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R-learninginactor-criticmodeloffersabiologically relevantmechanismforsequentialdecision-making

Neural Information Processing Systems

Afewstudies haveexplored sequential stay-or-leavedecisions in humans, or rodents - the model organism used to access neuronal activity at high resolution. In both cases, decision patterns were collected inforaging tasks-the experimental settings where subjects decide when to leave depleting resources (2).


Penguin: P arallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference

Neural Information Processing Systems

HE operations (e.g., ciphertext (ct) rotations/multiplications, additions), which could be orders of For example, a GCN layer's computation is dominated by the special consecutive HE operations are defined in Sec. 2. For generality, we assume both feature matrix and adjacency Parallel-Packing (see Sec. 3.2), the ciphertext size is fully exploited, and the total HE operation count We adopt a threat model setting consistent with prior works [9, 14, 3, 7, 18, 22, 27]. The cloud server is semi-honest (e.g.







Catch-A-Waveform: LearningtoGenerateAudio fromaSingleShortExample

Neural Information Processing Systems

Oncetrained,ourmodelcangeneraterandom samples of arbitrary duration that maintain semantic similarity to the training waveform, yet exhibit new compositions of its audio primitives.