| 9,712 |
CaJaDE: Explaining Query Results by Augmenting Provenance with Context
|
2022 |
VLDB |
5.285931e-05 |
| 9,730 |
Databases in the Era of Memory-Centric Computing
|
2025 |
CIDR |
5.2802775e-05 |
| 9,759 |
DPXPlain: Privately Explaining Aggregate Query Answers
|
2023 |
VLDB |
5.275967e-05 |
| 9,767 |
Data Augmentation for ML-driven Data Preparation and Integration
|
2021 |
VLDB |
5.275967e-05 |
| 9,769 |
iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks
|
2018 |
SIGMOD |
5.275967e-05 |
| 9,829 |
Thoth in Action: Memory Management in Modern Data Analytics
|
2017 |
VLDB |
5.2645874e-05 |
| 9,949 |
Cumulon: Matrix-Based Data Analytics in the Cloud with Spot Instances
|
2016 |
VLDB |
5.2295913e-05 |
| 10,000 |
A Unifying Algorithm for Hierarchical Queries
|
2026 |
PODS |
5.1725167e-05 |
| 10,141 |
Honeybee: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning
|
2026 |
SIGMOD |
5.1725167e-05 |
| 10,150 |
Curator: Efficient Vector Search with Low-Selectivity Filters
|
2026 |
SIGMOD |
5.1725167e-05 |
| 10,353 |
A Theoretical Framework for Distribution-Aware Dataset Search
|
2025 |
PODS |
5.1725167e-05 |
| 10,356 |
Circuits and Formulas for Datalog over Semirings
|
2025 |
PODS |
5.1725167e-05 |
| 10,403 |
Shapley Value Estimation Based on Differential Matrix
|
2025 |
SIGMOD |
5.1725167e-05 |
| 10,439 |
CauSumX: Summarized Causal Explanations For Group-By-Average Queries
|
2025 |
SIGMOD |
5.1725167e-05 |
| 10,693 |
LakeVisage: Towards Scalable, Flexible and Interactive Visualization Recommendation for Data Discovery over Data Lakes
|
2025 |
VLDB |
5.1725167e-05 |
| 10,757 |
PAR2QO: Parametric Penalty-Aware Robust Query Optimization
|
2025 |
VLDB |
5.1725167e-05 |
| 10,778 |
veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System
|
2025 |
VLDB |
5.1725167e-05 |
| 10,813 |
Hint-QPT: Hints for Robust Query Performance Tuning
|
2025 |
VLDB |
5.1725167e-05 |
| 10,927 |
k-Clustering with Comparison and Distance Oracles
|
2024 |
PODS |
5.1725167e-05 |
| 11,001 |
Database Native Model Selection: Harnessing Deep Neural Networks in Database Systems
|
2024 |
VLDB |
5.1725167e-05 |
| 11,146 |
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms
|
2024 |
VLDB |
5.1725167e-05 |
| 11,283 |
Explaining Differentially Private Query Results With DPXPlain
|
2023 |
VLDB |
5.1725167e-05 |
| 11,421 |
Rearchitecting In-Memory Object Stores for Low Latency
|
2022 |
VLDB |
5.1725167e-05 |
| 11,439 |
Algorithms for a Topology-aware Massively Parallel Computation Model
|
2021 |
PODS |
5.1725167e-05 |
| 11,474 |
On Optimizing the Trade-off between Privacy and Utility in Data Provenance
|
2021 |
SIGMOD |
5.1725167e-05 |
| 11,488 |
Practical Security and Privacy for Database Systems
|
2021 |
SIGMOD |
5.1725167e-05 |
| 11,620 |
MuSe: Multiple Deletion Semantics for Data Repair
|
2020 |
VLDB |
5.1725167e-05 |
| 11,671 |
RATest: Explaining Wrong Relational Queries Using Small Examples
|
2019 |
SIGMOD |
5.1725167e-05 |
| 11,756 |
Durable Top-k Queries on Temporal Data
|
2018 |
VLDB |
5.1725167e-05 |
| 11,832 |
Range-Max Queries on Uncertain Data
|
2016 |
PODS |
5.1725167e-05 |
| 11,873 |
A Demonstration of VisDPT: Visual Exploration of Differentially Private Trajectories
|
2016 |
VLDB |
5.1725167e-05 |
| 11,887 |
Design of Policy-Aware Differentially Private Algorithms
|
2016 |
VLDB |
5.1725167e-05 |
| 11,956 |
Tutorial: SQL-on-Hadoop Systems
|
2015 |
VLDB |
5.1725167e-05 |
| 11,981 |
iCheck: Computationally Combating "Lies, D-ned Lies, and Statistics"
|
2014 |
SIGMOD |
5.1725167e-05 |
| 12,009 |
Thoth: Towards Managing a Multi-System Cluster
|
2014 |
VLDB |
5.1725167e-05 |
| 12,026 |
Towards Building Wind Tunnels for Data Center Design
|
2014 |
VLDB |
5.1725167e-05 |
| 12,055 |
Execution and Optimization of Continuous Queries with Cyclops
|
2013 |
SIGMOD |
5.1725167e-05 |
| 12,067 |
Workload Management for Big Data Analytics
|
2013 |
SIGMOD |
5.1725167e-05 |
| 12,106 |
Permuting Data on Random-Access Block Storage
|
2013 |
VLDB |
5.1725167e-05 |
| 12,307 |
Exceeding Expectations and Clustering Uncertain Data
|
2009 |
PODS |
5.1725167e-05 |
| 12,319 |
Large-Scale Uncertainty Management Systems: Learning and Exploiting Your Data (Tutorial Summary)
|
2009 |
SIGMOD |
5.1725167e-05 |
| 12,429 |
Data-Driven Processing in Sensor Networks
|
2007 |
CIDR |
5.1725167e-05 |
| 12,489 |
Suppression and Failures in Sensor Networks: A Bayesian Approach
|
2007 |
VLDB |
5.1725167e-05 |
| 12,497 |
Asking the Right Questions: Model-driven Optimization using Probes
|
2006 |
PODS |
5.1725167e-05 |
| 12,528 |
Scalable Continuous Query Processing by Tracking Hotspots
|
2006 |
VLDB |
5.1725167e-05 |
| 12,580 |
k-Means Projective Clustering
|
2004 |
PODS |
5.1725167e-05 |
| 13,125 |
PACMMOD V3, N4 (SIGMOD), September 2025: Editorial
|
2025 |
SIGMOD |
- |
| 13,344 |
DIAS: Differentially Private Interactive Algorithm Selection using Pythia
|
2017 |
SIGMOD |
- |
| 13,352 |
Cumulon-D: Data Analytics in a Dynamic Spot Market
|
2017 |
VLDB |
- |
| 13,463 |
Big and Useful: What’s in the Data for Me? (Panel Description)
|
2013 |
VLDB |
- |