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 defines and proves the existence of train track maps on graphs of groups.
Extends knockoff filter for composite null hypotheses in variable selection.
In order to apply variational methods to the action functional for geodesics of a stationary spacetime, some hypotheses, useful to obtain classical Palais-Smale condition, are commonly used: pseudo-coercivity, bounds on certain coefficients of the metric, etc. We prove that these technical assumptions admit a natural i…
Investment strategies in financial markets can lead to instability due to market impacts.
Let A be a dg algebra over F_2 and let M be a dg A-bimodule. We show that under certain technical hypotheses on A, a noncommutative analog of the Hodge-to-de Rham spectral sequence starts at the Hochschild homology of the derived tensor product of M with itself and converges to the Hochschild homology of M. We apply th…
The rigidity of the Positive Mass Theorem states that the only complete asymptotically flat manifold of nonnegative scalar curvature and zero mass is Euclidean space. We study the stability of this statement for spaces that can be realized as graphical hypersurfaces in Euclidean space. We prove (under certain technical…
We use Morse theory to prove that the Lefschetz Hyperplane Theorem holds for compact smooth Deligne-Mumford stacks over the site of complex manifolds. For a hyperplane section, can be obtained from by a sequence of deformation retracts and attachments of high-dimensional finite disc quotients. We …
Partial connections are (singular) differential systems generalizing classical connections on principal bundles, yielding analogous decompositions for manifolds with nonfree group actions. Connection forms are interpreted as maps determining projections of the tangent bundle onto the partial connection; this approach e…
We give a complete answer to the question of when two curves in two different Riemannian manifolds can be seen as trajectories of rolling one manifold on the other without twisting or slipping. We show that up to technical hypotheses, a rolling along these curves exists if and only if the geodesic curvatures of each cu…
In 1998, Goresky, Kottwitz, and MacPherson showed that for certain spaces X equipped with a torus action, the T-equivariant cohomology ring of X can be described by combinatorial data obtained from its orbit decomposition. Thus, their theory transforms calculations of the equivariant topology of X to those of the combi…
We study a policy gradient method with L2 regularization for MAB problems.
Paper develops a consistent model selection framework for learning Hypotheses Space from data.
New foliations constructed from contact pairs, revealing flexible taut foliations.
Learning rates for least-squares regression are typically expressed in terms of -norms. In this paper we extend these rates to norms stronger than the -norm without requiring the regression function to be contained in the hypothesis space. In the special case of Sobolev reproducing kernel Hilbert spaces used …
We prove a global local rigidity result for character varieties of 3-manifolds into . Given a 3-manifold with toric boundary satisfying some technical hypotheses, we prove that all but a finite number of its Dehn fillings are globally locally rigid in the following sense: every irreducible repr…
Paper tackles efficient learning of non-convex hypotheses in metric spaces.
Boosting combines weak hypotheses to create accurate predictions under bounded VC dimension.
DivDis learns diverse hypotheses from underspecified data to improve robustness.
ChemCPA predicts cellular responses to novel drugs using transfer learning.
Machine Learning benefits from prior information and computational power for better performance and understanding.
New method uses LLMs to generate detailed scientific hypotheses.
Sequential tests for nonparametric hypotheses using supermartingales.
In many practical applications of multiple hypothesis testing using the False Discovery Rate (FDR), the given hypotheses can be naturally partitioned into groups, and one may not only want to control the number of false discoveries (wrongly rejected null hypotheses), but also the number of falsely discovered groups of …
In this paper, we diagnose deep neural networks for 3D point cloud processing to explore utilities of different intermediate-layer network architectures. We propose a number of hypotheses on the effects of specific intermediate-layer network architectures on the representation capacity of DNNs. In order to prove the hy…
We propose a method to generate multiple diverse and valid human pose hypotheses in 3D all consistent with the 2D detection of joints in a monocular RGB image. We use a novel generative model uniform (unbiased) in the space of anatomically plausible 3D poses. Our model is compositional (produces a pose by combining par…
Hypothesis testing in singular models is fundamentally about identifiable vs. non-identifiable parameters.
The paper uses RL to verify hypotheses, overcoming existing limitations.
There is a significant literature on methods for incorporating knowledge into multiple testing procedures so as to improve their power and precision. Some common forms of prior knowledge include (a) beliefs about which hypotheses are null, modeled by non-uniform prior weights; (b) differing importances of hypotheses, m…
Attention-based encoder decoder network uses a left-to-right beam search algorithm in the inference step. The current beam search expands hypotheses and traverses the expanded hypotheses at the next time step. This traversal is implemented using a for-loop program in general, and it leads to speed down of the recogniti…
s-RBFN integrates multiple hypotheses for efficient and diverse prediction.
It was proved in 1998 by Ben-David and Litman that a concept space has a sample compression scheme of size d if and only if every finite subspace has a sample compression scheme of size d. In the compactness theorem, measurability of the hypotheses of the created sample compression scheme is not guaranteed; at the same…
Near-optimal private tests for simple and MLR hypotheses developed under Gaussian differential privacy.
Current statistical inference problems in areas like astronomy, genomics, and marketing routinely involve the simultaneous testing of thousands -- even millions -- of null hypotheses. For high-dimensional multivariate distributions, these hypotheses may concern a wide range of parameters, with complex and unknown depen…
The paper limits the profitability of technical trading rules and finds they are not better than random trading.
Confirmation bias leads to biased estimates in noisy data analysis.
The paper proves weaker conditions for global smoothings of special Lagrangian submanifolds with conical singularities.
Active inference selects actions to maximize information gain, aiding structure learning.
The paper studies Liouville structures for taut foliations and Anosov flows, proving their topological invariance.
Study identifies and analyzes spurious correlations in data-driven models.
Transforms uniform learners to work under arbitrary distributions efficiently.
Boosting algorithms produce a classifier by iteratively combining base hypotheses. It has been observed experimentally that the generalization error keeps improving even after achieving zero training error. One popular explanation attributes this to improvements in margins. A common goal in a long line of research, is …
Algorithm estimates covariance from noisy data efficiently.
Abstract: A new approach to technical indicators without lag.
We consider a distributed learning setup where a network of agents sequentially access realizations of a set of random variables with unknown distributions. The network objective is to find a parametrized distribution that best describes their joint observations in the sense of the Kullback-Leibler divergence. Apart fr…
In this paper we use fuzzy systems theory to convert the technical trading rules commonly used by stock practitioners into excess demand functions which are then used to drive the price dynamics. The technical trading rules are recorded in natural languages where fuzzy words and vague expressions abound. In Part I of t…
Crowdsourcing has been successfully applied in many domains including astronomy, cryptography and biology. In order to test its potential for useful application in a Smart Grid context, this paper investigates the extent to which a crowd can contribute predictive hypotheses to a model of residential electric energy con…
The paper studies cohomology of groups acting on 1-manifolds and applies results to spectrum problems.
Technical trading rules have a long history of being used by practitioners in financial markets. Their profitable ability and efficiency of technical trading rules are yet controversial. In this paper, we test the performance of more than seven thousands traditional technical trading rules on the Shanghai Securities Co…