Results 51 to 60 of about 167,597 (287)
A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model [PDF]
ACM-SIAM Symposium on Discrete Algorithms, 2017 We study the active learning problem of top-$k$ ranking from multi-wise comparisons under the popular multinomial logit model. Our goal is to identify the top-$k$ items with high probability by adaptively querying sets for comparisons and observing the ...
Xi Chen, Yuanzhi Li, Jieming Mao
semanticscholar +1 more source
Sustainability, 2019 At present, electric cars are being developed rapidly in China as emerging carbon emission reduction vehicles, but their proportion in the Chinese automobile market is still small, and a large number of potential consumers are still holding a wait-and ...
Q. Yan +3 more
semanticscholar +1 more source
Learning to Rank under Multinomial Logit Choice
, 2020 updated with new material including regret bound for unknown position bias ...
Grant, James A., Leslie, David S.
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Multinomial Logit Bandit with Linear Utility Functions [PDF]
International Joint Conference on Artificial Intelligence, 2018 Multinomial logit bandit is a sequential subset selection problem which arises in many applications. In each round, the player selects a K-cardinality subset from N candidate items, and receives a reward which is governed by a multinomial logit (MNL ...
Mingdong Ou +3 more
semanticscholar +1 more source
Estimating Multinomial Logit Model with Multicollinear Data
Asian Journal of Mathematics & Statistics, 2010 The multinomial model is used to study the dependence relationship between a categorical response variable with more than two categories and a set of explicative variables. In presence of multicollinearity, the estimation of the multinomial model parameters becomes inaccurate.
CAMMINATIELLO, Ida, Lucadamo A.
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Penalized multinomial mixture logit model [PDF]
Computational Statistics, 2009 A classification problem is considered where the observed classes are mixtures of some subclasses. The multinomial logit model is used to model the dependence between subclasses labels and predictors. A version of the EM algorithm is proposed for fitting the resulting mixture model.
Bashir, Shaheena, Carter, Edward M.
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Multinomial Logit Model of Pedestrian Crossing Behaviors at Signalized Intersections
Discrete Dynamics in Nature and Society, 2013 Pedestrian crashes, making up a large proportion of road casualties, are more likely to occur at signalized intersections in China. This paper aims to study the different pedestrian behaviors of regular users, late starters, sneakers, and partial ...
Zhu-Ping Zhou +3 more
doaj +1 more source
Sustainability, 2019 Understanding the risk factors of e-bike collisions can improve e-bike riders’ safety awareness and help traffic professionals to develop effective countermeasures.
Yanyong Guo +3 more
semanticscholar +1 more source
Transportation Research Record, 2018 Discrete choice modeling is a fundamental part of travel demand forecasting. To date, this field has been dominated by parametric approaches (e.g., logit models), but non-parametric approaches such as artificial neural networks (ANNs) possess much ...
Dongwook Lee +2 more
semanticscholar +1 more source
Advances in Mechanical Engineering, 2017 Among the ways to construct experimental designs having been proposed, orthogonal design, uniform design, and D-efficient design are state-of-the-art methods. This article provides detailed comparisons on the efficiency and robustness among these methods
Hai Zhu +4 more
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