We revisit the search space design in most previous NAS methods and find the number and widths of blocks are set manually.
Ranked #113 on Image Classification on ImageNet
In other words, our operators form the building blocks of a new deep motion processing framework that embeds the motion into a common latent space, shared by a collection of homeomorphic skeletons.
A LadderNet has more paths for information flow because of skip connections and residual blocks, and can be viewed as an ensemble of Fully Convolutional Networks (FCN).
Ranked #3 on Retinal Vessel Segmentation on CHASE_DB1
Currently, researchers have paid great attention to retrieval-based dialogues in open-domain.
The last decade has witnessed a boom of neural network (NN) research and applications achieving state-of-the-art results in various domains.
We present a new model-based integrative method for clustering objects given both vectorial data, which describes the feature of each object, and network data, which indicates the similarity of connected objects.
In this paper, we propose a framework that imposes on blocks of variables a chain structure obtained by step-wise greedy search so that the DNN architecture can leverage the constructed grid.