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Learning Distributedand Fair Policiesfor Network Load Balancingas Markov Potential Game
At t 2 H inahorizonH ofthegireceiwi(t) 2 W, theworkload policy i 2 , where istheload t, a anactionai(t)= {aij(t)}Nj=1, accordingwi(t) are i(t). Q (o, a) r(o, a) Eo0[V (o0)] 2 , whereV (o0)= Ea0[Q (o0,a0) log (a0|o0)] and Q isthetargetQ network; theactorpolicy isupdatedwiththegradient r Eo[Ea [ log (a|o) Q (o, a)]].
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Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio
The system consumes, as input, audio signals from headset microphones and body pose, and produces, as output, a 3D sound field surrounding the transmitter's
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Episodic Memory in Lifelong Language Learning
Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, Dani Yogatama
Neural Information Processing Systems http://nips.cc/
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Compositional generalization through meta sequence-to-sequence learning
Neural Information Processing Systems http://nips.cc/
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