We present ReLATE, a deep reinforcement learning framework for automatically constructing an efficient sparse tensor format
We ask whether AI is capable of handling the complexity of sparse computation on their own. Unfortunately (or fortnuately?) As of today, the answer is an astounding no. However, we can still leverage AI to augment human expertise.
We demonstrate the efficiency and performance-portability of encoding sparse tensors in a linearized format
We discuss using high-performance tensor decomposition for topic modeling and malware detection
We discuss our experience in optimizing the CP and Tucker decomposition algorithms for sparse datasets on a distributed system.
We discuss our experience in optimizing the CP and Tucker decomposition algorithms for sparse datasets on a distributed system.
We share our experience in using tensor decomposition for detecting malware
We discuss our experience in optimizing the non-negative Tucker decomposition for sparse datasets on a distributed system.