Marina Meila | DeepAI

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∙ 02/01/2023

Dictionary-based Manifold Learning

We propose a paradigm for interpretable Manifold Learning for scientific...

0 Hanyu Zhang, et al. ∙

∙ 02/01/2023

The Parametric Stability of Well-separated Spherical Gaussian Mixtures

We quantify the parameter stability of a spherical Gaussian Mixture Mode...

0 Hanyu Zhang, et al. ∙

∙ 04/26/2022

Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space

We introduce a data-driven approach to building reduced dynamical models...

0 Nikolaos Evangelou, et al. ∙

∙ 03/31/2022

To ArXiv or not to ArXiv: A Study Quantifying Pros and Cons of Posting Preprints Online

Double-blind conferences have engaged in debates over whether to allow a...

0 Charvi Rastogi, et al. ∙

∙ 07/30/2021

Distribution free optimality intervals for clustering

We address the problem of validating the ouput of clustering algorithms....

0 Marina Meila, et al. ∙

∙ 07/23/2021

The decomposition of the higher-order homology embedding constructed from the k-Laplacian

The null space of the k-th order Laplacian ℒ_k, known as the k-th homolo...

0 Yu-Chia Chen, et al. ∙

∙ 04/21/2021

A class of network models recoverable by spectral clustering

Finding communities in networks is a problem that remains difficult, in ...

0 Yali Wan, et al. ∙

∙ 03/13/2021

Helmholtzian Eigenmap: Topological feature discovery edge flow learning from point cloud data

The manifold Helmholtzian (1-Laplacian) operator Δ_1 elegantly generaliz...

0 Yu-Chia Chen, et al. ∙

∙ 06/18/2020

Guarantees for Hierarchical Clustering by the Sublevel Set method

Meila (2018) introduces an optimization based method called the Sublevel...

0 Marina Meila, et al. ∙

∙ 07/02/2019

Selecting the independent coordinates of manifolds with large aspect ratios

Many manifold embedding algorithms fail apparently when the data manifol...

0 Yu-Chia Chen, et al. ∙

∙ 12/03/2018

Measuring the Robustness of Graph Properties

In this paper, we propose a perturbation framework to measure the robust...

0 Yali Wan, et al. ∙

∙ 11/29/2018

A regression approach for explaining manifold embedding coordinates

Manifold embedding algorithms map high dimensional data, down to coordin...

0 Marina Meila, et al. ∙

∙ 07/21/2018

How to sample connected K-partitions of a graph

A connected undirected graph G=(V,E) is given. This paper presents an al...

0 Marina Meila, et al. ∙

∙ 03/09/2016

megaman: Manifold Learning with Millions of points

Manifold Learning is a class of algorithms seeking a low-dimensional non...

0 James McQueen, et al. ∙

∙ 05/30/2014

Estimating Vector Fields on Manifolds and the Embedding of Directed Graphs

This paper considers the problem of embedding directed graphs in Euclide...

0 Dominique Perrault-Joncas, et al. ∙

∙ 12/06/2013

An Algorithmic Theory of Dependent Regularizers, Part 1: Submodular Structure

We present an exploration of the rich theoretical connections between se...

0 Hoyt Koepke, et al. ∙

∙ 05/30/2013

Non-linear dimensionality reduction: Riemannian metric estimation and the problem of geometric discovery

In recent years, manifold learning has become increasingly popular as a ...

0 Dominique Perraul-Joncas, et al. ∙

∙ 01/30/2013

An Experimental Comparison of Several Clustering and Initialization Methods

We examine methods for clustering in high dimensions. In the first part ...

0 Marina Meila, et al. ∙

∙ 01/16/2013

Tractable Bayesian Learning of Tree Belief Networks

In this paper we present decomposable priors, a family of priors over st...

0 Marina Meila, et al. ∙

∙ 07/04/2012

Unsupervised spectral learning

In spectral clustering and spectral image segmentation, the data is part...

0 Susan Shortreed, et al. ∙

∙ 06/20/2012

Consensus ranking under the exponential model

We analyze the generalized Mallows model, a popular exponential model ov...

0 Marina Meila, et al. ∙

∙ 03/15/2012

Dirichlet Process Mixtures of Generalized Mallows Models

We present a Dirichlet process mixture model over discrete incomplete ra...

0 Marina Meila, et al. ∙

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