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← Core Methods
Machine Learning
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Core Methods
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Clustering
3615 directly classified papers
Papers per year
2000: 1
2001: 3
2002: 4
2003: 7
2004: 2
2005: 4
2006: 34
2007: 19
2008: 22
2009: 23
2010: 38
2011: 51
2012: 74
2013: 125
2014: 111
2015: 107
2016: 158
2017: 203
2018: 219
2019: 319
2020: 310
2021: 336
2022: 293
2023: 394
2024: 345
2025: 287
2026: 126
Papers
Fast Large-scale Mixture Modeling with Component-specific Data Partitions
NIPS 2010
Joint Analysis of Time-Evolving Binary Matrices and Associated Documents
NIPS 2010
Robust Clustering as Ensembles of Affinity Relations
NIPS 2010
Dirichlet Process Mixtures of Generalized Linear Models
AISTATS 2010
Unsupervised Kernel Dimension Reduction
NIPS 2010
Rates of convergence for the cluster tree
NIPS 2010
Towards Property-Based Classification of Clustering Paradigms
NIPS 2010
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
NIPS 2010
Tree-Structured Stick Breaking for Hierarchical Data
NIPS 2010
Practical Large-Scale Optimization for Max-norm Regularization
NIPS 2010
Minimum Average Cost Clustering
NIPS 2010
Sample Complexity of Testing the Manifold Hypothesis
NIPS 2010
Random Projections for $k$-means Clustering
NIPS 2010
Movement extraction by detecting dynamics switches and repetitions
NIPS 2010
Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch
NIPS 2010
PAC-Bayesian Analysis of Co-clustering and Beyond
JMLR 2010
Mining Recurring Concept Drifts with Limited Labeled Streaming Data
ACML 2010
Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering
ACML 2010
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
JMLR 2010
Characterization, Stability and Convergence of Hierarchical Clustering Methods
JMLR 2010
Fast detection of multiple change-points shared by many signals using group LARS
NIPS 2010
Unsupervised discovery of object classes from range data using latent Dirichlet allocation
RSS 2009
Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions
JMLR 2009
Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering
NIPS 2009
Clustering sequence sets for motif discovery
NIPS 2009
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