Abstract

arXiv:0706.3639v1 [cs.AI] 25 Jun 2007

arXiv:0706.3639v1 [cs.AI] 25 Jun 2007 Technical Report IDSIA-07-07 A Collection of Definitions of Intelligence Shane Legg IDSIA, Galleria …

  Intelligence, Collection

Deep Residual Learning for Image Recognition - …

Deep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research fkahe, v-xiangz, v-shren, jiansung@microsoft.com

  Image, Learning, Residual, Recognition, Residual learning for image recognition

arXiv:1301.3781v3 [cs.CL] 7 Sep 2013

For all the following models, the training complexity is proportional to O = E T Q; (1) where E is number of the training epochs, T is the number of …

@google.com arXiv:1609.03499v2 [cs.SD] 19 Sep 2016

where 1 <x t <1 and = 255. This non-linear quantization produces a significantly better reconstruction than a simple linear quantization scheme. …

A Tutorial on UAVs for Wireless Networks: …

A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems Mohammad Mozaffari 1, ... to UAVs in wireless communications is the work in …

  Network, Communication, Wireless, Wireless communications, Wireless networks

Adversarial Generative Nets: Neural Network …

Adversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer Carnegie Mellon University

  Network, Attacks, Nets, Adversarial generative nets, Adversarial, Generative, Neural network, Neural, Neural network attacks

Massive Exploration of Neural Machine Translation ...

Massive Exploration of Neural Machine Translation Architectures Denny Britzy, Anna Goldie, Minh-Thang Luong, Quoc Le fdennybritz,agoldie,thangluong,qvlg@google.com Google Brain

  Architecture, Machine, Exploration, Translation, Neural, Exploration of neural machine translation, Exploration of neural machine translation architectures

Mastering Chess and Shogi by Self-Play with a …

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm David Silver, 1Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, 1Matthew Lai, Arthur Guez, Marc Lanctot,1

Going deeper with convolutions - arXiv

Going deeper with convolutions Christian Szegedy Google Inc. Wei Liu University of North Carolina, Chapel Hill Yangqing Jia Google Inc. Pierre Sermanet

  With, Going, Going deeper with convolutions, Deeper, Convolutions

Andrew G. Howard Menglong Zhu Bo Chen Dmitry ...

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand Marco Andreetto Hartwig Adam

  Applications

New business model in smart cities: Emerging …

New business model in smart cities: Emerging trends and methods of analysis Paolo Neirotti ‐Politecnico di Torino Department of Management and Production Engineering

  Model, Methods, Trends, Smart, Emerging, Cities, Smart cities, Emerging trends and methods

Allocating Marketing Resources - Harvard …

2 Allocating Marketing Resources Abstract Marketing is essential for the organic growth of a company. Not surprisingly, firms spend billions of dollars on marketing.

  Marketing, Resource, Harvard, Allocating, Allocating marketing resources

How to Build Better Scale Model Vehicles

How to Build Better Scale Model Vehicles Construction Considerations for Building Championship-Caliber Models Mark S. Gustavson Robert A. Wick Championship Publishing, L.L.C.

  Model, Scale, Vehicle, Better, Build, To build better scale model vehicles

Batteries for Electric Cars - Global Management …

Batteries for Electric Cars 1 Batteries for Electric Cars Challenges, Opportunities, and the Outlook to 2020 W hat impact will the development and cost of vari-

  Electric, Cars, Batteries, Batteries for electric cars

Initiatives for Sustainable Growth - toyota-global.com

sg sg01 Customer First and Quality First Business Unit Various initiatives in Toyota Advanced R&D and Engineering Company Four vehicle-based companies Toyota No.1

Fast-Forwarding to a Future of On-Demand Urban …

1 Introduction Imagine traveling from San Francisco’s Marina to work in downtown San Jose—a drive that would normally occupy the better part of …

  Better