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Clustering

756 directly classified papers

Papers per year

Papers

Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process IJCAI 2017
Projective Low-rank Subspace Clustering via Learning Deep Encoder IJCAI 2017
Self-weighted Multiview Clustering with Multiple Graphs IJCAI 2017
Beyond the Nystrom Approximation: Speeding up Spectral Clustering using Uniform Sampling and Weighted Kernel k-means IJCAI 2017
Scalable Normalized Cut with Improved Spectral Rotation IJCAI 2017
Online Nonnegative Matrix Factorization with General Divergences AISTATS 2017
Communication-Optimal Distributed Clustering NIPS 2016
New Resistance Distances with Global Information on Large Graphs AISTATS 2016
Estimating the Size of a Large Network and its Communities from a Random Sample NIPS 2016
Discriminatively Embedded K-Means for Multi-View Clustering CVPR 2016
Consistent Algorithms for Clustering Time Series JMLR 2016
On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm JMLR 2016
Covariance-based Clustering in Multivariate and Functional Data Analysis JMLR 2016
Local Network Community Detection with Continuous Optimization of Conductance and Weighted Kernel K-Means JMLR 2016
bandicoot: a Python Toolbox for Mobile Phone Metadata JMLR 2016
Predicting Restaurant Consumption Level through Social Media Footprints COLING 2016
A Novel Fast Framework for Topic Labeling Based on Similarity-preserved Hashing COLING 2016
Compressive Spectral Clustering ICML 2016
Controlling the distance to a Kemeny consensus without computing it ICML 2016
Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization COLING 2016
Predicting sentential semantic compatibility for aggregation in text-to-text generation COLING 2016
Exploring Differential Topic Models for Comparative Summarization of Scientific Papers COLING 2016
Graph Clustering: Block-models and model free results NIPS 2016
Robust Spectral Detection of Global Structures in the Data by Learning a Regularization NIPS 2016
Exploiting Tradeoffs for Exact Recovery in Heterogeneous Stochastic Block Models NIPS 2016