Results 41 to 50 of about 9,334,973 (302)
Top-1 accuracy (%) for models with different K on CIFAR10 and CIFAR100.
, 2023 Top-1 accuracy (%) for models with different K on CIFAR10 and CIFAR100.
Jiawei Peng (9733744) +5 more
core +1 more source
Top-k Spatial Preference Queries [PDF]
2007 IEEE 23rd International Conference on Data Engineering, 2007 A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, consider a real estate agency office that holds a database with available flats for lease. A customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other ...
Man Lung Yiu +3 more
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Top-k Ranking Bayesian Optimization
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 This paper presents a novel approach to top-k ranking Bayesian optimization (top-k ranking BO) which is a practical and significant generalization of preferential BO to handle top-k ranking and tie/indifference observations. We first design a surrogate model that is not only capable of catering to the above observations, but is also supported by a ...
Quoc Phong Nguyen +3 more
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Top-1 errors (%) for models with different K on CIFAR10.
, 2023 Top-1 errors (%) for models with different K on CIFAR10.
Jiawei Peng (9733744) +5 more
core +1 more source
Ensemble-based Top-k Recommender System Considering Incomplete Data [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user ...
M. Moradi, J. Hamidzadeh
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Successive Halving Top-k Operator
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 We propose a differentiable successive halving method of relaxing the top-k operator, rendering gradient-based optimization possible. The need to perform softmax iteratively on the entire vector of scores is avoided using a tournament-style selection. As a result, a much better approximation of top-k and lower computational cost is achieved compared to
Pietruszka, Michał +2 more
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Collaborative personalized top-k processing [PDF]
ACM Transactions on Database Systems, 2011 This article presents P4Q, a fully decentralized gossip-based protocol to personalize query processing in social tagging systems. P4Q dynamically associates each user with social acquaintances sharing similar tagging behaviors. Queries are gossiped among such acquaintances, computed on-the-fly in a collaborative, yet partitioned manner ...
Xiao Bai 0002 +3 more
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Top-k keyword search over probabilistic XML data
, 2011 Despite the proliferation of work on XML keyword query, it remains open to support keyword query over probabilistic XML data. Compared with traditional keyword search, it is far more expensive to answer a keyword query over probabilistic XML data due to ...
Chengfei Liu (18926683) +3 more
core +2 more sources
Semantic-Aware Top-k Multirequest Optimal Route
Complexity, 2019 In recent years, research on location-based services has received a lot of interest, in both industry and academic aspects, due to a wide range of potential applications.
Shuang Wang +8 more
doaj +1 more source
Approximate distributed top-k queries [PDF]
Distributed Computing, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Boaz Patt-Shamir, Allon Shafrir
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