3 accepted papers
In this paper, we present a new question-answering (QA) based key-value pair extraction approach, called KVPFormer, to robustly extracting key-value relationships between entities from form-like document images. Specifically, KVPFormer first identifies key entities from all entities in an image with…
Recently Adam has become a popular stochastic optimization method in deep learning area. To parallelize Adam in a distributed system, synchronous stochastic gradient (SSG) technique is widely used, which is inefficient due to heavy communication cost. In this paper, we attempt to parallelize Adam wi…
We present a new approach to scalable training of deep learning machines by incremental block training with intra-block parallel optimization to leverage data parallelism and blockwise model-update filtering to stabilize learning process. By using an implementation on a distributed GPU cluster with…