… and control algorithm based on ANNs and reinforcement learning. … control algorithms with
one of three retraining techniques, which … The IT server heat ( I T L o a d ( n ) ), CRAH return air …

… the machine-learning algorithm extract the most information possible. The novelty of our
constantly retraining approach … The whole process is run daily around 10 AM on KNIME Server, …

… of Machine Learning. From a high-level point of view, the … technique to reduce approximation
errors in retraining. • We … In our setting, the server S controls the whole training process by …

… for continuous learning and regular retraining. The proposed system keeps the … machine
learning algorithm used for the LF and the process of implementation to the hybrid cloud server: …

… the local machine to the remote server and from the remote server to the local … the server
these data is used to generate per-application traffic statistics. C5.0 Machine Learning Algorithm …

… of data points on machine learning methods relying on K-… the clients to the server in different
training rounds and aggregate … In lines 911, instead of retraining models on all the nonempty …

… techniques suffer from inefficiency due to two sequential operations of training and retraining…
It is impossible to utilize the PCMU method to train a CMU model on the server. On the other …

… that cannot send the data to the server, we need to push the … only works for traditional
machine learning methods that can be … of the FL process, we may need to retrain the model from …

… Learning is a distributed machine learning technique, this study implements four clients and
a server … Here local data refers to the data we have chosen for retraining and validation. But …

… suggested approach and the weight derived from retraining … machine learning models, one
naıve solution is to retrain the … on the server compare to the FedAvg, the proposed method …