Search Results for author:
Found 10 papers, 2 papers with code
Finsler-Laplace-Beltrami Operators with Application to Shape Analysis
In experimental evaluations we demonstrate that the proposed FLBO is a valuable alternative to the traditional Riemannian-based LBO and ALBOs for spatial filtering and shape correspondence estimation.
Flattening the Parent Bias: Hierarchical Semantic Segmentation in the Poincaré Ball
Hierarchy is a natural representation of semantic taxonomies, including the ones routinely used in image segmentation.
Matching under Imperfectly Transferable Utility
In this paper, we examine matching models with imperfectly transferable utility (ITU).
Existence of a Competitive Equilibrium with Substitutes, with Applications to Matching and Discrete Choice Models
We propose new results for the existence and uniqueness of a general nonparametric and nonseparable competitive equilibrium with substitutes.
Reducing Nearest Neighbor Training Sets Optimally and Exactly
We investigate the problem of finding the minimum cardinality reduced training set $P'\subseteq P$ such that $P$ and $P'$ induce the same classification.
Collective models and the marriage market
In this paper, I develop an integrated approach to collective models and matching models of the marriage market.
Power Bundle Adjustment for Large-Scale 3D Reconstruction
We demonstrate that employing the proposed Power Bundle Adjustment as a sub-problem solver significantly improves speed and accuracy of the distributed optimization.
Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete
We consider the problem of finding weights and biases for a two-layer fully connected neural network to fit a given set of data points as well as possible, also known as EmpiricalRiskMinimization.
Multidirectional Conjugate Gradients for Scalable Bundle Adjustment
We revisit the problem of large-scale bundle adjustment and propose a technique called Multidirectional Conjugate Gradients that accelerates the solution of the normal equation by up to 61%.
Matching Function Equilibria with Partial Assignment: Existence, Uniqueness and Estimation
We argue that models coming from a variety of fields, such as matching models and discrete choice models among others, share a common structure that we call matching function equilibria with partial assignment.
