--- abstract: 'We present a method for accurate representation of high-dimensional unknown functions from random samples drawn from its input space. The method builds representations of the function by recursively splitting the input space in smaller subspaces, while in each of these subspaces a linear approximation is computed. The representations of the function at all levels (i.e., depths in the tree) are retained during the learning process, such that a good generalisation is available as well as more accurate representations in some subareas. Therefore, fast and accurate learning are combined in this method. The method, which is applied to hand-eye coordination of a robot arm, is shown to be superior to other neural networks.' altloc: - http://www.robotic.dlr.de/Smagt/SmaGroGro94b.ps.gz chapter: ~ commentary: ~ commref: ~ confdates: 1994 conference: IEEE International Conference on Neural Networks confloc: Florida contact_email: ~ creators_id: [] creators_name: - family: Smagt given: P. van der honourific: '' lineage: '' - family: Groen given: F. honourific: '' lineage: '' - family: Groenewoud given: F. van het honourific: '' lineage: '' date: 1994 date_type: published datestamp: 1998-07-03 department: ~ dir: disk0/00/00/04/96 edit_lock_since: ~ edit_lock_until: ~ edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 496 fileinfo: /style/images/fileicons/application_postscript.png;/496/2/SmaGroGro94b.ps full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: 0 item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: 'neural networks, high-dimensional function approximation, learning, robot arm control' lastmod: 2011-03-11 08:54:00 latitude: ~ longitude: ~ metadata_visibility: show note: ~ number: ~ pagerange: 2787-2792 pubdom: FALSE publication: ~ publisher: IEEE refereed: FALSE referencetext: ~ relation_type: [] relation_uri: [] reportno: ~ rev_number: 10 series: ~ source: ~ status_changed: 2007-09-12 16:29:08 subjects: - comp-sci-neural-nets - comp-sci-robot succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: The locally linear nested network for robot manipulation type: confpaper userid: 462 volume: ~