Titlebook: Machine Learning and Knowledge Discovery in Databases. Research Track; European Conference, Albert Bifet,Jesse Davis,Indr? ?liobait? Confer

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/620545.jpg

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https://doi.org/10.1007/978-3-031-70344-7artificial intelligence; computer security; computer systems; computer vision; computational modelling; d

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0302-9743 k:?.The 56 full papers presented here, from this track, were carefully reviewed and selected from 224 submissions. These papers are present in the following volumes: Part IX and Part X..978-3-031-70343-0978-3-031-70344-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Landscape Analysis of?Stochastic Policy Gradient Methodse population and the empirical objective. In particular, our findings are agnostic to the choice of the algorithm and hold for a wide range of gradient-based methods. Consequently, we are able to recover and improve numerous existing results through the vanilla policy gradient. To the best of our kn

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Frequency Enhanced Pre-training for?Cross-City Few-shot Traffic Forecastingime and frequency domain and trains it with self-supervised tasks encompassing reconstruction and contrastive objectives. In the fine-tuning stage, we design modules to enrich training samples and maintain a momentum-updated graph structure, thereby mitigating the risk of overfitting to the few-shot

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Simple Graph Condensationoduce the Simple Graph Condensation (SimGC) framework, which aligns the condensed graph with the original graph from the input layer to the prediction layer, guided by a pre-trained Simple Graph Convolution (SGC) model on the original graph. Importantly, SimGC eliminates external parameters and excl

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