Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System
Summary: Columbus provides a unified feature-selection operations library inside Oracle R Enterprise for enterprise analytics. Supports diverse users, enables high-performance analytics on large data, and tracks end-to-end provenance for auditability. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pradap Konda
- 2. Arun Kumar
- 3. Christopher Ré
- 4. Vaishnavi Sashikanth
Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 901 | To Join or Not to Join? Thinking Twice about Joins before Feature Selection | 2016 | SIGMOD | 0.00015462938 |
| 1,172 | Learning Generalized Linear Models Over Normalized Data | 2015 | SIGMOD | 0.00013504249 |
| 2,158 | DIFF: A Relational Interface for Large-Scale Data Explanation | 2019 | VLDB | 9.4117885e-05 |
| 2,892 | VISTA: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale | 2020 | SIGMOD | 7.9570135e-05 |
| 4,123 | Are Key-Foreign Key Joins Safe to Avoid when Learning High-Capacity Classifiers? | 2018 | VLDB | 6.4290005e-05 |
| 4,794 | Demonstration of Santoku: Optimizing Machine Learning over Normalized Data | 2015 | VLDB | 5.910645e-05 |
| 7,605 | Causal Feature Selection for Algorithmic Fairness | 2022 | SIGMOD | 4.6943015e-05 |
| 8,864 | Cerebro: A Layered Data Platform for Scalable Deep Learning | 2021 | CIDR | 4.4283952e-05 |
| 13,461 | Ringtail: A Generalized Nowcasting System | 2013 | VLDB | - |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 13,461 | Ringtail: A Generalized Nowcasting System | 2013 | VLDB | - |
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| 638 | Towards a Unified Architecture for in-RDBMS Analytics | 2012 | SIGMOD | 0.00018810785 |
| 758 | Materialization Optimizations for Feature Selection Workloads | 2014 | SIGMOD | 0.00017053915 |