Deep Learning
A Algorithms Algorithm 1: MAP Propagation - Monte-Carlo Policy-Gradient Control 1 Input: differentiable policy function: ฯ
Random synaptic feedback weights support error backpropagation for deep learning.
MAP Propagation Algorithm: Faster Learning with a Team of Reinforcement Learning Agents
The high variance stems from the lack of structural credit assignment, i.e. a single scalar
9b8619251a19057cff70779273e95aa6-Paper.pdf
There are, actually, two parts to this question: 1) Can training of non-normalized models be stable?
Hard-Attention for Scalable Image Classification
We compare our model against hard-attention baselines on ImageNet, achieving higher accuracy with less resources (FLOPs, processing time and memory).
Group Contextual Encoding for 3D Point Clouds
Global context is crucial for 3D point cloud scene understanding tasks.
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning
In other words, the assumptions in these works imply that the state space is already well-explored.
