Sentence examples for estimation learning from inspiring English sources

The structural optimization is realized via genetic algorithms (GAs) and HCM method whereas in case of the parametric optimization we proceed with a standard least square estimation (learning).

For tracking a moving target, we mathematically model the task as searching a location sequence with the most likelihood, in which we first augment the probabilistic estimation learned in localization to construct the Emission Matrix and propose two human mobility models to approximate the Transmission Matrix in the Hidden Markov Model.

The proposed SpCoA++ method performs an iterative estimation of learning spatial concepts and updating a language model using place information.

The decentralized consensus optimization formulation (1) arises in many practical applications, such as averaging [9 11], estimation [12 17], learning [18 21], etc.

Fig. 1 Schematic diagram of a, c the conventional paradigm for facial age estimation by learning the age information from a facial image directly, and b,d the proposed paradigm by aggregating the comparisons of a facial image with baseline samples to determine the age in a comparative manner.

During these estimation and learning processes, the PPI interaction mathematical model can derive the most probable PPI network for cancer and normal patients from large amount of microarray data and big databases to interpret the hidden biological mechanisms.

To explain these results, we propose dual underlying mechanisms of reward-driven perceptual learning: one mechanism that operates 'automatically', free from goal-directed processes, and another mechanism that involves more 'top-down', goal-directed computations, and requires conscious estimation of learning contingencies.

In this regard, the proposed LLNFM-based methodology reached better results for running-times, as well as root mean square error (RMSE) estimations in learning and testing processes of training/checking data-set in comparison with those of the proposed adaptive neuro-fuzzy inference system (ANFIS) based methodology.

The estimations after learning were obtained as q = v + | μ | N and P = | μ | N q.

Many estimation, prediction, and learning applications have a dynamic nature.

Sugano et al. [1] take the cropped eye region as a point in a local manifold model and make gaze estimation by clustering learning samples with similar head poses and constructing their local manifold model.