Marina Meila

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 29

Top Topics

Locality Preserving

Manifold Learning

Top Venues

J. Mach. Learn. Res.

Publications

Samson J. Koelle, Hanyu Zhang, Octavian-Vlad Murad, Marina Meila
Consistency of Dictionary-Based Manifold Learning. AISTATS (2024)
Hanyu Zhang, Samson Koelle, Marina Meila
Dictionary-based Manifold Learning. CoRR (2023)
Marina Meila, Hanyu Zhang
Manifold learning: what, how, and why. CoRR (2023)
Hanyu Zhang, Marina Meila
The Parametric Stability of Well-separated Spherical Gaussian Mixtures. CoRR (2023)
Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis
Double Diffusion Maps and their Latent Harmonics for scientific computations in latent space. J. Comput. Phys. 485 (2023)
Marina Meila, Annelise Wagner, Christopher Meek
Recursive inversion models for permutations. Stat. Comput. 32 (4) (2022)
Charvi Rastogi, Ivan Stelmakh, Xinwei Shen, Marina Meila, Federico Echenique, Shuchi Chawla, Nihar B. Shah
To ArXiv or not to ArXiv: A Study Quantifying Pros and Cons of Posting Preprints Online. CoRR (2022)
Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo, Daniel Lehmberg, Marina Meila, Ioannis G. Kevrekidis
Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space. CoRR (2022)
Samson Koelle, Hanyu Zhang, Marina Meila, Yu-Chia Chen
Manifold Coordinates with Physical Meaning. J. Mach. Learn. Res. 23 (2022)
Yu-Chia Chen, Marina Meila, Ioannis G. Kevrekidis
Helmholtzian Eigenmap: Topological feature discovery & edge flow learning from point cloud data. CoRR (2021)
Yali Wan, Marina Meila
A class of network models recoverable by spectral clustering. CoRR (2021)
Yu-Chia Chen, Marina Meila
The decomposition of the higher-order homology embedding constructed from the k-Laplacian. CoRR (2021)
Yu-Chia Chen, Marina Meila
The decomposition of the higher-order homology embedding constructed from the $k$-Laplacian. NeurIPS (2021)
Marina Meila, Hanyu Zhang
Distribution free optimality intervals for clustering. CoRR (2021)
Marina Meila
Guarantees for Hierarchical Clustering by the Sublevel Set method. CoRR (2020)
Yu-Chia Chen, Marina Meila
Selecting the independent coordinates of manifolds with large aspect ratios. NeurIPS (2019)
Yu-Chia Chen, Marina Meila
Selecting the independent coordinates of manifolds with large aspect ratios. CoRR (2019)
Yali Wan, Marina Meila
Measuring the Robustness of Graph Properties. CoRR (2019)
Marina Meila
Good (K-means) clusterings are unique (up to small perturbations). J. Multivar. Anal. 173 (2019)
Marina Meila
How to sample connected K-partitions of a graph. CoRR (2018)
Marina Meila, Samson Koelle, Hanyu Zhang
A regression approach for explaining manifold embedding coordinates. CoRR (2018)
Marina Meila
How to tell when a clustering is (approximately) correct using convex relaxations. NeurIPS (2018)
Dominique Joncas, Marina Meila, James McQueen
Improved Graph Laplacian via Geometric Self-Consistency. NIPS (2017)
James McQueen, Marina Meila, Jacob VanderPlas, Zhongyue Zhang
megaman: Manifold Learning with Millions of points. CoRR (2016)
Yali Wan, Marina Meila
Benchmarking recovery theorems for the DC-SBM. ISAIM (2016)
James McQueen, Marina Meila, Jacob VanderPlas, Zhongyue Zhang
Megaman: Scalable Manifold Learning in Python. J. Mach. Learn. Res. 17 (2016)
Marina Meila, Harr Chen
Bayesian Non-Parametric Clustering of Ranking Data. IEEE Trans. Pattern Anal. Mach. Intell. 38 (11) (2016)
Yali Wan, Marina Meila
Graph Clustering: Block-models and model free results. NIPS (2016)
James McQueen, Marina Meila, Dominique Joncas
Nearly Isometric Embedding by Relaxation. NIPS (2016)
Yali Wan, Marina Meila
A class of network models recoverable by spectral clustering. NIPS (2015)
Christopher Meek, Marina Meila
Recursive Inversion Models for Permutations. NIPS (2014)
Dominique C. Perrault-Joncas, Marina Meila
Estimating Vector Fields on Manifolds and the Embedding of Directed Graphs. CoRR (2014)
Zaeem Hussain, Marina Meila
Graph Sensitive Indices for Comparing Clusterings. CoRR (2014)
Dominique C. Perrault-Joncas, Marina Meila
Improved graph Laplacian via geometric self-consistency. CoRR (2014)
Marina Meila, David Heckerman
An Experimental Comparison of Several Clustering and Initialization Methods CoRR (2013)
Marina Meila, Tommi S. Jaakkola
Tractable Bayesian Learning of Tree Belief Networks CoRR (2013)
Raman Arora, Marina Meila
Consensus Ranking with Signed Permutations. AISTATS (2013)
Susan M. Shortreed, Marina Meila
Unsupervised spectral learning CoRR (2012)
Marina Meila, Le Bao
Estimation and Clustering with Infinite Rankings CoRR (2012)
Marina Meila, Harr Chen
Dirichlet Process Mixtures of Generalized Mallows Models CoRR (2012)
