https://cis.temple.edu/~giorgio/cis587/readings/rete.html
(R1 (has-goal ?x simplify) (expression ?x 0 + ?y) ==>....) (R2 (has-goal ?x simplify) (expression ?x 0 * ?y) ==>....) and the following facts: (has-goal e1 simplicity) (expression e1 0 + 3) (has-goal e2 simplicity) (expression e2 0 + 5) (has-goal e3 simplicity) (expression e3 0 * 2) Then the Rete is +----------+ | ENTRANCE | +----------+ x ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Reinforcement_Learning-based_Dual-Identity_Double_Auction_in_Personalized_Federated_Learning.pdf
Similarly, G2 is divided into multiple b trees G2,j. A tree G2,j = {V 2,j, {j}, E2,j} has a single seller j as the root and multiple buyers as leaves. We add a virtual buyer 0 to each tree. Its bid price b0j is amax b th . Set V 2,j includes the buyers connected to j in G2 and buyer 0. Let q = argmini∈V
https://cis.temple.edu/~jiewu/research/publications/Publication_files/FedCPD.pdf
0 2 2 2 L1 + E 0G2 + E2 0G2 2 + 2 L2E2 0G2 2 + 2 Theorem 2. (Non-convex FedCPD convergence). 0 < e < 0, e 2 f1 1; 2; : : : ; Eg, where represents the de- 2; cay factor for the learning rate. If the learning rate for each epoch satisfies the following condition, the loss function de-creases monotonically, leading to convergence:
https://ronlevygroup.cst.temple.edu/courses/2020_fall/chem5302/lectures/chem5302_lecture2.pdf
Canonical Ensemble: An ensemble with the same Number of molecules, Volume and Temperature, but different Energy per system. (N, V, T)
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https://community.mis.temple.edu/mis5121beaver/files/2015/02/Ex-2-Order-to-Cash-Guide.pdf
Focus Order-to-Cash Cycle and Accounting Entries Test of Transactions Application Controls
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London: J. Murray; 1859. Vaughan TG. IcyTree: rapid browser-based visualization for phylogenetic trees and networks. Bioinformatics. 2017;33:btx155. Kreft Ł, Botzki A, Coppens F, Vandepoele K, Van Bel M. PhyD3: a phylogenetic tree viewer with extended phyloXML support for functional genomics data visualization. Bioinformatics. 2017;33(18):2946 ...
https://sites.temple.edu/pdames/files/2016/07/DamesTokekarKumarISRR2015.pdf
Let Xt = fx1;t;x2;t;:::;xnt;tg denote a realization of a RFS of target states at time t. A probability distribution of a RFS is characterized by a discrete distribution over the cardinality of the set and a family of densities for the elements of the set conditioned on the size, i.e.,
https://cis.temple.edu/~jiewu/research/publications/Publication_files/ICDE2024_Online_Federated_Learning_on_Distributed_Unknown_Data_Using_UAVs.pdf
For the energy consumption during the learning phase, we set e1 = 0.01J and e2 = 80J [18]. To better align with real-world data collection scenarios, we design fine-grained PoI data models from three perspectives: data distribution, data generation patterns, and data quality.