Fine Grained Tensor Network Methods

Ultra-Fine Grained Dual-Phase Steels

This paper provides an overview on obtaining low-carbon ultra-fine grained dual-phase steels through rapid intercritical annealing of cold-rolled sheet as improved materials for automotive applications. A laboratory processing route was designed that involves cold-rolling of a tempered martensite structure followed by a second tempering step to produce a fine grained aggregate of ferrite and ca...

Exposing Fine-Grained Parallelism in Algebraic Multigrid Methods

Algebraic multigrid methods for large, sparse linear systems are a necessity in many computational simulations, yet parallel algorithms for such solvers are generally decomposed into coarse-grained tasks suitable for distributed computers with traditional processing cores. However, accelerating multigrid on massively parallel throughput-oriented processors, such as the GPU, demands algorithms w...

Embedding Methods for Fine Grained Entity Type Classification

We propose a new approach to the task of fine grained entity type classifications based on label embeddings that allows for information sharing among related labels. Specifically, we learn an embedding for each label and each feature such that labels which frequently co-occur are close in the embedded space. We show that it outperforms state-of-the-art methods on two fine grained entity-classif...

Seuss: Decoupling responsibilities from static methods for fine-grained configurability

Unit testing is often made more difficult by the heavy use of classes as namespaces and the proliferation of static methods to encapsulate configuration code. We have analyzed the use of 120 static methods from 96 projects by categorizing them according to their responsibilities. We find that most static methods support a hodgepodge of mixed responsibilities, held together only by their common ...

General methods for fine-grained morphological and syntactic disambiguation