Travelled to:1 × Canada
1 × Japan
1 × Slovenia
2 × Italy
4 × USA
Collaborated with:D.Margaritis D.Fox ∅ J.O'Sullivan T.M.Mitchell W.Burgard S.Park F.Pfenning M.Rosencrantz G.J.Gordon C.Faloutsos J.Langford Y.Liu R.Emery D.Chakrabarti H.Jans C.Matenar
Talks about:learn (6) robot (3) model (3) base (3) environ (2) mobil (2) use (2) probabilist (1) comparison (1) represent (1)
Person: Sebastian Thrun
DBLP: Thrun:Sebastian
Contributed to:
2006
2005
20042001
20011999199819961993Wrote 10 papers:
- ASE-2006-Thrun #challenge
- Winning the DARPA Grand Challenge: A Robot Race through the Mojave Desert (ST), p. 11.
- POPL-2005-ParkPT #probability
- A probabilistic language based upon sampling functions (SP, FP, ST), pp. 171–182.
- ICML-2004-RosencrantzGT #learning #predict
- Learning low dimensional predictive representations (MR, GJG, ST).
- ICML-2001-LiuECBT #3d #mobile #modelling #using
- Using EM to Learn 3D Models of Indoor Environments with Mobile Robots (YL, RE, DC, WB, ST), pp. 329–336.
- VLDB-2001-MargaritisFT #data mining #mining #named #performance #scalability
- NetCube: A Scalable Tool for Fast Data Mining and Compression (DM, CF, ST), pp. 311–320.
- ICML-1999-BurgardFJMT #mobile #scalability #using
- Sonar-Based Mapping of Large-Scale Mobile Robot Environments using EM (WB, DF, HJ, CM, ST), pp. 67–76.
- ICML-1999-ThrunLF #learning #markov #modelling #monte carlo #parametricity #probability #process
- Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes (ST, JL, DF), pp. 415–424.
- ICML-1998-MargaritisT #3d #image #learning #sequence
- Learning to Locate an Object in 3D Space from a Sequence of Camera Images (DM, ST), pp. 332–340.
- ICML-1996-ThrunO #algorithm #learning #multi
- Discovering Structure in Multiple Learning Tasks: The TC Algorithm (ST, JO), pp. 489–497.
- ICML-1993-MitchellT #comparison #learning #network
- Explanation Based Learning: A Comparison of Symbolic and Neural Network Approaches (TMM, ST), pp. 197–204.