OAECD algorithm is also focused on the static environment and has poor robustness for dynamic environment. In the Gonzalez’s literature the performance of the conventional algorithm was improved by changing the
An improved integrality gap for asymmetric TSP paths - Friggstad, Gupta, et al. - 2013 () Citation Context ...nown to be at least 2 [CGK06] and at most O(log n/ log log n) [AGM+10]. For the asymmetric path version, the integrality gap is known to be 2 at least 2 [CGK06,...
Pandit N, Tripathi A, Tapaswi S, Pandit M (2012) An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch. Appl Soft Comput J 12(11):3500–3513.https://doi.org/10.1016/j.asoc.2012.06.011 ArticleGoogle Scholar Rajasomashekar S, Aravindhababu P (2012...
Let A be an algorithm that generates a feasible solution to every instance I of a problem P. Let F*(I) be the value of an optimal solution, and let F′(I) be the value of the solution generated by A. Definition. A is a k-absolute approximation algorithm for P iff |F*(I) −...
As a consequence of our improved algorithm, we solve within several minutes affine equivalence problem instances of size up toon a single core. Optimizing our implementation and exploiting parallelism would most likely allow solving instances of size at leastusing an academic budget. Such instances are...
the improved surrogate model yields a better accuracy. However, we can also observe that excessive layers will lead to overfitting of the model, resulting in suboptimal results. Similar results can be obtained in Fig.6b, which analyzes the performance for a varying number of neurons. It can be...
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Generating Instance-level Prompts for Rehearsal-free Continual Learning(ICCV 2023)[paper] Heterogeneous Continual Learning(CVPR 2023)[paper] Partial Hypernetworks for Continual Learning(CoLLAs 2023)[paper] Learnability and Algorithm for Continual Learning(ICML 2023)[paper] Parameter-Level Soft-Masking for...
We present a new label-setting algorithm for the Multiobjective Shortest Path (MOSP) problem that computes a minimum complete set of efficient paths for a given instance. The size of the priority queue used in the algorithm is bounded by the number of nodes in the input graph and extracted ...
SqueezeNodule-Net V2 was 1.5 times larger but also 1.5 times faster than our first version, while achieving improved classification results (0.7–2.1%). SqueezeNodule-Net V2 was compared to state-of-the-art CNNs, such as LeNet-5, DenseNet-121, ResNet-50 and VGG-11. As it was found,...