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Guo Zhou, Yongquan Zhou
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Top-rank convolutional neural network and its application to medical image-based diagnosis
10.1016/j.patcog.2021.108138 · 2021
Learning to rank for information retrieval
10.1561/1500000016 · 2009
Optimizing search engines using clickthrough data
2002
Learning to rank using gradient descent
2005
Learning to rank for information retrieval and natural language processing
10.1007/978-3-031-02155-8 · 2011
Stability and generalization of bipartite ranking algorithms
2005
Generalization bounds for the area under the ROC curve
2005
Bipartite ranking: a risk-theoretic perspective
2016
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2018
The meaning and use of the area under a receiver operating characteristic (ROC) curve
10.1148/radiology.143.1.7063747 · 1982
AUC optimization vs. error rate minimization
2003
Ranking and empirical minimization of U-statistics
10.1214/009052607000000910 · 2008
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2005
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1998
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Unresolved referenced work
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Large-scale linear RankSVM
10.1162/neco_a_00571 · 2014
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2016
RankSVM for offline signature verification
2019
UriBLAD: a urine-based gene expression assay for noninvasive detection of bladder cancer
10.1016/j.jmoldx.2020.10.005 · 2021
Computational prediction and characterization of cell-type-specific and shared binding sites
10.1093/bioinformatics/btac798 · 2022
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2004
Combining ranking with traditional methods for ordinal class imbalance
2017
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2013
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2007
Accuracy at the top
2012
Top rank optimization in linear time
2014
Future directions in learning to rank
2011
Learning to rank: from pairwise approach to listwise approach
2007
Statistical analysis of Bayes optimal subset ranking
10.1109/tit.2008.929939 · 2008
Large margin rank boundaries for ordinal regression
2000
Listwise approach to learning to rank: theory and algorithm
2008
Bipartite ranking from multiple labels: on loss versus label aggregation
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2003
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2009
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Recranker: instruction tuning large language model as ranker for top-k recommendation
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Beyond singular prototype: a prototype splitting strategy for few-shot medical image segmentation
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Paired contrastive feature for highly reliable offline signature verification
10.1016/j.patcog.2023.109816 · doi-reference
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10.1016/j.neucom.2023.127172 · doi-reference
Ultrasound volume projection image quality selection by ranking from convolutional RankNet
10.1016/j.compmedimag.2020.101847 · doi-reference
Deep ranking for person re-identification via joint representation learning
10.1109/tip.2016.2545929 · doi-reference
Listwise learning to rank by exploring structure of objects
10.1109/tkde.2016.2535214 · doi-reference
Learning bregman distance functions for structural learning to rank
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Learning to rank using user clicks and visual features for image retrieval
10.1109/tcyb.2014.2336697 · doi-reference
Picture collage
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Analysis and optimization of loss functions for multiclass, top-k, and multilabel classification
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10.1016/j.patcog.2023.109682 · doi-reference
Optimizing two-way partial AUC with an end-to-end framework
10.1109/tpami.2022.3185311 · doi-reference
AUC maximization in the era of big data and AI: a survey
10.1145/3554729 · doi-reference
Statistical analysis of Bayes optimal subset ranking
10.1109/tit.2008.929939 · doi-reference
Computational prediction and characterization of cell-type-specific and shared binding sites
10.1093/bioinformatics/btac798 · doi-reference
UriBLAD: a urine-based gene expression assay for noninvasive detection of bladder cancer
10.1016/j.jmoldx.2020.10.005 · doi-reference
Large-scale linear RankSVM
10.1162/neco_a_00571 · doi-reference
Ranking and empirical minimization of U-statistics
10.1214/009052607000000910 · doi-reference
The meaning and use of the area under a receiver operating characteristic (ROC) curve
10.1148/radiology.143.1.7063747 · doi-reference
Learning to rank for information retrieval and natural language processing
10.1007/978-3-031-02155-8 · doi-reference
Top-rank convolutional neural network and its application to medical image-based diagnosis
10.1016/j.patcog.2021.108138 · doi-reference
Learning to rank for information retrieval
10.1561/1500000016 · doi-reference