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Found 4 papers, 0 papers with code
ProjB: An Improved Bilinear Biased ProjE model for Knowledge Graph Completion
Experimental results on benchmark Knowledge Graphs (KGs) such as FB15K and WN18 show that the proposed approach outperforms the state-of-the-art models in entity prediction task using linear and bilinear methods and other recent powerful ones.
Uncertainty Principle based optimization; new metaheuristics framework
In the branch of quantum mechanics, canonically conjugate observables such as position and momentum cannot both be distinctly determined in any quantum state.
Modified swarm-based metaheuristics enhance Gradient Descent initialization performance: Application for EEG spatial filtering
Gradient Descent (GD) approximators often fail in the solution space with multiple scales of convexities, i. e., in subspace learning and neural network scenarios.
A New Approach for Optimizing Highly Nonlinear Problems Based on the Observer Effect Concept
A lot of real-world engineering problems represent dynamicity with nests of nonlinearities due to highly complex network of exponential functions or large number of differential equations interacting together.
