… learning algorithms and techniques that promote or better employ … They construct an MT
system over each corpus and then … parameterize all distributions q using common parameters A …

… We choose parameters of our model as … corpus using the SRI Language Modeling Toolkit
[43] with modified KN smoothing [18]. We used minimum error rate training [35] to optimize the …

… We propose a MTL model using the monolingual Transformer-… The distance between the
parameters of the model is … In order to optimize both approaches STLBETO and MTL in both …

… algorithms, such as quantum-inspired genetic algorithm (… context of feature selection and
parameter optimization for text … were tested on real datasets using classical hardware (quantum-…

… is connected to the system that is taught to optimize criteria (… that not only optimizes
hyper-parameters but also network … Convergence rates of neural networks using genetic …

… Monolingual NMT systems use neural network architectures to … We create a parallel
corpus using 164 matched titles from … The network parameters are optimized by minimizing a …

… And we optimize these two tasks simultaneously to ensure the … Thus, the recipe for using our
approach follows a two-stage … we apply grid search to get hyperparameters, eg lr, batch size…

… to solve them autonomously using algorithms. Some authors such … Algorithms and methods,
tuned by parameters obtained … k-means, and Fast evolutionary algorithm for clustering data …

… model combinations through evolutionary algorithms. There is … , the language using the
largest amount of CT corpus in our … Current open-source MT systems have limited abilities of low-…

… of these systems should not only shed light on how to optimise … such as neural networks and
evolutionary algorithms. An ABM … policies to changes in other parameters of the model, and …