Using this new form, it is possible to change the constrained dynamic optimization problem into an unconstrained dynamic optimization problem. The fundamentals of calculus of variations are then applied to this new cost functional and the necessary conditions for optimality are obtained. These necessary...
an efficient algorithm for structural optimum design has been developed. The main advantages of this method are the generality in use, the efficiency in computation and the capability in identifying automatically the set of active constraints. On the basis of the virtual...
system of automated planning of production and shop order management in ferrous The main scientific interests of V. S. Mikhalevich were connected with investigations in optimization theory and system analysis and with the development of newest computer technologies and computer complexes, creation of ...
2016.07-IHT-Training skinny deep neural networks with iterative hard thresholding methods 2016.08-Recurrent Neural Networks With Limited Numerical Precision 2016.10-Deep model compression: Distilling knowledge from noisy teachers 2016.10-Federated Optimization: Distributed Machine Learning for On-Device Intelligence...
The response surface approach to global optimization has three major advan- tages. First, the technique often requires the fewest function evaluations of all competing methods. This is possible because, with typical engineering functions, one can often interpolate and extrapolate quite accurately over la...
Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates - ili3p/HORD
A traveling salesman problem (TSP) is an NP-hard optimization problem. So it is necessary to use intelligent and heuristic methods to solve such a hard pro... A Haeri,R Tavakkoli-Moghaddam - 《Journal of Business Economics & Management》 被引量: 13发表: 2012年 An integrated approach to ...
These operators are intended to be extremely generic in their application, just as the concept of dynamic memory is. As a result, they are unable to take advantage of the various optimization techniques and opportunities that specific use cases present. Each source code file is modeled after its...
I-SHEEP: Self-Alignment of LLM from Scratch through an Iterative Self-Enhancement Paradigm. 2024. [arxiv] Bai et al. Aligning Large Language Model with Direct Multi-Preference Optimization for Recommendation. CIKM 2024. [paper] StarWhisper: A large language model for Astronomy, based on ChatGLM...
Pan et al. conducted a series of studies and proposed a discrete particle swarm optimization (DPSO) algorithm [29], a hybrid discrete particle swarm optimization (HDPSO) algorithm [30] and an improved iterated greedy (IIG) algorithm [31]. Their computational results showed that these meta-...