Shifting multi-hypergraphs via collaborative probabilistic voting

Kim S, Nowozin S, Kohli P, Yoo CD (2011) Higher-order correlation clustering for image segmentation. In: Shawe-Taylor J, Zemel RS, Bartlett PL, Pereira FCN, Weinberger KQ (eds) Advances in neural information processing systems 24: 25th annual conference on neural information processing systems 2011. Proceedings of a meeting held 12–14 Dec 2011, Granada, Spain

Cho M, Lee KM (2012) Progressive graph matching: making a move of graphs via probabilistic voting. In: 2012 IEEE conference on computer vision and pattern recognition, Providence, RI, USA, 16–21 June 2012

Pavan M, Pelillo M (2007) Dominant sets and pairwise clustering. IEEE Trans Pattern Anal Mach Intell 29(1):167–171

Cho M, Lee KM (2012) Mode-seeking on graphs via random walks. In: 2012 IEEE conference on computer vision and pattern recognition, Providence, RI, USA, 16–21 June 2012

Wu L, Wang Y, Shepherd J (2013) Efficient image and tag co-ranking: a bregman divergence optimization method. In: Jaimes A, Sebe N, Boujemaa N, Gatica-Perez D, Shamma DA, Worring M, Zimmermann R (eds) ACM multimedia conference, MM ’13. Barcelona, Spain, 21–25 Oct 2013

Liu H, Yan S (2010) Robust graph mode seeking by graph shift. In: Frnkranz J, Joachims T (eds) Proceedings of the 27th international conference on machine learning (ICML-10), June 21–24, 2010. Haifa, Israel, pp 671–678

Comaniciu D, Meer P (2002) Mean shift: a robust approach toward feature space analysis. IEEE Trans Pattern Anal Mach Intell 24(5):603–619

Wang Y, Huang X, Wu L (2013) Clustering via geometric median shift over Riemannian manifolds. Inf Sci 20:292–305

Wang Y, Huang X (2010) Geometric median-shift over riemannian manifolds. In: Zhang B-T, Orgun MA (eds) PRICAI 2010: trends in artificial intelligence, 11th Pacific Rim international conference on artificial intelligence, Daegu, Korea, August 30–September 2, 2010. Proceedings. pp 268–279

Sheikh Y, Khan EA, Kanade T (2007) Mode seeking by medoidshifts. In: IEEE 11th international conference on computer vision, ICCV 2007, Rio de Janeiro, Brazil, 14–20 Oct 2007

Wang Y, Wu L, Huang X, Lin X (2012) Human action recognition from video sequences by enforcing tri-view constraints. Comput J 55(9):1030–1040

Wang Y, Lin X, Zhang Q (2013) Towards metric fusion on multi-view data: a cross-view based graph random walk approach. In: He Q, Iyengar A, Nejdl W, Pei J, Rastogi R (eds) 22nd ACM international conference on information and knowledge management, CIKM’13, San Francisco, CA, USA, October 27–November 1, 2013

Wang Y, Lin X, Wu L et al (2014) Exploiting correlation consensus: towards subspace clustering for multi-modal data. In: 22nd ACM international conference on multimedia, ACM Multimedia’14, Orlando, FL, USA, 3–7 Nov 2014

Wang Y, Pei J, Lin X, Zhang Q, Zhang W (2014) An iterative fusion approach to graph-based semi-supervised learning from multiple views. In: Tseng VS, Ho TB, Zhou Z-H, Chen ALP, Kao H-Y (eds) Advances in knowledge discovery and data mining—18th Pacific-Asia conference, PAKDD 2014, Tainan, Taiwan, 13–16 May 2014. Proceedings, part II

Wang Y, Cheema MA, Lin X, Zhang Q (2013) Multi-manifold ranking: using multiple features for better image retrieval. In: Pei J, Tseng VS, Cao L, Motoda H, Xu G (eds) Advances in knowledge discovery and data mining, 17th Pacific-Asia conference, PAKDD 2013, Gold Coast, Australia, 14–17 April 2013. Proceedings, part II

Wang Y, Lin X, Zhang Q, Wu L (2014) Shifting hypergraphs by probabilistic voting. In: Tseng VS, Ho TB, Zhou Z-H, Chen ALP, Kao H-Y (eds) Advances in knowledge discovery and data mining—18th Pacific-Asia conference, PAKDD 2014, Tainan, Taiwan, May 13–16, 2014, pp 234–246

