Travelled to:
1 × Canada
1 × France
1 × USA
Collaborated with:
J.Schmidhuber ∅ S.Zhang Y.LeCun D.Horgan K.Gregor D.Silver Y.Sun D.Wierstra Diego Perez Liebana Spyridon Samothrakis Julian Togelius S.M.Lucas
Talks about:
game (3) video (2) learn (2) architectur (1) stochast (1) interact (1) gradient (1) function (1) descript (1) approxim (1)
Person: Tom Schaul
DBLP: Schaul:Tom
Contributed to:
Wrote 6 papers:
- ICML-2015-SchaulHGS #approximate
- Universal Value Function Approximators (TS, DH, KG, DS), pp. 1312–1320.
- ICML-c3-2013-SchaulZL #learning
- No more pesky learning rates (TS, SZ, YL), pp. 343–351.
- ICML-2009-YiWSS #probability #using
- Stochastic search using the natural gradient (YS, DW, TS, JS), pp. 1161–1168.
- CIG-2008-SchaulS #architecture #game studies #network #scalability
- A scalable neural network architecture for board games (TS, JS), pp. 357–364.
- CIG-2013-Schaul #game studies #interactive #learning #modelling #video
- A video game description language for model-based or interactive learning (TS), pp. 1–8.
- CIG-2016-LiebanaSTSL #game studies #robust #video
- Analyzing the robustness of general video game playing agents (DPL, SS, JT, TS, SML), pp. 1–8.