Computer science Sampling-based query execution time prediction and query re-optimization THE UNIVERSITY OF WISCONSIN - MADISON Jeffrey F. Naughton WuWentaoThe problem of query execution time prediction and query optimization is fundamental in database systems. Although decades of research has been ...
The problem of query execution time prediction and query optimization is fundamental in database systems. Although decades of research has been devoted to this area and significant progress has been made, it remains a challenging problem for many queries in real-world database workloads. 关键词: ...
reinforcement-learningmodel-predictive-controlmodel-based-rlderivative-free-optimizationsampling-based-planning UpdatedOct 20, 2020 Python yiyunevin/RL-RRT-Local-Planner Star49 A ROS package of a autonomous navigation method based on SAC and Bidirectional RRT* (Repository RL-RRT-Global-Planner). ...
On the other hand, when the current solution is locally optimal, any efforts on the local optimization would be useless. For example, in Fig. 1b, the optimal solution passes through the narrow passage between the two obstacles; thus, sampling the neighborhood of the current solution would lead...
Choosing the points that would minimize the objective for the case of equal risks corresponds to selection of query points that would minimize the classification error; hence, the points at the decision boundary are the one that are the most informative. FIG. 15 illustrate the case when it is...
The local-based correlation measure hl(·) is defined as hl(pi, pij ) = Q(pi)⊤K(pij − pi) (1) where Q and K stand for the linear layers applied on the query input and the key input, respectively. Here we use the (latent) features of the center point pi as the query ...
RDF query path optimization using hybrid genetic algorithms: Semantic web vs. data-intensive cloud computing Int. J. Cloud Appl. Comput., 12 (1) (2022), pp. 1-16 CrossrefGoogle Scholar 14. X. Wang Genetic RRT: Asymptotically optimal sampling-based path planning via optimization of genetic ...
RRT*-Smart aims to produce straighter paths through its optimization process. However, as shown in Figure 8c, the algorithm may struggle to make significant corrections when the environment imposes complex path adjustments, potentially leading to less efficient paths. In contrast, TA-RRT* effectively...
Subsequently, these transformed vectors are partitioned into multiple “heads”, each possessing its own independent matrices for Query, Key, and Value. For each head, a self-attention operation is executed, as delineated in the relevant equations. Ultimately, the outputs from all heads are ...
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