Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic
  Guarantees   The rising volume of datasets has made training machine learning (ML) models
a major computational cost in the enterprise. Given the iterative nature of
model and parameter tuning, many analysts use a small sample of their entire
data during their initial stage of analysis to make quick decisions (e.g., what
features or hyperparameters to use) and use the entire dataset only in later
stages (i.e., when they have converged to a specific model). This sampling,
however, is performed in an ad-hoc fashion. Most practitioners cannot precisely
capture the effect of sampling on the quality of their model, and eventually on
their decision-making process during the tuning phase. Moreover, without
systematic support for sampling operators, many optimizations and reuse
opportunities are lost.
  In this paper, we introduce BlinkML, a system for fast, quality-guaranteed ML
training. BlinkML allows users to make error-computation tradeoffs: instead of
training a model on their full data (i.e., full model), BlinkML can quickly
train an approximate model with quality guarantees using a sample. The quality
guarantees ensure that, with high probability, the approximate model makes the
same predictions as the full model. BlinkML currently supports any ML model
that relies on maximum likelihood estimation (MLE), which includes Generalized
Linear Models (e.g., linear regression, logistic regression, max entropy
classifier, Poisson regression) as well as PPCA (Probabilistic Principal
Component Analysis). Our experiments show that BlinkML can speed up the
training of large-scale ML tasks by 6.26x-629x while guaranteeing the same
predictions, with 95% probability, as the full model.

31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con