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Found 3 papers, 1 papers with code
Clustering of Big Data with Mixed Features
The improvements are threefold: (1) the new algorithm is applicable to mixed data; (2) the algorithm is capable of detecting outliers and clusters of relatively lower density values; (3) the algorithm is competent at deciding the correct number of clusters.
Domain Randomization and Generative Models for Robotic Grasping
In this work, we explore a novel data generation pipeline for training a deep neural network to perform grasp planning that applies the idea of domain randomization to object synthesis.
Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model
Nevertheless, often the overall gist of what the policy does in simulation remains valid in the real world.
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