Multiple Choice Learning: Learning to Produce Multiple Structured Outputs
暂无分享,去创建一个
Pushmeet Kohli | Dhruv Batra | Abner Guzmán-Rivera | Pushmeet Kohli | Dhruv Batra | Abner Guzmán-Rivera
[1] E. Lawler. A PROCEDURE FOR COMPUTING THE K BEST SOLUTIONS TO DISCRETE OPTIMIZATION PROBLEMS AND ITS APPLICATION TO THE SHORTEST PATH PROBLEM , 1972 .
[2] W. A. Martin,et al. Parsing , 1980, ACL.
[3] Edward Courtney,et al. 5 = 10 M , 1993 .
[4] D. Opitz,et al. Popular Ensemble Methods: An Empirical Study , 1999, J. Artif. Intell. Res..
[5] Marie-Pierre Jolly,et al. Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[6] Marie-Pierre Jolly,et al. Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images , 2001, ICCV.
[7] Olga Veksler,et al. Fast Approximate Energy Minimization via Graph Cuts , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[8] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[9] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[10] Ben Taskar,et al. Max-Margin Markov Networks , 2003, NIPS.
[11] Y. Weiss,et al. Finding the M Most Probable Configurations using Loopy Belief Propagation , 2003, NIPS 2003.
[12] Vladimir Kolmogorov,et al. What energy functions can be minimized via graph cuts? , 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[13] R. Zabih,et al. What energy functions can be minimized via graph cuts , 2004 .
[14] Anoop Sarkar,et al. Discriminative Reranking for Machine Translation , 2004, NAACL.
[15] Marisa E. Campbell,et al. SIGGRAPH 2004 , 2004, INTR.
[16] Andrew Blake,et al. "GrabCut" , 2004, ACM Trans. Graph..
[17] Michael Collins,et al. Discriminative Reranking for Natural Language Parsing , 2000, CL.
[18] David Chiang,et al. Better k-best Parsing , 2005, IWPT.
[19] Thomas Hofmann,et al. Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..
[20] Jianguo Zhang,et al. The PASCAL Visual Object Classes Challenge , 2006 .
[21] Luc Van Gool,et al. The 2005 PASCAL Visual Object Classes Challenge , 2005, MLCW.
[22] Vladimir Kolmogorov,et al. Convergent Tree-Reweighted Message Passing for Energy Minimization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Yair Weiss,et al. Minimizing and Learning Energy Functions for Side-Chain Prediction , 2007, RECOMB.
[24] Christoph H. Lampert,et al. Learning to Localize Objects with Structured Output Regression , 2008, ECCV.
[25] Pushmeet Kohli,et al. Measuring uncertainty in graph cut solutions , 2008, Comput. Vis. Image Underst..
[26] Amir Globerson,et al. An LP View of the M-best MAP problem , 2009, NIPS.
[27] Thorsten Joachims,et al. Cutting-plane training of structural SVMs , 2009, Machine Learning.
[28] Dan Klein,et al. Top-Down K-Best A* Parsing , 2010, ACL.
[29] Jiebo Luo,et al. iCoseg: Interactive co-segmentation with intelligent scribble guidance , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[30] Christoph H. Lampert. Maximum Margin Multi-Label Structured Prediction , 2011, NIPS.
[31] Deva Ramanan,et al. N-best maximal decoders for part models , 2011, 2011 International Conference on Computer Vision.
[32] Gregory Shakhnarovich,et al. Diverse M-Best Solutions in Markov Random Fields , 2012, ECCV.
[33] Лобинский Павел Андреевич. Решение задачи тактического планирования производства с помощью IBM ILOG CPLEX Optimization Studio , 2012 .
[34] Martial Hebert,et al. Contextual Sequence Prediction with Application to Control Library Optimization , 2012, Robotics: Science and Systems.
[35] Pascal Fua,et al. SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.