ACM SIGMOD Philadelphia, USA, 2022
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SIGMOD 2022: Accepted Research Papers

  • SLAM: Efficient Sweep Line Algorithms for Kernel Density Visualization
    Tsz Nam Chan (Hong Kong Baptist University)*; Leong Hou U (University of Macau); Byron Choi (Hong Kong Baptist University); Jianliang Xu (Hong Kong Baptist University)
  • Serenade - Low-Latency Session-Based Recommendation in e-Commerce at Scale
    Barrie Kersbergen (; Olivier Sprangers (University of Amsterdam); Sebastian Schelter (University of Amsterdam)*
  • Sherman: A Write-Optimized Distributed B+Tree Index on Disaggregated Memory
    Qing Wang (Tsinghua University)*; Youyou Lu (; Jiwu Shu (
  • P4DB - The Case for In-Network OLTP
    Matthias Jasny (TU Darmstadt)*; Lasse Thostrup (TU Darmstadt); Tobias Ziegler (TU Darmstadt); Carsten Binnig (TU Darmstadt)
  • HET-GMP: a Graph-based System Approach to Scaling Large Embedding Model Training
    Xupeng Miao (Peking University)*; Yining Shi (Peking University); Hailin Zhang (Peking University); Xin Zhang (Peking University); Xiaonan Nie (Peking University); Zhi Yang (Peking University); Bin Cui (Peking University)
  • Compact Walks: Taming Knowledge-Graph Embeddings with Domain- and Task-Specific Pathways
    Pei-Yu Hou (NCSU); Daniel Korn (UNC Chapel Hill); Cleber Melo-Filho (UNC Chapel Hill); David Wright (NCSU); Alexander Tropsha (UNC); Rada Chirkova (NC State University)*
  • Rethinking Stateful Stream Processing with RDMA
    Bonaventura Del Monte (Technische Universität Berlin)*; Steffen Zeuch (DFKI Berlin); Tilmann Rabl (HPI, University of Potsdam); Volker Markl (Technische Universität Berlin)
  • Optimizing Recursive Queries with Progam Synthesis
    Yisu R Wang (University of Washington)*; Mahmoud Abo Khamis (RelationalAI); Hung Ngo (RelationalAI); Reinhard Pichler (TU Wien); Dan Suciu (University of Washington)
  • Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects
    Clemens Lutz (Technische Universität Berlin)*; Sebastian Breß (Snowflake); Steffen Zeuch (DFKI Berlin); Tilmann Rabl (HPI, University of Potsdam); Volker Markl (Technische Universität Berlin)
  • HYPERSONIC: A Hybrid Parallelization Approach for Scalable Complex Event Processing
    Maor Yankovitch (Technion)*; Ilya Kolchinsky (Technion); Assaf Schuster (Technion)
  • Conjunctive Queries with Comparisons
    Qichen Wang (Hong Kong University of Science and Technology); Ke Yi (Hong Kong Univ. of Science and Technology)*
  • Faster and Better Solution to Embed Lp Metrics by Tree Metrics
    Yuxiang Zeng (Hong Kong University of Science and Technology); Yongxin Tong (Beihang University); Lei Chen (Hong Kong University of Science and Technology)*
  • Computing the Shapley Value of Facts in Query Answering
    Nave Frost (Tel-Aviv University)*; Daniel Deutch (Tel Aviv University); Benny Kimelfeld (Technion); Mikaël Monet (Millenium Instititute for Foundational Research on Data)
  • DenForest: Enabling Fast Deletion in Incremental Density-Based Clustering over Sliding Windows
    Bogyeong Kim (Seoul National University); Kyoseung Koo (Seoul National University); Undraa Enkhbat (Seoul National University); Bongki Moon (Seoul National University)*
  • Proteus: Autonomous Adaptive Storage for Mixed Workloads
    Michael Abebe (University of Waterloo)*; Horatiu Lazu (University of Waterloo); Khuzaima Daudjee (University of Waterloo)
  • OTIF: Efficient Tracker Pre-processing over Large Video Datasets
    Favyen Bastani (MIT CSAIL)*; Samuel Madden (MIT)
  • Camel: Managing Data for Efficient Stream Learning
    Yiming Li (Hong Kong University of Science and Technology)*; Yanyan Shen (Shanghai Jiao Tong University); Lei Chen (Hong Kong University of Science and Technology)
  • A Convex-Programming Approach for Efficient Directed Densest Subgraph Discovery
    Chenhao Ma (The University of Hong Kong)*; Yixiang Fang (School of Data Science, The Chinese University of Hong Kong, Shenzhen); Reynold Cheng ("The University of Hong Kong, China"); Laks V.S. Lakshmanan (The University of British Columbia); xiaolin han (The University of Hong Kong)
  • Scalable and Effective Bipartite Network Embedding
    Renchi Yang (National University of Singapore)*; Jieming Shi (The Hong Kong Polytechnic University); Keke Huang (National University of Singapore); Xiaokui Xiao (National University of Singapore)
  • Secure and Policy-Compliant Query Processing on Heterogeneous Computational Storage Architectures
