Multiview Learning

arXiv

• Semi-supervised Deep Representation Learning for Multi-View Problems

  • Vahid Noroozi, Sara Bahaadini, Lei Zheng, Sihong Xie, Weixiang Shao, Philip S. Yu, IEEE Big Data, arXiv:1811
  • CCA

• Product Title Refinement via Multi-Modal Generative Adversarial Learning

  • Jianguo Zhang, Pengcheng Zou, Zhao Li, Yao Wan, Ye Liu, Xiuming Pan, Yu Gong, Philip S. Yu, NIPS workshop, arXiv:1811
  • GAN

Survey

• Feature Selection with Multi-view Data: A Survey

  • R Zhang, F Nie, X Li, X Wei - Information Fusion, 2018
  • (doi)

• A Survey on Multi-view Learning

  • Chang Xu, Dacheng Tao, Chao Xu, arXiv:1304

• A Survey of Multi-View Representation Learning

  • Yingming Li ; Ming Yang ; Zhongfei Mark Zhang, TKDE, 1809

• Learning Representation for Multi-View Data Analysis: Models and Applications

  • Zhengming DingHandong ZhaoYun Fu Link

Spectral Clustering

Single View

• Robust and efficient multi-way spectral clustering, [matlab]

  • Anil Damle, Victor Minden, Lexing Ying, arXiv:1609

• ICML 2018, Fast Approximate Spectral Clustering for Dynamic Networks -Lionel Martin, Andreas Loukas, Pierre Vandergheynst, arXiv:1706

• Efficient Kernel Selection via Spectral Analysis Jian Li, Yong Liu, Hailun Lin, Yinliang Yue, Weiping Wang (PDF | Details)

• Beyond the Nystrom Approximation: Speeding up Spectral Clustering using Uniform Sampling and Weighted Kernel k-means

  • Mahesh Mohan, Claire Monteleoni
  • (PDF | Details)

• Guided Graph Spectral Embedding: Application to the C. elegans Connectome

  • M Petrović, TAW Bolton, MG Preti, R Liégeois
  • (arXiv:1812)

Implementation

• A fast implementation of spectral clustering on GPU-CPU Platform
  • Jin, Yu and JaJa, Joseph F,
  • code

Multiview

• Essential Tensor Learning for Multi-view Spectral Clustering

k-means Clustering

Single View

• ICML 2018, k-means clustering using random matrix sparsification

• Scalable Normalized Cut with Improved Spectral Rotation

  • Xiaojun Chen, Feiping Nie, Joshua Zhexue Huang, Min Yang
  • (PDF | Details)

NIPS 2018

• Differentially Private k-Means with Constant Multiplicative Error

  • U Stemmer, H Kaplan
  • (PDF | Supplemental | Poster)

• Statistical and Computational Trade-Offs in Kernel k-Means

  • Daniele Calandriello, Lorenzo Rosasco
  • (PDF | Supplemental)

• Query k-means Clustering and the Double Dixie Cup Problem

  • I Chien, Chao Pan, Olgica Milenkovic
  • (PDF | Supplemental)

NIPS 2017

• Sparse embedded k-means clustering

  • Weiwei Liu, Xiaobo Shen, Ivor Tsang
  • (PDF | Supplemental | Reviews)

• k-Medoids For k-Means Seeding

  • James Newling, François Fleuret
  • (PDF | Supplemental | Reviews)

• Clustering Stable Instances of Euclidean k-means

  • Aravindan Vijayaraghavan, Abhratanu Dutta, Alex Wang
  • (PDF | Supplemental | Reviews)

• Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting k-means, and Local Search

  • Benjamin Moseley, Joshua Wang
  • (PDF | Supplemental | Reviews)

NIPS 2016

• Fast and Provably Good Seedings for k-Means
  • Olivier Bachem, Mario Lucic, Hamed Hassani, Andreas Krause
  • (PDF | Supplemental | Reviews)

ICML 2016

• k-variates++: more pluses in the k-means++

  • Richard Nock, Raphael Canyasse, Roksana Boreli, Frank Nielsen
  • (PDF | Supplementary Material)

• Fast k-means with accurate bounds

  • James Newling, Francois Fleuret
  • (PDF | Supplementary Material)

