Hampshire
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
U, which achieves an unbiased stochastic approximation of the meta gradient for bi-level optimization.
Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantization
Weight-sharing quantization has emerged as a technique to reduce energy expenditure during inference in large neural networks by constraining their weights to a limited set of values.
Manipulating a Learning Defender and Ways to Counteract
Jiarui Gan, Qingyu Guo, Long Tran-Thanh, Bo An, Michael Wooldridge
Neural Information Processing Systems http://nips.cc/
Bridging Machine Learning and Logical Reasoning by Abductive Learning
Wang-Zhou Dai, Qiuling Xu, Yang Yu, Zhi-Hua Zhou
Perception and reasoning are two representative abilities of intelligence that are integrated seamlessly during human problem-solving processes.
DeepSetPredictionNetworks
Concretely,wecontributethefollowing: 1. Wepropose amodel (section 3, Algorithm 1) that can predict aset from afeature vector (vector-to-set) while properly taking the structure of sets into account.