sigmod2023-index.txt

Session 1: Time Series and data series
Time2State: An Unsupervised Framework for Inferring the Latent States in Time Series Data
Grouping Time Series for Efficient Columnar Storage
Time Series Data Validity
Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting
Dumpy: A Compact and Adaptive Index for Large Data Series Collections
ForestTI: A Scalable Inverted-Index-Oriented Timeseries Management System with Flexible Memory Efficiency

Session 2: Privacy, security and encryption, blockchains
Toward Efficient Homomorphic Encryption for Outsourced Databases through Parallel Caching
RLS Side Channels: Investigating Leakage of Row-Level Security Protected Data Through Query Execution Time
A Framework for Privacy Preserving Localized Graph Pattern Query Processing
Measuring Re-identification Risk
Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump
When Private Blockchain Meets Deterministic Database

Session 3: Transactions & Indexing
Circinus: Fast Redundancy-Reduced Subgraph Matching
I/O-Efficient Butterfly Counting at Scale
Maximum k-Biplex Search on Bipartite Graphs: A Symmetric-BK Branching Approach
Scaling Up k-Clique Densest Subgraph Detection
Maximal Defective Clique Enumeration
Efficient Biclique Counting in Large Bipartite Graphs


Session 4: Sampling and cardinality estimation
Efficient Estimation of Pairwise Effective Resistance
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation
FactorJoin: A New Cardinality Estimation Framework for Join Queries
Efficient Sampling Approaches to Shapley Value Approximation
SafeBound: A Practical System for Generating Cardinality Bounds
LAQy: Efficient and Reusable Query Approximations via Lazy Sampling


Session 5: Time series and temporal data
LightCTS: A Lightweight Framework for Correlated Time Series Forecasting
T-Rex: Optimizing Pattern Search on Time Series
OM^3: An Ordered Multi-level Min-Max Representation for Interactive Progressive Visualization of Time Series
LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation
DAMR: Dynamic Adjacency Matrix Representation Learning for Multivariate Time Series Imputation
On Querying Spanned Connected Components in Large Temporal Graphs


Session 6: Differential privacy
A Neural Approach to Spatio-Temporal Data Release with User-Level Differential Privacy
An Effective and Differentially Private Protocol for Secure Distributed Cardinality Estimation
Practical Differentially Private and Byzantine-resilient Federated Learning
PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy
Global and Local Differentially Private Release of Count-Weighted Graphs
Better than Composition: How to Answer Multiple Relational Queries under Differential Privacy


Session 7: Sampling, cardinality estimation, uncertainties and probabilities
Together is Better: Heavy Hitters Latency Quantile Estimation
Efficient and Effective Cardinality Estimation for Skyline Family
JoinSketch: A Sketch Algorithm for Accurate and Unbiased Inner-Product Estimation
Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences
Probabilistic Reasoning at Scale: Trigger Graphs to the Rescue
rkHit: Representative Query with Uncertain Preference


Session 8: Clustering
A New Sparse Data Clustering Method Based on Frequent Items
An Efficient Algorithm for Distance-based Structural Graph Clustering
Fast Density-Based Clustering: Geometric Approach
FINEX: A Fast Index for Exact & Flexible Density-Based Clustering
Efficient and Effective Attributed Hypergraph Clustering via K-Nearest Neighbor Augmentation
Prerequisite-driven Fair Clustering on Heterogeneous Information Networks


Session 9: Joins
Raster Intervals: An Approximation Technique for Polygon Intersection Joins
Detecting Logic Bugs of Join Optimizations in DBMS
Efficiently Computing Join Orders with Heuristic Search
Ready to Leap (by Co-Design)? Join Order Optimisation on Quantum Hardware
Design and Analysis of a Processing-in-DIMM Join Algorithm: A Case Study with UPMEM DIMMs
Free Join: Unifying Worst-Case Optimal and Traditional Joins


Session 10: Learning, embeddings and analytics on graphs
CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression
Making It Tractable to Catch Duplicates and Conflicts in Graphs
Grep: A Graph Learning Based Database Partitioning System
Efficient Tree-SVD for Subset Node Embedding over Large Dynamic Graphs
Graph Learning for Interaction Analysis in Smart Home Rule Data
T-FSM: A Task-Based System for Massively Parallel Frequent Subgraph Pattern Mining from a Big Graph



Session 11: Data Models, Semantics, and Integration
Learned Data-aware Image Representations of Line Charts for Similarity Search
Discovering Similarity Inclusion Dependencies
SANTOS: Relationship-based Semantic Table Union Search
Composite Object Normal Forms
Discovering Top-k Rules using Subjective and Objective Criteria
Exploratory Training: When Annonators Learn About Data