• k-Means Clustering with Distributed Dimensions

  • Hu Ding, Yu Liu, Lingxiao Huang, Jian Li
  • (PDF | Supplementary Material)

• Speeding up k-means by approximating Euclidean distances via block vectors

  • Thomas Bottesch, Thomas Bühler, Markus Kächele ; PMLR 48:2578-2586
  • (PDF]

Implementation

• cuda

Co-training

Source

ICML

2015

• On deep multi-view representation learning, [pdf]

• Weiran Wang, Raman Arora, Karen Livescu, Jeff Bilmes, arXiv:1602

NIPS

2018

• Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation

  • Edward Smith, Scott Fujimoto, David Meger

• Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels

  • Shahin Shahrampour, Vahid Tarokh

• Multimodal Generative Models for Scalable Weakly-Supervised Learning

  • Mike Wu, Noah Goodman

• Mental Sampling in Multimodal Representations

  • Jianqiao Zhu, Adam Sanborn, Nick Chater

• Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces

  • Yu-An Chung, Wei-Hung Weng, Schrasing Tong, James Glass

• Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo

  • HOLDEN LEE, Andrej Risteski, Rong Ge

2017

• Multi-view Matrix Factorization for Linear Dynamical System Estimation

  • Mahdi Karami, Martha White, Dale Schuurmans, Csaba Szepesvari

• Learning a Multi-View Stereo Machine

  • Abhishek Kar, Christian Häne, Jitendra Malik

• Multi-View Decision Processes: The Helper-AI Problem

  • Christos Dimitrakakis, David C. Parkes, Goran Radanovic, Paul Tylkin

2010

• Predictive Subspace Learning for Multi-view Data: a Large Margin Approach
  • Ning Chen, Jun Zhu, Eric P. Xing
  • (PDF | Details | Supplemental | TPAMI)

IEEE Transactions on Pattern Analysis and Machine Intelligence

2018

• Binary Multi-View Clustering

2012

• Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis
  • Ning Chen; Jun Zhu; Fuchun Sun; Eric Poe Xing

IEEE Transactions on Image Processing

IEEE Transactions on Knowledge and Data Engineering

IJCAI

2018

• Deep Multi-View Concept Learning, [pdf]

  • Cai Xu, Ziyu Guan, Wei Zhao, Yunfei Niu, Quan Wang, Zhiheng Wang

• Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders, [pdf]

  • Tengfei Ma, Cao Xiao, Jiayu Zhou, Fei Wang

• Quality Matters: Assessing cQA Pair Quality via Transductive Multi-View Learning, [pdf]

  • Xiaochi Wei, Heyan Huang, Liqiang Nie, Fuli Feng, Richang Hong, Tat-Seng Chua

• Robust Multi-view Representation: A Unified Perspective from Multi-view Learning to Domain Adaption, [pdf]

  • Zhengming Ding, Ming Shao, Yun Fu

• Hierarchical Graph Structure Learning for Multi-View 3D Model Retrieval, [pdf]

  • Yuting Su, Wenhui Li, Anan Liu, Weizhi Nie

• CR-GAN: Learning Complete Representations for Multi-view Generation, [pdf]

  • Yu Tian, Xi Peng, Long Zhao, Shaoting Zhang, Dimitris N. Metaxas

• Adaptive Collaborative Similarity Learning for Unsupervised Multi-view Feature Selection, [pdf]

  • Xiao Dong, Lei Zhu, Xuemeng Song, Jingjing Li, Zhiyong Cheng

• Doubly Aligned Incomplete Multi-view Clustering, [pdf]

  • Menglei Hu, Songcan Chen

• Robust Auto-Weighted Multi-View Clustering, [pdf]

  • Pengzhen Ren, Yun Xiao, Pengfei Xu, Jun Guo, Xiaojiang Chen, Xin Wang, Dingyi Fang

• Incomplete Multi-View Weak-Label Learning, [pdf]

  • Qiaoyu Tan, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zili Zhang

• FISH-MML: Fisher-HSIC Multi-View Metric Learning, [pdf]

