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.
VOWEL trains WTA-SNNs for multi-valued events, overcoming resource limitations.
The paper constructs a multi-valued inverse of quasiregular maps and develops pull-back theory for differential forms.
We construct several types of multi-valued solutions to the Monge-Ampere equation in higher dimensions.
Extends Campanato theory to multi-valued functions for geometric variational problems.
XTNet estimates complex cross-treatment effects in multi-category, multi-valued settings.
We apply the technique of integrable extensions to the symmetry pseudo-group of the dKP-hyper CR interpolating equation. This allows us to find a covering for this equation and to construct multi-valued Einstein-Weyl structures.
In this paper we prove that an embedded and simply connected constant mean curvature surface with curvature large at a point contains a multi-valued graph around that point on the scale of , where is the norm squared of the second fundamental form. This generalizes Colding and Minicozzi's result for mini…
This paper analyzes meta-learners for estimating multi-valued treatment effects.
New method estimates causal effects with multi-valued, time-varying treatments.
New category theory for complex projective plane sections.
In the early 1980's Almgren developed a theory of Dirichlet energy minimizing multi-valued functions, proving that the Hausdorff dimension of the singular set (including branch points) of such a function is at most where is the dimension of its domain. Almgren used this result in an essential way to show t…
This paper is the second in a series where we attempt to give a complete description of the space of all embedded minimal surfaces of fixed genus in a fixed (but arbitrary) closed 3-manifold. The key for understanding such surfaces is to understand the local structure in a ball and in particular the structure of an emb…
The Chekanov theorem generalizes the classic Lyusternik-Shnirel'man and Morse theorems concerning critical points of a smooth function on a closed manifold. A Legendrian submanifold Λof space of 1-jets of the functions on a manifold M defines a multi-valued function whose graph is the projection of Λin J^0 M = M x R. T…
After appropriate normalizations an embedded disk whose second fundamental form has large norm contains a multi-valued graph, provided the L^P norm of the mean curvature is sufficiently small. This generalizes to non-minimal surfaces a well known result of Colding and Minicozzi.
For multi-valued functions---such as when the conditional distribution on targets given the inputs is multi-modal---standard regression approaches are not always desirable because they provide the conditional mean. Modal regression algorithms address this issue by instead finding the conditional mode(s). Most, however,…
DiffOPF solves multi-valued OPF problems by sampling from system history.
In the 1980's, Almgren developed a theory of multi-valued Dirichlet energy minimizing functions on dimensional domains and used it, in an essential way, to bound the Hausdorff dimension of the singular sets of area minimizing rectifiable currents of dimension and codimension . Recent work of the second …
Study on a weighted Suita conjecture for higher derivatives and their geometric properties.
In this paper, we consider multi-valued graphs with a prescribed real analytic interface that minimize the Dirichlet energy. Such objects arise as a linearized model of area minimizing currents with real analytic boundaries and our main result is that their singular set is discrete in 2 dimensions. This confirms (and p…
We analyze a notion of multiple valued sections of a vector bundle over an abstract smooth Riemannian manifold, which was suggested by W. Allard in the unpublished note "Some useful techniques for dealing with multiple valued functions" and generalizes Almgren's -valued functions. We study some relevant properties o…
We prove an Alexandrov type theorem for a quotient space of . More precisely we classify the compact embedded surfaces with constant mean curvature in the quotient of by a subgroup of isometries generated by a parabolic translation along horocycles of $\mathbb …
This is the second paper of a series of three on the regularity of higher codimension area minimizing integral currents. Here we perform the second main step in the analysis of the singularities, namely the construction of a center manifold, i.e. an approximate average of the sheets of an almost flat area minimizing cu…
Alternative proof and extension of curvature estimates for minimal immersions.
In this paper, we propose an active learning method for an inverse problem that aims to find an input that achieves a desired structured-output. The proposed method provides new acquisition functions for minimizing the error between the desired structured-output and the prediction of a Gaussian process model, by effect…
In this article, we study local holomorphic isometric embeddings from ${\BB}^n$ into ${\BB}^{N_1}\times... \times{\BB}^{N_m}$ with respect to the normalized Bergman metrics up to conformal factors. Assume that each conformal factor is smooth Nash algebraic. Then each component of the map is a multi-valued holomorphic m…
A clustering may be considered as fair on pre-specified sensitive attributes if the proportions of sensitive attribute groups in each cluster reflect that in the dataset. In this paper, we consider the task of fair clustering for scenarios involving multiple multi-valued or numeric sensitive attributes. We propose a fa…
Develops a neural model to predict event occurrence and timing.
Paper proposes a new trading strategy using corporate event detection from news articles.
Events are happening in real-world and real-time, which can be planned and organized occasions involving multiple people and objects. Social media platforms publish a lot of text messages containing public events with comprehensive topics. However, mining social events is challenging due to the heterogeneous event elem…
AUC is unreliable in rare event settings but stable with moderate numbers of events.
Non-spanning identification of scheduled event risk in option pricing.
New approach predicts event probabilities for better event detection.
Study examines HTE estimation from time-to-event data with competing events.
GANs improve event generation in physics experiments.
REST framework predicts stock trends by considering stock-specific and related-stock events.
Considering event structure information has proven helpful in text-based stock movement prediction. However, existing works mainly adopt the coarse-grained events, which loses the specific semantic information of diverse event types. In this work, we propose to incorporate the fine-grained events in stock movement pred…
New deep learning method handles rare and imbalanced events in time series.
We present ProxiModel, a novel event mining framework for extracting high-quality structured event knowledge from large, redundant, and noisy news data sources. The proposed model differentiates itself from other approaches by modeling both the event correlation within each individual document as well as across the cor…
Combining multiple collider events improves machine learning performance.
The study uses financial events to predict stock market movements.
Proposes a model for predicting events from event streams.
LOBDIF predicts limit order book events using a diffusion model.
Electroencephalography (EEG) during sleep is used by clinicians to evaluate various neurological disorders. In sleep medicine, it is relevant to detect macro-events (> 10s) such as sleep stages, and micro-events (<2s) such as spindles and K-complexes. Annotations of such events require a trained sleep expert, a time co…
Neural network model predicts alternating event-free periods.
The plausibility of uncommon events and miracles based on testimony of such an event has been much discussed. When analyzing the probabilities involved, it has mostly been assumed that the common events can be taken as data in the calculations. However, we usually have only testimonies for the common events. While this…
New STH distance finds patterns in event timeseries without resampling.
Paper tackles event stream outliers using a novel weight function.
Traditional event detection classifies a word or a phrase in a given sentence for a set of predefined event types. The limitation of such predefined set is that it prevents the adaptation of the event detection models to new event types. We study a novel formulation of event detection that describes types via several k…