Session 12: Transactions
Transaction Scheduling: From Conflicts to Runtime Conflicts
MRV: Enforcing Numeric Invariants in Parallel Updates to Hotspots with Randomized Splitting
Polaris: Enabling Transaction Priority in Optimistic Concurrency Control
DBPA: A Benchmark for Transactional Database Performance Anomalies
Detock: High Performance Multi-region Transactions at Scale
One-shot garbage collection for in-memory OLTP through temporality-aware version storage


Session 13: Ramdom walks and reachability on graphs
Personalized PageRank on Evolving Graphs with an Incremental Index-Update Scheme
Towards Generating Hop-constrained s-t Simple Path Graphs
Effective and Efficient PageRank-based Positioning for Graph Visualization
LightRW: FPGA Accelerated Graph Dynamic Random Walks
Parallel Strong Connectivity Based on Faster Reachability
HR-Index: An Effectiveness Index Method for Historical Reachability Queries over Evolving Graphs

Session 14: Streams
Fast Continuous Subgraph Matching over Streaming Graphs via Backtracking Reduction
MorphStream: Adaptive Scheduling for Scalable Transactional Stream Processing on Multicores
INEv: In-Network Evaluation for Event Stream Processing
Pontus: Finding Waves in Data Streams
Data Stream Clustering: An In-depth Empirical Study
Ghost: A General Framework for High-Performance Online Similarity Queries over Distributed Trajectory Streams

Session 15: Spatial and temporal data
Effectiveness Perspectives and a Deep Relevance Model for Spatial Keyword Queries
EAR-Oracle: On Efficient Indexing for Distance Queries between Arbitrary Points on Terrain Surface
Spatio-Temporal Denoising Graph Autoencoders with Data Augmentation for Photovoltaic Data Imputation
Caerus: A Caching-based Framework for Scalable Temporal Graph Neural Networks
GeoGauss: Strongly Consistent Coordinator-Free OLTP for Geo-Replicated SQL Database
The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data

Session 16: Query Optimization
Exploiting Structure in Regular Expression Queries
Computing the Difference of Conjunctive Queries Efficiently
Selection Pushdown in Column Stores using Bit Manipulation Instructions
Efficient Query Re-optimization with Judicious Subquery Selections
Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines
Query-Guided Resolution of Uncertain Databases

Session 17: DB4ML
Incremental Tabular Learning on Heterogeneous Feature Space
FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data
FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement
ML2DAC: Meta-Learning to Democratize AutoML for Clustering Analysis
GoodCore: Coreset Selection over Incomplete Data for Data-effective and Data-efficient Machine Learning
DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning

Session 18: Subgraph matching and counting
Efficient Star-based Truss Maintenance on Dynamic Graphs
Hereditary Cohesive Subgraphs Enumeration on Bipartite Graphs: The Power of Pivot-based Approaches
GuP: Fast Subgraph Matching by Guard-based Pruning
Efficient and Effective Algorithms for Generalized Densest Subgraph Discovery
Efficient GPU-Accelerated Subgraph Matching
Theories and Principles Matter: Towards Visually Appealing and Effective Abstraction of Property Graph Queries

Session 19: Coordination, distribution and clouds
Incentive-Aware Decentralized Data Collaboration
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning
dsJSON: A Distributed SQL JSON Processor
Generalizing Bulk-Synchronous Parallel Processing for Data Science: from data to threads and agent-based simulations
DARQ Matter Binds Everything: Performant and Composable Cloud Programming via Resilient Steps
Using Cloud Functions as Accelerator for Elastic Data Analytics

Session 20: Spatial and temporal data
Matching Roles from Temporal Data
ST4ML: Machine Learning Oriented Spatio-Temporal Data Processing at Scale
Mining Geospatial Relationships from Text
SSIN: Self-Supervised Learning for Rainfall Spatial Interpolation
WISK: A Workload-aware Learned Index for Spatial Keyword Queries
QHL: A Fast Algorithm for Exact Constrained Shortest Path Search on Road Networks

Session 21: ML4DB and Outlier detection
Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data
BALANCE: Bayesian Linear Attribution for Root Cause Localization
Kepler: Robust Learning for Parametric Query Optimization
XInsight: eXplainable Data Analysis Through The Lens of Causality
AutoOD: Automatic Outlier Detection
Robust and Transferable Log-based Anomaly Detection

