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Multi-class classification problem is among the most popular and well-studied statistical frameworks.
1903
Earlier work this paper cites.
1904
Earlier work this paper cites.
[author] Chow, C. -K. C. (1957). An optimum character recognition system using decision functions. IRE Transactions on Electronic Computers 4 247–254
1957
Earlier work this paper cites.
[author] Chow, C.C. (1970). On optimum error and reject trade-off. IEEE Trans. Inform. Theory 16 41–46
1970
Earlier work this paper cites.
Grycko, E
1993
Earlier work this paper cites.
[author] Turney, Peter DP. D. (1994). Cost-sensitive classification: Empirical evaluation of a hybrid genetic decision tree induction algorithm. Journal of artificial intelligence research 2 369–409
1994
Earlier work this paper cites.
Ha, T. M
1996
Earlier work this paper cites.
[author] LeCun, YannY., Bottou, LéonL., Bengio, YoshuaY. and Haffner, PatrickP. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE 86 2278–2324
1998
Earlier work this paper cites.
[author] Vapnik, V.V. (1998). Statistical learning theory. Wiley
1998
Earlier work this paper cites.
Elkan, C
2001
Earlier work this paper cites.
Ling, C. X
2003
Earlier work this paper cites.
[author] Zhang, TongT. (2004). Statistical behavior and consistency of classification methods based on convex risk minimization. Annals of Statistics 56–85
2004
Earlier work this paper cites.
[author] Bartlett, P.P., Jordan, M.M. and McAuliffe, J.J. (2006). Convexity, classification, and risk bounds. Journal of the American Statistical Association 101 138–156
2006
Earlier work this paper cites.
[author] Herbei, R.R. and Wegkamp, M.M. (2006). Classification with reject option. Canad. J. Statist. 34 709–721
2006
Earlier work this paper cites.
2006
Earlier work this paper cites.
Ciregan, D
2012
Earlier work this paper cites.
[author] Dembczyński, KrzysztofK., Waegeman, WillemW., Cheng, WeiweiW. and Hüllermeier, EykeE. (2012). On label dependence and loss minimization in multi-label classification. Machine Learning 88 5–45
2012
Earlier work this paper cites.
[author] Royle, J AndrewJ. A., Chandler, Richard BR. B., Yackulic, CharlesC. and Nichols, James DJ. D. (2012). Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions. Methods in Ecology and Evolution 3 545–554
2012
Cited alongside, same era.
2012
Cited alongside, same era.
[author] Embrechts, PaulP. and Hofert, MariusM. (2013). A note on generalized inverses. Mathematical Methods of Operations Research 77 423–432
2013
Cited alongside, same era.
[author] Hastie, TrevorT. and Fithian, WillW. (2013). Inference from presence-only data; the ongoing controversy. Ecography 36 864–867
2013
Cited alongside, same era.
[author] Bhatia, K.K., Dahiya, K.K., Jain, H.H., Mittal, A.A., Prabhu, Y.Y. and Varma, M.M. (2016). The extreme classification repository: Multi-label datasets and code
2016
Later among the works it cites.
[author] Champ, JulienJ., Lorieul, TitouanT., Bonnet, PierreP., Maghnaoui, NajateN., Sereno, ChristopheC., Dessup, ThierryT., Boursiquot, Jean-MichelJ.-M., Audeguin, LaurentL., Lacombe, ThierryT. and Joly, AlexisA. (2016). Categorizing plant images at the variety level: Did you say fine-grained? Pattern Recognition Letters 81 71–79
2016
Later among the works it cites.
Lapin, M
2016
Later among the works it cites.
[author] Denis, ChristopheC. and Hebiri, MohamedM. (2017). Confidence sets with expected sizes for multiclass classification. Journal of Machine Learning Research 18 1-28
2017
Later among the works it cites.
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2013
Cited alongside, same era.
[author] Zhang, Min-LingM.-L. and Zhou, Zhi-HuaZ.-H. (2013). A review on multi-label learning algorithms. IEEE transactions on knowledge and data engineering 26 1819–1837
2013
Cited alongside, same era.
