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Probabilistic Label Trees for Extreme Multi-label Classification
Extreme multi-label classification (XMLC) is a learning task of tagging ...
09/23/2020 ∙ by Kalina Jasinska-Kobus, et al. ∙
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Optimal Learning of Mallows Block Model
The Mallows model, introduced in the seminal paper of Mallows 1957, is o...
06/03/2019 ∙ by Robert Busa-Fekete, et al. ∙
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On the computational complexity of the probabilistic label tree algorithms
Label tree-based algorithms are widely used to tackle multi-class and mu...
06/01/2019 ∙ by Robert Busa-Fekete, et al. ∙
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Learning to Crawl
Web crawling is the problem of keeping a cache of webpages fresh, i.e., ...
05/29/2019 ∙ by Utkarsh Upadhyay, et al. ∙
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A no-regret generalization of hierarchical softmax to extreme multi-label classification
Extreme multi-label classification (XMLC) is a problem of tagging an ins...
10/27/2018 ∙ by Marek Wydmuch, et al. ∙
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Preference-based Online Learning with Dueling Bandits: A Survey
In machine learning, the notion of multi-armed bandits refers to a class...
07/30/2018 ∙ by Robert Busa-Fekete, et al. ∙
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Distributed Stochastic Optimization via Adaptive Stochastic Gradient Descent
Stochastic convex optimization algorithms are the most popular way to tr...
02/16/2018 ∙ by Ashok Cutkosky, et al. ∙
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Fast classification using sparse decision DAGs
In this paper we propose an algorithm that builds sparse decision DAGs (...
06/27/2012 ∙ by Djalel Benbouzid, et al. ∙
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