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Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Yasemin Altun,Kamalika Das,Sa?o D?eroski Conference proceedings

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31#
發(fā)表于 2025-3-26 23:06:43 | 只看該作者
32#
發(fā)表于 2025-3-27 01:16:41 | 只看該作者
A Novel Framework for Online Sales Burst Predictionhe seasonal and categorical features of sales burst. Based on the real data from JD.com, we conduct extensive experiments and discover that the proposed model makes a relative MSE improvement of 71% and 30% over LSTM and ARMA.
33#
發(fā)表于 2025-3-27 09:14:48 | 只看該作者
Analyzing Granger Causality in Climate Data with Time Series Classification Methodsatasets from the area of climate-vegetation dynamics. The results indicate that specialized time series classification methods are able to improve existing inference procedures. Substantial differences are observed among the methods that were tested.
34#
發(fā)表于 2025-3-27 12:14:19 | 只看該作者
Probabilistic Inference of Twitter Users’ Age Based on What They Followdetermining the age of Twitter users from data that is native to the Twitter ecosystem. The key idea is to use a Bayesian framework to generalise ground-truth age information from a few Twitter users to the entire network based on what/whom they follow. Our approach scales to inferring the age of 700 million Twitter accounts with high accuracy.
35#
發(fā)表于 2025-3-27 15:07:55 | 只看該作者
36#
發(fā)表于 2025-3-27 18:11:35 | 只看該作者
37#
發(fā)表于 2025-3-28 00:29:10 | 只看該作者
38#
發(fā)表于 2025-3-28 04:10:51 | 只看該作者
Optimal Client Recommendation for Market Makers in Illiquid Financial Productst recommendations for a particular bond that needs to be traded, ranked by probability of interest. We show that a model based on Latent Dirichlet Allocation offers promising performance to deliver relevant recommendations for sales traders.
39#
發(fā)表于 2025-3-28 09:50:36 | 只看該作者
40#
發(fā)表于 2025-3-28 13:20:15 | 只看該作者
Conference proceedings 2017covery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017.?.The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track.?.The contributions wer
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