• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 64 matches

• 2020
• 
  Sumia Abdulhussien Razooqi Al-Obaidi, Davood Zabihzadeh, Hamideh Hajiabadi:
  Robust metric learning based on the rescaled hinge loss. Int. J. Mach. Learn. Cybern. 11(11): 2515-2528 (2020)
• 
  Manisha Singla, Debdas Ghosh, K. K. Shukla:
  Improved Sparsity of Support Vector Machine with Robustness Towards Label Noise Based on Rescaled α-Hinge Loss with Non-smooth Regularizer. Neural Process. Lett. 52(3): 2211-2239 (2020)
• 
  Jiaqian Yu, Matthew B. Blaschko:
  The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses. IEEE Trans. Pattern Anal. Mach. Intell. 42(3): 735-748 (2020)
• 
  Manisha Singla, Debdas Ghosh, K. K. Shukla, Witold Pedrycz:
  Robust twin support vector regression based on rescaled Hinge loss. Pattern Recognit. 105: 107395 (2020)
• 
  Kexin Wang, Yu Zhou, Jiajun Zhang, Shaonan Wang, Chengqing Zong:
  Structurally Comparative Hinge Loss for Dependency-Based Neural Text Representation. ACM Trans. Asian Low Resour. Lang. Inf. Process. 19(4): 58:1-58:19 (2020)
• 
  Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daumé III, Lise Getoor:
  Interpretable Engagement Models for MOOCs Using Hinge-Loss Markov Random Fields. IEEE Trans. Learn. Technol. 13(1): 107-122 (2020)
• 
  Imran Razzak, Tariq Mahmood Khan:
  One-Class Support Tensor Machines with Bounded Hinge Loss Function for Anomaly Detection. IJCNN 2020: 1-8
• 
  Franco Pellegrini, Giulio Biroli:
  An analytic theory of shallow networks dynamics for hinge loss classification. NeurIPS 2020
• 
  Kunal Talwar:
  On the Error Resistance of Hinge-Loss Minimization. NeurIPS 2020
• 
  Yutong Wang, Clayton Scott:
  Weston-Watkins Hinge Loss and Ordered Partitions. NeurIPS 2020
• 
  Golnoosh Farnadi, Lise Getoor, Marie-Francine Moens, Martine De Cock:
  User Profiling Using Hinge-loss Markov Random Fields. CoRR abs/2001.01177 (2020)
• 
  Yutong Wang, Clayton D. Scott:
  Weston-Watkins Hinge Loss and Ordered Partitions. CoRR abs/2006.07346 (2020)
• 
  Franco Pellegrini, Giulio Biroli:
  An analytic theory of shallow networks dynamics for hinge loss classification. CoRR abs/2006.11209 (2020)
• 
  Justin Lizama:
  Implicitly Maximizing Margins with the Hinge Loss. CoRR abs/2006.14286 (2020)
• 
  Davood Zabihzadeh, Amar Tuama, Ali Karami-Mollaee:
  Low-Rank Robust Online Distance/Similarity Learning based on the Rescaled Hinge Loss. CoRR abs/2010.03268 (2020)
• 
  Kunal Talwar:
  On the Error Resistance of Hinge Loss Minimization. CoRR abs/2012.00989 (2020)
• 2019
• 
  Ling-Wei Huang, Yuan-Hai Shao, Jun Zhang, Yu-Ting Zhao, Jia-Ying Teng:
  Robust Rescaled Hinge Loss Twin Support Vector Machine for Imbalanced Noisy Classification. IEEE Access 7: 65390-65404 (2019)
• 
  Nan Wang, Yiming Xue, Qiang Lin, Ping Zhong:
  Structured sparse multi-view feature selection based on weighted hinge loss. Multim. Tools Appl. 78(11): 15455-15481 (2019)
• 
  Hanyang Peng, Cheng-Lin Liu:
  Discriminative Feature Selection via Employing Smooth and Robust Hinge Loss. IEEE Trans. Neural Networks Learn. Syst. 30(3): 788-802 (2019)
• 
  Sriram Srinivasan, Behrouz Babaki, Golnoosh Farnadi, Lise Getoor:
  Lifted Hinge-Loss Markov Random Fields. AAAI 2019: 7975-7983
• 
  Hanieh Poostchi, Massimo Piccardi:
  A multi-constraint structured hinge loss for named-entity recognition. ALTA 2019: 41-46
• 
  Yue Zhang, Arti Ramesh:
  Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields. IJCAI 2019: 6050-6056
• 
  Sumia Abdulhussien Razooqi Al-Obaidi, Davood Zabihzadeh, Ali Salim Rasheed, Reza Monsefi:
  Robust Metric Learning based on the Rescaled Hinge Loss. CoRR abs/1904.11711 (2019)
• 
  Denali Molitor, Deanna Needell, Rachel Ward:
  Bias of Homotopic Gradient Descent for the Hinge Loss. CoRR abs/1907.11746 (2019)
• 
  Ilya Kavalerov, Wojciech Czaja, Rama Chellappa:
  cGANs with Multi-Hinge Loss. CoRR abs/1912.04216 (2019)
• 2018
• 
  Bin Gu, Xin Quan, Yunhua Gu, Victor S. Sheng, Guansheng Zheng:
  Chunk incremental learning for cost-sensitive hinge loss support vector machine. Pattern Recognit. 83: 196-208 (2018)
• 
  Hong-Jie Xing, Man Ji:
  Robust one-class support vector machine with rescaled hinge loss function. Pattern Recognit. 84: 152-164 (2018)
• 
  Ryota Kamiya, Yoshikazu Washizawa:
  Discriminative sparse representation learning using multiclass hinge loss. APSIPA 2018: 955-958
• 
  Jeffrey Hajewski, Suely Oliveira, David E. Stewart:
  Smoothed Hinge Loss and ℓ1 Support Vector Machines. ICDM Workshops 2018: 1217-1223
• 
  Vasily Sachnev, B. S. Mahanand:
  A Cognitive Ensemble Classifier based on Risk Sensitive Hinge Loss Function for Alzheimer's Disease diagnosis in early stages. SSCI 2018: 807-812

skipping 34 more matches