We show in this work that non-local correlations of dihedral potentials play a decisive role in the description of the total molecular energy—an effect which is neglected in most state-of-the-art dihedral force
Machine learning holds multidimensional capacity and witnesses its applications in varied fields such as speech recognition, online fraud detection, image recognition, product recognition, etc. [17]. Sensor machine learning is a comparatively new application of machine learning that uses various machine le...
If you have preexisting features in your dataframe (regardless if you use TuneTA to create new ones), I've added a helper prune_df function to prune the all of the features based on intercorrelation. This is helpful, for example, if you have custom features that you would like to combi...
We take inspiration from the recently introduced k-support norm, which has been successfully applied to sparse prediction problems with correlated features, but lacks any explicit structural constraints commonly found in machine learning and image processing. We address this problem by incorporating a ...
In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE Chaudhuri K, Kakade SM, Livescu K, Sridharan K (2009) Multi-view Clustering via Canonical Correlation Analysis. In: Proceedings of the 26th Annual International Conference on Machine Learning, pp. ...
Here we report flexible three-dimensional artificial chemical synapse networks, in which two-terminal memristive devices, namely, electronic synapses (e-synapses), are connected by vertically stacking crossbar electrodes. The e-synapses resemble the key features of biological synapses: unilateral ...
The machine-translated outputs of the existing translation systems of these languages go through manual post-editing to build the datasets. In addition to text, we build MT systems by exploiting features from images and audio recordings in the source language, i.e., Manipuri. We carried out ...
As a player, you had to use the features of the terrain, and a small number of tools, to safely guide the group to the exit. Although most distributed systems run software that is significantly more sophisticated than the AI in control of a lemming, they can still suffer a similar fate...
PearSAN is a machine learning-assisted optimization algorithm applicable to inverse design problems with large design spaces, where traditional optimizers struggle. The algorithm leverages the latent space of a generative model for rapid sampling and employs a Pearson correlated surrogate model to predict...
For example, machine learning algorithms may be tailored in attempts to realize an efficient use of server resources for predictive maintenance for the associated servers. Accordingly, machine learning may be used to improve the useful life of server infrastructure by reducing inefficient use of ...