[ Balog | Bratières | Chen | Cunningham | Davies | Duvenaud | Eaton | Frellsen | Frigola | Van Gael | Gal | Ghahramani | Heaukulani | Heller | Hernández-Lobato | Hoffman | Houlsby | Huszár | Knowles | Lacoste-Julien | Li | Lloyd | Lopez-Paz | Matthews | Mc Hutchon | Mohamed | Navarro | Orbanz | Ortega | Palla | Quadrianto | Rasmussen | Rojas-Carulla | Roy | Saatçi | Ścibior | Shah | Steinrücken | Tobar | Rich Turner | Ryan Turner | Snelson | Weller | van der Wilk | Williamson | Wilson ] , November 2016.Abstract: We develop a first line of attack for solving programming competition-style problems from input-output examples using deep learning.To provide the finest leadership, quality, service and accountability in electrical contracting that our customers deserve and expect.
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Empirically, we show that our approach leads to an order of magnitude speedup over the strong non-augmented baselines and a Recurrent Neural Network approach, and that we are able to solve problems of difficulty comparable to the simplest problems on programming competition websites. In , pages 32-41, Jersey City, New Jersey, USA, June 2016.