The process of moving the hand to a target in space involves a series of sensorimotor
transformations that translate visual and other sensory information about the location of the …

Efficient algorithms that incorporate different types of spectral data and ancillary data are
being developed to extract continuous vegetation variables. Inferring continuous variables …

Reinforcement learning (RL) can automate a wide variety of robotic skills, but learning each
new skill requires considerable real-world data collection and manual representation …

Series Introduction Example Computer Languages Prerequisite Knowledge Fundamental
Algorithms Other Resources Structure of this Book This book is the third in a series covering …

The deterministic annealing approach to clustering and its extensions has demonstrated
substantial performance improvement over standard supervised and unsupervised learning …

Neurofuzzy adaptive modelling and control | Guide books skip to main content ACM Digital
Library home ACM home Google, Inc. (search) Advanced Search Browse About Sign in …

Dataclusteringisacommontechniqueforstatis…, whichisusedin many? elds, including
machine learning, data mining, pattern recognition, image analysis and bioinformatics …

Learning discriminative task-specific features simultaneously for multiple distinct tasks is a
fundamental problem in multi-task learning. Recent state-of-the-art models consider directly …

In this paper, the classic 'divide and conquer (DAC)'paradigm is applied as a top-down black-
box technique for the forecasting of daily streamflows from the streamflow records alone, ie …

Transfer of pre-trained representations can improve sample efficiency and reduce
computational requirements for new tasks. However, representations used for transfer are …