Large-scale machine learning (ML) algorithms are often iterative, using repeated read-only
data access and I/O-bound matrix-vector multiplications to converge to an optimal model. It …

The envelope model was first introduced as a parsimonious version of multivariate linear
regression. It uses dimension reduction techniques to remove immaterial variation in the …

We give a commentary on the challenges of big data for Statistics. We then narrow our
discussion to one of those challenges: dimension reduction. This leads to consideration of …

Re-Pair [5] is an effective grammar-based compression scheme achieving strong
compression rates in practice. Let n, σ, and d be the text length, alphabet size, and dictionary …

Large-scale machine learning algorithms are often iterative, using repeated read-only data
access and I/O-bound matrix-vector multiplications to converge to an optimal model. It is …

Compression is an effective technique for fitting data in available memory, reducing I/O, and
increasing instruction parallelism. While data systems primarily rely on lossless …

A grammar compression is a context-free grammar (CFG) deriving a single string
deterministically. For an input string of length N over an alphabet of size sigma, the smallest …

Impossibility Results for Grammar-Compressed Linear Algebra Page 1 Impossibility Results
for Grammar-Compressed Linear Algebra Amir Abboud IBM Almaden Research Center amir.abboud@gmail.com …

应用驱动创新, 数据库技术就是在支持主流应用的提质降本增效中发展起来的. 从OLTP, OLAP
到今天的在线机器学习建模无不如此. 机器学习是当前人工智能技术落地的主要途径 …

Bitvectors that support rank and select queries are the workhorses of succinct data
structures, implementations of which are now widespread, for example, in bioinformatics …