arXiv research

Paper tackles distribution matching by partially matching distributions, achieving robust results.

We consider partial matchings, which are finite graphs consisting of edges and vertices of degree zero or one. We consider transformations between two states of partial matchings. We introduce a method of presenting a transformation between partial matchings. We introduce the notion of the lattice presentation of a par…

Partial soft-matching distance improves neural representation comparison by allowing some neurons to remain unmatched.

Proposes GM-PLL for better partial label learning.

New method for partial matching of shapes with Varifolds.

Algorithm identifies optimal stable matching in uncertain two-sided markets.

New algorithm improves PPS for multi-object matching.

New model for shape graph registration with partial matching constraints.

New method synchronizes partial permutations using non-negative factorizations.

Given two graphs, the graph matching problem is to align the two vertex sets so as to minimize the number of adjacency disagreements between the two graphs. The seeded graph matching problem is the graph matching problem when we are first given a partial alignment that we are tasked with completing. In this paper, we m…

New method trains reflected Schrödinger bridges without complex derivatives.

New algorithms solve partial optimal transport problems for applications like PU learning.

Solves partial assignment problems using random clique complexes.

Paper tackles graph matching with partially correct seeds, improving performance guarantees.

Greedy algorithm performs well in online matching despite non-i.i.d. connections.

PPM improves graph matching for correlated Gaussian Wigner models with high probability.

Algorithm reduces regret in complex game scenarios.

Generative network integrates into ROM for PDEs, matching measurements and estimating uncertainties.

New method controls linear systems with partial info and disturbances.

This paper sets thresholds for recovering vertex correspondences in partially correlated graphs.

Joint matching over a collection of objects aims at aggregating information from a large collection of similar instances (e.g. images, graphs, shapes) to improve maps between pairs of them. Given multiple matches computed between a few object pairs in isolation, the goal is to recover an entire collection of maps that …

Robustly aligns datasets with partial GW distance to handle contamination.

Quantum modularity proven for specific theta series.

Adapts score matching for missing data in flexible settings.

FSBM improves matching efficiency with minimal supervision.

Fenrir uses probabilistic numerics to simplify solving initial value problems.

Graph matching method for noisy induced subgraph detection.

Proposes a method to create predictive sets from partially labeled data.

New method learns PDE solutions from low-fidelity data.

Partial fusion combines neural networks to balance accuracy and efficiency.

Wave maps from circle to manifold controllable if homotopy classes match.

Efficient RL in partially observable risk-sensitive environments with hindsight observations.

Gradient matching is a promising tool for learning parameters and state dynamics of ordinary differential equations. It is a grid free inference approach, which, for fully observable systems is at times competitive with numerical integration. However, for many real-world applications, only sparse observations are avail…

In this paper, we study the information-theoretic limits of community detection in the symmetric two-community stochastic block model, with intra-community and inter-community edge probabilities $\frac{a}{n}$ and $\frac{b}{n}$ respectively. We consider the sparse setting, in which $a$ and $b$ do not scale with $n$, and…

Paper explores VRM for PSMLC with partially labeled medical images.

Bayesian neural networks can be partially stochastic without losing predictive power.

We develop an encompassing framework for matching, covariate balancing, and doubly-robust methods for causal inference from observational data called generalized optimal matching (GOM). The framework is given by generalizing a new functional-analytical formulation of optimal matching, giving rise to the class of GOM me…

New link polynomials linked to cluster theory.

Study shows partially-typed NER datasets can match fully-typed ones in model performance.

Improves domain adaptation by clustering target representations.

Study optimal policy regret in partially observable Markov games with adaptive opponents.

A new method matches similar regions in non-rigid shapes using spectra of differential operators.

We study how a gluing construction, which produces compact manifolds with holonomy G_2 from matching pairs of asymptotically cylindrical G_2-manifolds, behaves under deformations. We show that the gluing construction defines a smooth map from a moduli space of gluing data to the moduli space of torsion-free G_2-structu…

Robust GW distance improves graph data alignment.

Improved graph matching using covariates for network data integration.

The bipartite record linkage task consists of merging two disparate datafiles containing information on two overlapping sets of entities. This is non-trivial in the absence of unique identifiers and it is important for a wide variety of applications given that it needs to be solved whenever we have to combine informati…

Matching correlated VAR time series databases by recovering matching permutations.

Paper offers robust recovery for 1-bit sensing with partial Gaussian circulant matrices.