provide a systematic review of approaches that apply deep learning models at various levels within the query execution engine. We categorize these approaches into three groups based on how such models are applied: improving performance of index structures and consequently data manipulation algorithms, que...
However, the selection of beneficial indexes is a non-trivial problem and still challenging. Recent work in deep reinforcement learning (DRL) may bring a new perspective on this problem. In this paper, we studied the index selection problem in the context of reinforcement learning and proposed ...
We first define trajectory data and provide a brief overview of widely-used deep learning models. Systematically, we explore deep learning applications in trajectory management (pre-processing, storage, analysis, and visualization) and mining (trajectory-related forecasting, trajectory-related recommendation...
State of health is a critical state which evaluates the degradation level of batteries. However, it cannot be measured directly but requires estimation. While accurate state of health estimation has progressed markedly, the time- and resource-consuming d
Here, we introduce spatial architecture characterization by deep learning (SPACEL) for ST data analysis. SPACEL comprises three modules: Spoint embeds a multiple-layer perceptron with a probabilistic model to deconvolute cell type composition for each spot in a single ST slice; Splane employs a ...
Moreover, these signatures are often limited to local, contiguous sequences within the data whilst ignoring their context in relation to each other and throughout the malware file as a whole. We present a Deep Learning based malware classification approach that requires no expert domain knowledge ...
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In this work, we used BERT-Base, a multi-lingual uncased pre-trained model, which was trained with the Multi-Genre Natural Language Inference (MultiNLI) corpus. 2.4.3. BETO This word-embedding model is a Spanish version of BERT proposed in [41]. The model was trained with Spanish data ...
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learni...
Copy the generated Client Id and Client Secret. Use these values later in the "Steps Performed in Mindtickle" section (below). Steps Performed in Mindtickle To complete the content sync with LinkedIn Learning, enter the LinkedIn Learning data into the Mindtickle configuration. On the Mindtickle Con...