Session 22: Knowledge graphs and data integration
A Universal Question-Answering Platform for Knowledge Graphs
Deep Active Alignment of Knowledge Graph Entities and Schemata
Maestro: Automatic Generation of Comprehensive Benchmarks for Question Answering Over Knowledge Graphs
Ground Truth Inference for Weakly Supervised Entity Matching
FlexER: Flexible Entity Resolution for Multiple Intents
Unicorn: A Unified Multi-tasking Model for Supporting Matching Tasks in Data Integration

Session 23: Indexing and estimation
When Tree Meets Hash: Reducing Random Reads for Index Structures on Persistent Memories
NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks
Pea Hash: A Performant Extendible Adaptive Hashing Index
Updatable Learned Indexes Meet Disk-Resident DBMS - From Evaluations to Design Choices
InfiniFilter: Expanding Filters to Infinity and Beyond
A Step Toward Deep Online Aggregation

Session 24: Big Data analytics and data science pipelines
HybridPipe: Combining Human-generated and Machine-generated Pipelines for Data Preparation
GIO: Generating Efficient Matrix and Frame Readers for Custom Data Formats by Example
Predicate Pushdown for Data Science Pipelines
DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data
Runtime Variation in Big Data Analytics
QaaD (Query-as-a-Data): Scalable Execution of Massive Number of Small Queries in Spark

Session 25: Indexing and similarity search
Efficient Approximate Nearest Neighbor Search in Multi-dimensional Databases
High-Dimensional Approximate Nearest Neighbor Search: with Reliable and Efficient Distance Comparison Operations
SplinterDB and Maplets: Improving the Tradeoffs in Key-Value Store Compaction Policy
IcebergHT: High Performance PMEM Hash Tables Through Stability and Low Associativity
Hamming Tree: The case for Energy-Aware Indexing for NVMs
LiteHST: A Tree Embedding based Method for Similarity Search

Session 26: Graphs
TED: Towards Discovering Top-𝑘 Edge-Diversified Patterns in a Graph Database
Shortest Paths Discovery in Uncertain Networks via Transfer Learning
Efficient Personalized PageRank Computation: The Power of Variance-Reduced Monte Carlo Approaches
Efficient Resistance Distance Computation: the Power of Landmark-based Approaches
GraphINC: Graph Pattern Mining at Network Speed
Scapin: Scalable Graph Structure Perturbation by Augmented Influence Maximization

Session 27: Modern hardware, performance, and benchmarking
Design Guidelines for Correct, Efficient, and Scalable Synchronization using One-Sided RDMA
Distributed GPU Joins on Fast RDMA-capable Networks
ClipSim: A GPU-friendly Parallel Framework for Single-Source SimRank with Accuracy Guarantee
Virtual-Memory Assisted Buffer Management
Optimizing Tensor Programs on Flexible Storage
How To Optimize My Blockchain? A Multi-Level Recommendation Approach

Session 28: Data mining and discovery
Regularized Pairwise Relationship based Analytics for Structured Data
Few-shot Text-to-SQL Translation using Structure and Content Prompt Learning
GitTables: A Large-Scale Corpus of Relational Tables
Near-Duplicate Sequence Search at Scale for Neural Language Model Memorization Evaluation
Unsupervised Hashing with Semantic Concept Mining
FEC: Efficient Deep Recommendation Model Training with Flexible Embedding Communication


Session 29: Compression and fairness
Double-Anonymous Sketch: Achieving Fairness for Finding Global Top-K Frequent Items
LadderFilter: Filtering Infrequent Items with Small Memory and Time Overhead
TowerSensing: Linearly Compressing Sketches with Flexibility
iFlipper: Label Flipping for Individual Fairness
Hierarchical Residual Encoding for Multiresolution Compression
BtrBlocks: Efficient Columnar Compression for Data Lakes

Session 30: Diffusion and Propagation in Graphs
DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with GPU
Scalable and Efficient Full-Graph GNN Training for Large Graphs
Managing Conflicting Interests of Stakeholders in Influencer Marketing
EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs
Mitigating Filter Bubbles Under a Competitive Diffusion Model
Popularity Ratio Maximization: Surpassing Competitors through Influence Propagation

Session 31: Optimizing data systems
LinCQA: Faster Consistent Query Answering with Linear Time Guarantees
Data-Sharing Markets: Model, Protocol, and Algorithms to Incentivize the Formation of Data-Sharing Consortia
Foreign Keys Open the Door for Faster Incremental View Maintenance
Efficient and Portable Einstein Summation in SQL
dbET: Execution Time Distribution-based Plan Selection
AWARE: Workload-aware, Redundancy-exploiting Linear Algebra