Dealing with missing data: Part II

By Beata Walczak, D. Massart. 2001

209 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/21587354b50a1c92b921bbff9652af85da217aa7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Aditya G. Parameswaran
2. Petr Kadlec
3. Sibylle Strandt
4. Hector Garcia-Molina
5. Bogdan Gabrys
6. Manas R. Joglekar
7. Christopher R'e
8. Alexander J. Ratner

In Environmental Engineering

1. Bogdan Gabrys
2. Sibylle Strandt
3. Petr Kadlec

In Statistics and Probability

1. Hector Garcia-Molina
2. Aditya G. Parameswaran
3. Bogdan Gabrys
4. Manas R. Joglekar
5. Sibylle Strandt
6. Petr Kadlec

Citations in the corpus

• Comprehensive and reliable crowd assessment algorithms (2014, background): “B) We present experimental results on synthetic data (Section IV-B) and 3 real datasets (Section IV-C) to study the performance of our confidence intervals on k-ary tasks.”
• Data-driven Soft Sensors in the process industry (2009, methodology): “…takes into account the multivariate statistics of the data and thus makes the reconstruction of the missing values dependent on the other available variables of the affected samples (see e.g. Walczak and Massart (2001b) for maximum-likelihood multivariate approach to missing values replacement).”