[author] Cai, T. TonyT. T., Low, MarkM. and Ma, ZongmingZ. (2014). Adaptive Confidence Bands for Nonparametric Regression Functions. Journal of the American Statistical Association 109 1054-1070
2014
Cited alongside, same era.
[author] Le Capitaine, HoelH. (2014). A unified view of class-selection with probabilistic classifiers. Pattern recognition 47 843–853
2014
Cited alongside, same era.
[author] Lei, JingJ. (2014). Classification with Confidence. Biometrika
2014
Cited alongside, same era.
[author] Lei, JingJ. and Wasserman, LarryL. (2014). Distribution-free prediction bands for non-parametric regression. Journal of the Royal Statistical Society Series B 76 71-96
2014
Cited alongside, same era.
Champ, J
2015
Cited alongside, same era.
[author] Göeau, HervéH., Joly, AlexisA. and Bonnet, PierreP. (2015a). LifeCLEF plant identification task 2015. CLEF working notes 2015
2015
Cited alongside, same era.
[author] Lambin, PhilippeP., Zindler, JaapJ., Vanneste, Ben GLB. G., Van De Voorde, LienL., Eekers, DanielleD., Compter, IngeI., Panth, Kranthi MarellaK. M., Peerlings, JurgenJ., Larue, Ruben THMR. T., Deist, Timo MT. M. et al. (2017). Decision support systems for personalized and participative radiation oncology. Advanced drug delivery reviews 109 131–153
2017
Later among the works it cites.
[author] Vovk, VladimirV., Nouretdinov, IliaI., Fedorova, ValentinaV., Petej, IvanI. and Gammerman, AlexA. (2017). Criteria of efficiency for set-valued classification. Annals of Mathematics and Artificial Intelligence 81 21-47
2017
Later among the works it cites.
[author] Berrada, LeonardL., Zisserman, AndrewA. and Kumar, M PawanM. P. (2018). Smooth loss functions for deep top-k classification. ICLR
2018
Later among the works it cites.
[author] Lei, J.J., G’Sell, M.M., Rinaldo, A.A., Tibshirani, R.R. and Wasserman, L.L. (2018). Distribution-free predictive inference for regression. J. Amer. Statist. Assoc. 113 1094–1111
2018
Later among the works it cites.
[author] Ramaswamy, Harish GH. G., Tewari, AmbujA., Agarwal, ShivaniS. et al. (2018). Consistent algorithms for multiclass classification with an abstain option. Electronic Journal of Statistics 12 530–554
2018
Later among the works it cites.
[author] Zhang, ChongC., Wang, WenboW. and Qiao, XingyeX. (2018). On reject and refine options in multicategory classification. J. Amer. Statist. Assoc. 113 730–745
2018
Later among the works it cites.
Mac Aodha, O
2019
Later among the works it cites.
[author] Ni, C.C., Charoenphakdee, N.N., Honda, J.J. and Sugiyama, M.M. (2019). On the Calibration of Multiclass Classification with Rejection. In Advances in Neural Information Processing Systems 32 2586–2596
2019
Later among the works it cites.
[author] Denis, ChristopheC. and Hebiri, MohamedM. (2020). Consistency of plug-in confidence sets for classification in semi-supervised learning. Journal of Nonparametric Statistics 32 42–72
2020
Later among the works it cites.
[author] Gyöfi, L.L. and Walk, H.H. (2020). Nearest neighbor based conformal prediction. Submitted
2020
Later among the works it cites.
[author] Lorieul, TitouanT., Joly, AlexisA. and Shasha, DennisD. (2020). Average-K classification: when and how to predict adaptive confidence sets rather than top-K
2020
Later among the works it cites.
[author] Chzhen, EvgeniiE., Denis, ChristopheC. and Hebiri, MohamedM. (2021). Minimax semi-supervised set-valued approach to multi-class classification. Bernoulli
2021
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