Marina Meila, Kapil Phadnis, Arthur Patterson, Jeff A. Bilmes
Consensus ranking under the exponential model CoRR (2012)
Marina Meila
Local equivalences of distances between clusterings - a geometric perspective. Mach. Learn. 86 (3) (2012)
Alnur Ali, Marina Meila
Experiments with Kemeny ranking: What works when? Math. Soc. Sci. 64 (1) (2012)
Dominique C. Perrault-Joncas, Marina Meila
Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators. NIPS (2011)
Marina Meila, Harr Chen
Dirichlet Process Mixtures of Generalized Mallows Models. UAI (2010)
Dominique C. Perrault-Joncas, Marina Meila, Marc Scott
Building a Job Lanscape from Directional Transition Data. AAAI Fall Symposium: Manifold Learning and Its Applications (2010)
Tommi S. Jaakkola, David A. Sontag, Amir Globerson, Marina Meila
Learning Bayesian Network Structure using LP Relaxations. AISTATS (2010)
Marina Meila, Le Bao
An Exponential Model for Infinite Rankings. J. Mach. Learn. Res. 11 (2010)
Bhushan Mandhani, Marina Meila
Tractable Search for Learning Exponential Models of Rankings. AISTATS (2009)
Marina Meila, Caren Marzban, Ulvi Yurtsever
Gravimetric Detection by Compressed Sensing. IGARSS (2) (2008)
Marina Meila, Le Bao
Estimation and clustering with infinite rankings. UAI (2008)
Marina Meila, William Pentney
Clustering by weighted cuts in directed graphs. SDM (2007)
Anamika Sarkar, Marina Meila, B. Robert Franza
IκB, NF-κB Regulation Model: Simulation Analysis of Small Number of Molecules. EURASIP J. Bioinform. Syst. Biol. 2007 (2007)
Marina Meila, Xiaotong Shen
Preface. AISTATS (2007)
Marina Meila, Kapil Phadnis, Arthur Patterson, Jeff A. Bilmes
Consensus ranking under the exponential model. UAI (2007)
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Meila, Gabriel Berson, Michael L. Cunningham, Raymond W. Sze
Symbolic Signatures for Deformable Shapes. IEEE Trans. Pattern Anal. Mach. Intell. 28 (1) (2006)
Marina Meila
The uniqueness of a good optimum for K-means. ICML (2006)
Marina Meila, Tommi S. Jaakkola
Tractable Bayesian learning of tree belief networks. Stat. Comput. 16 (1) (2006)
Anne Patrikainen, Marina Meila
Comparing Subspace Clusterings. IEEE Trans. Knowl. Data Eng. 18 (7) (2006)
Marina Meila
Comparing clusterings: an axiomatic view. ICML (2005)
Susan M. Shortreed, Marina Meila
Unsupervised Spectral Learning. UAI (2005)
William Pentney, Marina Meila
Spectral Clustering of Biological Sequence Data. AAAI (2005)
Marina Meila, Susan M. Shortreed, Liang Xu
Regularized spectral learning. AISTATS (2005)
Cody C. T. Kwok, Dieter Fox, Marina Meila
Real-time particle filters. Proc. IEEE 92 (3) (2004)
Marina Meila
Comparing Clusterings by the Variation of Information. COLT (2003)
Marina Meila
Data centering in feature space. AISTATS (2003)
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Meila
A New Paradigm for Recognizing 3-D Object Shapes from Range Data. ICCV (2003)
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Meila, Gabriel Berson
Discriminating Deformable Shape Classes. NIPS (2003)
Cody C. T. Kwok, Dieter Fox, Marina Meila
Adaptive real-time particle filters for robot localization. ICRA (2003)
Cody C. T. Kwok, Dieter Fox, Marina Meila
Real-Time Particle Filters. NIPS (2002)
Marina Meila, Jianbo Shi
A Random Walks View of Spectral Segmentation. AISTATS (2001)
Marina Meila, David Heckerman
An Experimental Comparison of Model-Based Clustering Methods. Mach. Learn. 42 (1/2) (2001)
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Meila
A New Signature-Based Method for Efficient 3-D Object Recognition. CVPR (1) (2001)
Jeff A. Bilmes, Gang Ji, Marina Meila
Intransitive Likelihood-Ratio Classifiers. NIPS (2001)
Marina Meila, Tommi S. Jaakkola
Tractable Bayesian Learning of Tree Belief Networks. UAI (2000)
Marina Meila, Jianbo Shi
Learning Segmentation by Random Walks. NIPS (2000)
Marina Meila, Michael I. Jordan
Learning with Mixtures of Trees. J. Mach. Learn. Res. 1 (2000)
Tommi S. Jaakkola, Marina Meila, Tony Jebara
Maximum Entropy Discrimination. NIPS (1999)
Marina Meila
An Accelerated Chow and Liu Algorithm: Fitting Tree Distributions to High-Dimensional Sparse Data. ICML (1999)
Marina Meila, David Heckerman
An Experimental Comparison of Several Clustering and Initialization Methods. UAI (1998)
Marina Meila, Michael I. Jordan
An Objective Function for Belief Net Triangulation. AISTATS (1997)
Marina Meila, Michael I. Jordan
Estimating Dependency Structure as a Hidden Variable. NIPS (1997)
Marina Meila, Michael I. Jordan
Triangulation by Continuous Embedding. NIPS (1996)
Marina Meila, Michael I. Jordan
Learning Fine Motion by Markov Mixtures of Experts. NIPS (1995)