  • Changqing Zhang, Yeqinq Liu, Yue Liu, Qinghua Hu, Xinwang Liu, Pengfei Zhu

• Robust Multi-view Learning via Half-quadratic Minimization, [pdf]

  • Yonghua Zhu, Xiaofeng Zhu, Wei Zheng

• Semi-Supervised Multi-Modal Learning with Incomplete Modalities, [pdf]

  • Yang Yang, De-Chuan Zhan, Xiang-Rong Sheng, Yuan Jiang

• Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification, [pdf]

  • Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu

2017

• Self-weighted Multiview Clustering with Multiple Graphs

  • Feiping Nie, Jing Li, Xuelong Li
  • (PDF | Details)

• Vertex-Weighted Hypergraph Learning for Multi-View Object Classification

  • Lifan Su, Yue Gao, Xibin Zhao, Hai Wan, Ming Gu, Jiaguang Sun
  • (PDF | Details)

• From Ensemble Clustering to Multi-View Clustering

  • Zhiqiang Tao, Hongfu Liu, Sheng Li, Zhengming Ding, Yun Fu
  • (PDF | Details)

• Multiple Medoids based Multi-view Relational Fuzzy Clustering with Minimax Optimization

  • Yangtao Wang, Lihui Chen, Xiao-Li Li
  • (PDF | Details)

• Dynamic Multi-View Hashing for Online Image Retrieval

  • Liang Xie, Jialie Shen, Jungong Han, Lei Zhu, Ling Shao
  • (PDF | Details)

• Multi-view Feature Learning with Discriminative Regularization

  • Jinglin Xu, Junwei Han, Feiping Nie
  • (PDF | Details)

• Nonlinear Maximum Margin Multi-View Learning with Adaptive Kernel

  • Jia He, Changying Du, Changde Du, Fuzhen Zhuang, Qing He, Guoping Long
  • (PDF | Details)

• Vertex-Weighted Hypergraph Learning for Multi-View Object Classification

  • Lifan Su, Yue Gao, Xibin Zhao, Hai Wan, Ming Gu, Jiaguang Sun
  • (PDF | Details)

• Approximating Discrete Probability Distribution of Image Emotions by Multi-Modal Features Fusion

  • Sicheng Zhao, Guiguang Ding, Yue Gao, Jungong Han
  • (PDF | Details)

• Multiple Kernel Clustering Framework with Improved Kernels

  • Yueqing Wang, Xinwang Liu, Yong Dou, Rongchun Li
  • (PDF | Details)

• Approximate Large-scale Multiple Kernel k-means Using Deep Neural Network

  • Yueqing Wang, Xinwang Liu, Yong Dou, Rongchun Li
  • (PDF | Details)

• Multiple Indefinite Kernel Learning for Feature Selection

  • Hui Xue, Yu Song, Hai-Ming Xu
  • (PDF | Details)

2016

• Iterative Views Agreement: An Iterative Low-Rank Based Structured Optimization Method to Multi-View Spectral Clustering

  • Yang Wang, Wenjie Zhang, Lin Wu, Xuemin Lin, Meng Fang, Shirui Pan, arXiv:1608

• Multiple Kernel Clustering with Local Kernel Alignment Maximization, [pdf]

  • Miaomiao Li, Xinwang Liu, Lei Wang, Yong Dou, Jianping Yin, En Zhu

• Multi-View Learning with Limited and Noisy Tagging, [pdf]

  • Yingming Li, Ming Yang, Zenglin Xu, Zhongfei (Mark) Zhang

AAAI

2019

• MEAL: Multi-Model Ensemble via Adversarial Learning
  • Zhiqiang Shen, Zhankui He, Xiangyang Xue
  • (arXiv:1812 | pytorch)

others

IEEE Transactions on Fuzzy System

• A Multi-view & Multi-exemplar Fuzzy Clustering Approach: Theoretical Analysis and Experimental Studies

  • Zhang Yuanpeng ; Fu-lai Chung ; ShiTong Wang
  • (DOI)

• Deep Collective Matrix Factorization for Augmented Multi-View Learning

  • R Mariappan, V Rajan
  • (arXiv: 1811)

Graph Embedding

LLE

• When Locally Linear Embedding Hits Boundary
  • Hau-tieng Wu, Nan Wu， arXiv:1811