypothesis to be tested simultaneously for statistical significance. This is a very common situation in many data mining applications. For instance, assessing simultaneously the significance of all frequent itemsets of a single dataset entai…
We prove that the metric on the direct image of an adjoint positive line bundle by a locally trivial submersion between projective manifolds is Nakano positive, under the assumption that the typical fiber has zero first Betti number. As a consequence, we get that the symmetric powers of an ample vector bundle ten…
Paper introduces reinforcement learning for managing power grids.
In the general framework of a semimartingale financial model and a utility function defined on the positive real line, we compute the first-order expansion of marginal utility-based prices with respect to a ``small'' number of random endowments. We show that this linear approximation has some important qualitative …
New method estimates log-determinant using trace powers, avoiding classical limitations.
Introduces -positivity in Lie groups, generalizing Lusztig's positivity.
CR invariant differential operators on densities with leading part a power of the sub-Laplacian are derived. One family of such operators is constructed from the ``conformally invariant powers of the Laplacian'' via the Fefferman metric; the powers which arise for these operators are bounded in terms of the dimension. …
Study optimal holomorphic extensions for jets along submanifolds as tensor powers increase.
Study of torsion forms for positive line bundles.
Establishes geometric properties of elements in the positive semigroup of a general real semisimple Lie group.
Researchers prove Transformers are Turing-complete and analyze their components.
Improved reasoning model by sampling from power distribution without additional training.
Quandle cocycle invariants form a powerful and well developed tool in knot theory. This paper treats their variations - namely, positive and twisted quandle cocycle invariants, and shadow invariants. We interpret the former as particular cases of the latter. As an application, several constructions from the shadow worl…
Let Gamma be a group generated by two positive multi-twists. We give some sufficient conditions for Gamma to be free or have no `unexpectedly reducible' elements. For a group Gamma generated by two Dehn twists, we classify the elements in Gamma which are multi-twists. As a consequence we are able to list all the lanter…
SynthBH uses synthetic data to control FDR in multiple testing.
We introduce -positivity, a new notion of positivity in real semisimple Lie groups. The notion of -positivity generalizes at the same time Lusztig's total positivity in split real Lie groups as well as well known concepts of positivity in Lie groups of Hermitian type. We show that there are two other families of …
New algorithm balances user reward and statistical inference by mixing TS with UR based on difference size.
Proportional transaction costs present difficult theoretical problems in trading algorithm design, on account of their lack of analytical tractability. The author derives a solution of DT-NT-DT form for an arbitrary model in which the the traded asset has diffusive dynamics described by one or more stochastic risk fact…
The role of kernels is central to machine learning. Motivated by the importance of power-law distributions in statistical modeling, in this paper, we propose the notion of power-law kernels to investigate power-laws in learning problem. We propose two power-law kernels by generalizing Gaussian and Laplacian kernels. Th…
Upper diameter bound for manifolds with positive scalar curvature.
J. Hempel's definition of the distance of a Heegaard surface generalizes to a complexity for a knot which is in bridge position with respect to a Heegaard surface. Our main result is that the distance of a knot in bridge position is bounded above by twice the genus, plus the number of boundary components, of an essenti…
New flow expands hypersurfaces in hyperbolic space, showing round limiting shape for certain powers.