Results 41 to 50 of about 1,099,722 (325)
Sensors, 2022 When learning to play a musical instrument, it is important to improve the quality of self-practice. Many systems have been developed to assist practice. Some practice assistance systems use special sensors (pressure, flow, and motion sensors) to acquire
Jin Kuroda, Gou Koutaki
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Learning to Rank from Samples of Variable Quality [PDF]
, 2018 Training deep neural networks requires many training samples, but in practice, training labels are expensive to obtain and may be of varying quality, as some may be from trusted expert labelers while others might be from heuristics or other sources of ...
Dehghani, Mostafa, Kamps, Jaap
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Towards intelligent geospatial data discovery: a machine learning framework for search ranking
International Journal of Digital Earth, 2018 Current search engines in most geospatial data portals tend to induce users to focus on one single-data characteristic dimension (e.g. popularity and release date).
Yongyao Jiang +8 more
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ADAPTATION OF LAMBDAMART MODEL TO SEMI-SUPERVISED LEARNING
Вісник Національного технічного університету "ХПÌ": Системний аналіз, управління та інформаційні технології, 2023 The problem of information searching is very common in the age of the internet and Big Data. Usually, there are huge collections of documents and only multiple percent of them are relevant. In this setup brute-force methods are useless.
Klym Yamkovyi
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Pairwise Learning to Rank for Image Quality Assessment
IEEE Access, 2020 Because the pairwise comparison is a natural and effective way to obtain subjective image quality scores, we propose an objective full-reference image quality assessment (FR-IQA) index based on pairwise learning to rank (PLR).
Yiqing Shi +4 more
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Automatic Estimation of Ulcerative Colitis Severity by Learning to Rank With Calibration
IEEE Access, 2022 For automatic disease-severity-level estimation, a large-scale medical image dataset with level annotations is generally necessary. However, attaching absolute-level annotations (such as levels 0, 1, and 3) is very costly and even inaccurate due to the ...
Takeaki Kadota +6 more
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Learning to Rank based on Analogical Reasoning
, 2017 Object ranking or "learning to rank" is an important problem in the realm of preference learning. On the basis of training data in the form of a set of rankings of objects represented as feature vectors, the goal is to learn a ranking function that ...
Fahandar, Mohsen Ahmadi +1 more
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Conference Paper Recommendation for Academic Conferences
IEEE Access, 2018 With the rapid growth of scientific publications, research paper recommendation which suggests relevant research papers to users can bring great benefits to researchers.
Shuchen Li +3 more
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Hashing as Tie-Aware Learning to Rank
, 2018 Hashing, or learning binary embeddings of data, is frequently used in nearest neighbor retrieval. In this paper, we develop learning to rank formulations for hashing, aimed at directly optimizing ranking-based evaluation metrics such as Average Precision
Bargal, Sarah Adel +3 more
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Learning to efficiently rank [PDF]
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, 2010 It has been shown that learning to rank approaches are capable of learning highly effective ranking functions. However, these approaches have mostly ignored the important issue of efficiency. Given that both efficiency and effectiveness are important for real search engines, models that are optimized for effectiveness may not meet the strict efficiency
Lidan Wang, Jimmy Lin, Donald Metzler
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