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 addresses causal estimation for text data with apparent overlap violations.
Paper extends causal inference methods beyond unconfoundedness and overlap assumptions.
The assumption of positivity in causal inference (also known as common support and co-variate overlap) is necessary to obtain valid causal estimates. Therefore, confirming it holds in a given dataset is an important first step of any causal analysis. Most common methods to date are insufficient for discovering non-posi…
Study optimizes estimating linear functionals from observational data without strict overlap.
CATR rationalizes text data to stabilize causal effect estimation.
BayesBag improves reproducibility of Bayesian inference under model misspecification.
Unified framework for fairness, robustness, and distribution shifts.
New method for estimating mean in SS inference with selection bias and decaying overlap.
DOLCE improves off-policy evaluation and learning by decomposing effects.
New metric scores perturbations across populations, not cells, improving model comparison.
Overlapping clustering problem is an important learning issue in which clusters are not mutually exclusive and each object may belongs simultaneously to several clusters. This paper presents a kernel based method that produces overlapping clusters on a high feature space using mercer kernel techniques to improve separa…
Deconfounding scores improve causal effect estimation with weak overlap.
A new method speeds up overlapping group lasso computations.
Estimates CATE under hidden confounding, accounting for bias and ignorance.
In medicine, visualizing chromosomes is important for medical diagnostics, drug development, and biomedical research. Unfortunately, chromosomes often overlap and it is necessary to identify and distinguish between the overlapping chromosomes. A segmentation solution that is fast and automated will enable scaling of co…
New method improves CATE estimation in low overlap regions.
Proposes a sensitivity framework to handle limited overlap in causal inference.
Producing overlapping schemes is a major issue in clustering. Recent proposed overlapping methods relies on the search of an optimal covering and are based on different metrics, such as Euclidean distance and I-Divergence, used to measure closeness between observations. In this paper, we propose the use of another meas…
The study simplifies assessing overlap in logistic regression models using empirical likelihood.
Recently, to solve large-scale lasso and group lasso problems, screening rules have been developed, the goal of which is to reduce the problem size by efficiently discarding zero coefficients using simple rules independently of the others. However, screening for overlapping group lasso remains an open challenge because…
Community detection is a fundamental problem in network analysis which is made more challenging by overlaps between communities which often occur in practice. Here we propose a general, flexible, and interpretable generative model for overlapping communities, which can be thought of as a generalization of the degree-co…
RISA improves VFL by using imputed samples with low uncertainty.
As research into community finding in social networks progresses, there is a need for algorithms capable of detecting overlapping community structure. Many algorithms have been proposed in recent years that are capable of assigning each node to more than a single community. The performance of these algorithms tends to …
We present a principled approach for detecting overlapping temporal community structure in dynamic networks. Our method is based on the following framework: find the overlapping temporal community structure that maximizes a quality function associated with each snapshot of the network subject to a temporal smoothness c…
Bayesian methods detect significant IIA violations in similarity choice data.
New mechanism detects overlap density for weak-to-strong generalization.
We calculate eigenvector overlaps between intersecting time periods of covariance matrices.
Community detection is a task of fundamental importance in social network analysis that can be used in a variety of knowledge-based domains. While there exist many works on community detection based on connectivity structures, they suffer from either considering the overlapping or non-overlapping communities. In this w…
Unified approach for fair classification with overlapping groups.
New LT-O-learners improve HLTE estimation with low overlap.
ION-C solves overlapping network integration problems efficiently.
Overlap between treatment groups is required for non-parametric estimation of causal effects. If a subgroup of subjects always receives the same intervention, we cannot estimate the effect of intervention changes on that subgroup without further assumptions. When overlap does not hold globally, characterizing local reg…
Study on Langevin dynamics for recovering planted signals in spiked matrix models.
The correspondence between Riemann-Finsler geometries and effective field theories with spin-independent Lorentz violation is explored. We obtain the general quadratic action for effective scalar field theories in any spacetime dimension with Lorentz-violating operators of arbitrary mass dimension. Classical relativist…
New method detects overlapping communities in weighted graphs without pure nodes assumption.
This contribution to the CPT'13 meeting briefly introduces Lorentz and CPT violation and outlines two recent developments in the field.
K-fold Cross Validation is commonly used to evaluate classifiers and tune their hyperparameters. However, it assumes that data points are Independent and Identically Distributed (i.i.d.) so that samples used in the training and test sets can be selected randomly and uniformly. In Human Activity Recognition datasets, we…
Study on overlaps of singular vectors in Gaussian matrix submatrices.
Deconfounding scores improve causal effect estimation with weak overlap.
Improved off-policy evaluation for MDPs with weak distributional overlap.
Bipartite Riemann-Finsler geometries with complementary Finsler structures are constructed. Calculable examples are presented based on a bilinear-form coefficient for explicit Lorentz violation.
This paper presents a novel spectral algorithm with additive clustering designed to identify overlapping communities in networks. The algorithm is based on geometric properties of the spectrum of the expected adjacency matrix in a random graph model that we call stochastic blockmodel with overlap (SBMO). An adaptive ve…
A new overlapping space solves the configuration search problem for graph embeddings.
Detecting faults and SLA violations in a timely manner is critical for telecom providers, in order to avoid loss in business, revenue and reputation. At the same time predicting SLA violations for user services in telecom environments is difficult, due to time-varying user demands and infrastructure load conditions. In…
We present a new approach to assessing the robustness of neural networks based on estimating the proportion of inputs for which a property is violated. Specifically, we estimate the probability of the event that the property is violated under an input model. Our approach critically varies from the formal verification f…
New metrics assess class overlap and imbalance in datasets.
Sliced inverse regression (SIR) is a pioneer tool for supervised dimension reduction. It identifies the effective dimension reduction space, the subspace of significant factors with intrinsic lower dimensionality. In this paper, we propose to refine the SIR algorithm through an overlapping slicing scheme. The new algor…
CVTMLE improves statistical inference in settings of positivity or Donsker class violations.