Huang Y, Liu Q, Zhang S, Metaxas DN (2010) Image retrieval via probabilistic hypergraph ranking. In: The twenty-third IEEE conference on computer vision and pattern recognition, CVPR 2010, San Francisco, CA, USA, 13–18 June 2010

Ding L, Yilmaz A (2010) Parallel mining of association rules. Pattern Recognit 43(5):1863–1873

Bomze IM (2002) Branch-and-bound approaches to standard quadratic optimization problems. J Glob Optim 22(1–4):17–37

Weibull JW (1995) Evolutionary game theory. MIT Press, Cambridge 1995

Zangwill WI (1969) Nonlinear programming: a unified approach. Pretice-Hall press, Upper Saddle River

Lowe DG (1999) Object recognition from local scale-invariant features. In: Proceedings of the international conference on computer vision, Kerkyra, Corfu, Greece, 20–25 Sept 1999

Boureau Y-L, Bach F, LeCun Y, Ponce J (2010) Learning mid-level features for recognition. In: The twenty-third IEEE conference on computer vision and pattern recognition, CVPR 2010, San Francisco, CA, USA, 13–18 June 2010

Duchenme O, Bach F, Kweon I, Ponce J (2009) A tensor-based algorithm for high-order graph matching. In: 2009 IEEE computer society conference on computer vision and pattern recognition (CVPR 2009), Miami, FL, USA, 20–25 June 2009

Zass R, Shashua A (2008) Probabilistic graph and hypergraph matching. In: 2008 IEEE computer society conference on computer vision and pattern recognition (CVPR 2008), Anchorage, Alaska, USA, 24–26 June 2008

Leoradeanu M, Hebert M (2005) A spectral technique for correspondence problems using pairwise constraints. In: Carey MJ, Schneider DA (eds) 10th IEEE international conference on computer vision (ICCV 2005), Beijing, China, 17–20 Oct 2005

Leordeanu M, Hebert M, Sukthankar R (2009) Integer projected fixed point for graph matching and map inference. In: Bengio Y, Schuurmans D, Lafferty JD, Williams CKI, Culotta A (eds) Advances in neural information processing systems 22: 23rd annual conference on neural information processing systems 2009. Proceedings of a meeting held 7–10 December 2009, Vancouver, BC, Canada

Leordeanu M, Sminchisescu C (2012) Efficient hypergraph clustering. In: Lawrence ND, Girolami M (eds) Proceedings of the fifteenth international conference on artificial intelligence and statistics, AISTATS 2012, La Palma, Canary Islands, April 21–23, 2012, pp 676–684

Goferman S, Zelnik-Manor L, Tal A (2010) Context-aware saliency detection. In: The twenty-third IEEE conference on computer vision and pattern recognition, CVPR 2010, San Francisco, CA, USA, 13–18 June 2010

Cheng M-M, Zhang G-X, Mitra NJ, Huang X, Hu S-M (2011) Global contrast based salient region detection. In: The 24th IEEE conference on computer vision and pattern recognition, CVPR 2011, Colorado Springs, CO, USA, 20–25 June 2011

Liu H, Latecki L, Yan S (2010) Robust clustering as ensembles of affinity relations. In: Lafferty JD, Williams CKI, Shawe-Taylor J, Zemel RS, Culotta A (eds) Advances in neural information processing systems 23: 24th annual conference on neural information processing systems 2010. Proceedings of a meeting held 6–9 December 2010, Vancouver, BC, Canada

Bulo S, Pellilo M (2009) A game-theoretic approach to hypergraph clustering. In: Bengio Y, Schuurmans D, Lafferty JD, Williams CKI, Culotta A (eds) Advances in neural information processing systems 22: 23rd annual conference on neural information processing systems 2009. Proceedings of a meeting held 7–10 December 2009, Vancouver, BC, Canada

Everingham M, Van Gool L, Williams CKI, Winn J, Zisserman A (2012) The PASCAL visual object classes challenge 2012 (VOC2012) results. http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html

Macrini D, Siddiqi K, Dickinson S (2008) From skeletons to bone graphs: medial abstractions for object recognition. In: 2008 IEEE computer society conference on computer vision and pattern recognition (CVPR 2008), 24–26 June 2008, Anchorage, Alaska, USA