[PDF] Top 20 Maximum Principle Based Algorithms for Deep Learning

... to deep learning is explored in order to devise alternative frameworks for training ...Pontryagin’s maximum principle ...with deep learning, such as trapping in slow manifolds ... See full document

... three algorithms- KNN, Rule model and Deep Learning are applied and their performances are ..., Deep Learning has highest accuracy of 76.03% +/-10.72%. Rule based classifier ... See full document

... both deep learning and fuzzy logic algorithms, and it keeps the po- tential operational implementation reasonably ...system based on deep learning in this paper, applies ... See full document

... probabilistic based machine learning ...Scout based on PC machine in 1996, which pushed NBA games’ data into data mining and knowledge discovery technology field and enabled coaches to find some ... See full document

... The problem of synthesizing the control of the intellectual suspension of a vehicle is regarded as a problem of synthesizing optimal law of parametric control. There currently exists a quite extensive experience in ... See full document

... However deep learning algorithms usually require an extremely large training dataset, which is not always available we propose a novel neural-network based algorithm, which we refer to as ... See full document

... As mentioned above, fine-grained image classification is a very challenging research topic. In order to achieve satisfactory classification results, many existing classification algorithms rely heavily on manual ... See full document

... making. Deep learning provides us an effective way to understand big data with a ...Q-learning based moving object recognition approach, which firstly finds out moving object region and then ... See full document

... built based on the idea of the adaptive neuro‑fuzzy inference sys‑ tem (ANFIS) and its capabilities in response simulation, data cleansing and restoration capability were verified using measurement data from ... See full document

... Exact and well-timed traffic flow information is important for the successfuldeployment of intelligent transportation systems. Over the last few years, traffic data have been report, and we have really entered the era of ... See full document

... EEP learning (DL) is considered one of the dynamic research areas comprehensively and effectively applied in different ...is based on algorithms for learning multiple levels of representation ... See full document

... Genetic Algorithms are ...are based on. Genetic Algorithms pos- tulate that the search space contains gradients between poor solutions and good ... See full document

... and maximum likelihood (ML) method, and compared the applicability of the three estimation methods by using observed flood ...distributions based on the MOM, ML, and PWM methods ...distribution based ... See full document

... The Agriculture sector in India is declining day by day which affects the production capacity of the ecosystem. There is an urgent need to solve the problem in the domain to restore vibrancy and put it back on higher ... See full document

... This is the peer reviewed version of the following article: Applebaum, D. and Le Ngan, T. (2019), The positive maximum principle on Lie groups. J. London Math. Soc., which has been published in final form ... See full document

... Riding on the Business process management principles, several new innovative technologies emerged in the automation industry. Robotic Process Automation is one such Next-gen software technology that enabled businesses to ... See full document

... tracted a large number of users to become content creators. An important aspect of this line of work is the feedback received in the form of comments which show how well the content is being received by the audience. ... See full document

... successful learning is motivating to pursue further research on the topic, being said that a CNN with a series of consecutive layers of convolutions is not even the most advanced type of deep ... See full document

... The principle of maximum entropy is often utilized in this context to fill in the missing pieces of available information and is normally claimed to be fair and ...of maximum entropy distributions ... See full document

... A Deep Neural Network consists of an input layer, severalhidden layers, and an output layer. Each layer includes severalunits called neurons. These neurons are also called as artificial neurons. A neuron receives ... See full document