    Harshavardhan Unnibhavi (Technische Universität München)*; David Martins Cerdeira (University of Minho); Antonio Barbalace (The University of Edinburgh); Nuno Santos (INESC-ID / Instituto Superior Técnico, Universidade de Lisboa); Pramod Bhatotia (TU Munich)
  • Video-zilla: An Indexing Layer for Large-Scale Video Analytics
    Bo Hu (Yale University)*; Peizhen Guo (Yale University); Wenjun Hu (Yale University)
  • Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification
    Maliha Tashfia Islam (University of Massachusetts Amherst)*; Anna Fariha (Microsoft); Alexandra Meliou (University of Massachusetts Amherst); Babak Salimi (Unievristy of California at San Diego)
  • Evaluating Multi-GPU Sorting with Modern Interconnects
    Tobias Maltenberger (Hasso Plattner Institute)*; Ivan Ilic (Hasso Plattner Institute); Ilin Tolovski (Hasso Plattner Institute); Tilmann Rabl (HPI, University of Potsdam)
  • DB-BERT: a Database Tuning Tool that "Reads the Manual"
    Immanuel Trummer (Cornell)*
  • R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys
    Wei DONG (Hong Kong University of Science and Technology, Hong Kong); Juanru FANG (HKUST); Ke Yi (Hong Kong Univ. of Science and Technology)*; Yuchao Tao (Duke University); Ashwin Machanavajjhala (Duke)
  • Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems
    Matthew Butrovich (Carnegie Mellon University)*; Wan Shen Lim (Carnegie Mellon University); Lin Ma (Carnegie Mellon University); John Rollinson (Army Cyber Institute); William Zhang (Carnegie Mellon University); Yu Xia (MIT); Andrew Pavlo (Carnegie Mellon University)
  • Nautilus: An Optimized System for Deep Transfer Learning over Evolving Training Datasets
    Supun C Nakandala (University of California, San Diego)*; Arun Kumar (University of California, San Diego)
  • FILA: Online Auditing of Machine Learning Model Accuracy under Finite Labelling Budget
    Naiqing Guan (University of Toronto)*; Nick Koudas (University of Toronto)
  • Efficient Algorithms for Maximal k-Biplex Enumeration
    Kaiqiang Yu (Nanyang Technological University)*; Cheng Long (Nanyang Technological University); Shengxin Liu (Harbin Institute of Technology, Shenzhen); Da Yan (University of Alabama at Birmingham)
  • Where Is My Training Bottleneck? Hidden Trade-Offs in Deep Learning Preprocessing Pipelines
    Alexander Isenko (Technical University of Munich)*; Ruben Mayer (Technical University of Munich); Jeffery Jedele (Technical University of Munich); Hans-Arno Jacobsen (University of Toronto)
  • Complaint-Driven Training Data Debugging at Interactive Speeds
    Lampros Flokas (Columbia University)*; Weiyuan Wu (Simon Fraser University); Yejia Liu (Simon Fraser University); Jiannan Wang (Simon Fraser University); Nakul Verma (Columbia University); Eugene Wu (Columbia University)
  • JEDI: These Aren't the JSON Documents You're Looking for...
    Thomas Hütter (University of Salzburg)*; Nikolaus Augsten (University of Salzburg); Christoph Kirsch (University of Salzburg); Michael Carey (UC Irvine); Chen Li (UC Irvine)
  • Towards a Practical Database Management System with Verifiable ACID Properties and Transaction Correctness
    Yu Xia (MIT)*; Xiangyao Yu (University of Wisconsin-Madison); Matthew Butrovich (Carnegie Mellon University); Andrew Pavlo (Carnegie Mellon University); Srinivas Devadas (MIT)
  • Confidence Bounded Replica Currency Estimation
    Yu Sun (Tsinghua University); Zheng Zheng (McMaster University); Shaoxu Song (Tsinghua University)*; Fei Chiang (McMaster University)
  • Optimizing Parallel Recursive Datalog Evaluation on Multicore Machines
    Jiacheng Wu (Tsinghua University)*; Jin Wang (UCLA); Carlo Zaniolo (UCLA, USA)
  • Reptile: Aggregation-level Explanations for Hierarchical Data
    Zezhou Huang (Columbia University); Eugene Wu (Columbia University)*
  • Protecting Data Markets from Strategic Buyers
    Raul Castro Fernandez (UChicago)*
  • Serverless Data Science - Are We There Yet? A Case Study of Model Serving
    Yuncheng Wu (National University of Singapore)*; Tien Tuan Anh Dinh (Singapore University of Technology and Design); Guoyu Hu (National University of Singapore); Meihui Zhang (Beijing Institute of Technology); Yeow Meng Chee (National University of Singapore); Beng Chin Ooi (NUS)
  • Optimizing Data-intensive Systems in Disaggregated Data Centers with TELEPORT
    "Qizhen Zhang (University of Pennsylvania)*; Xinyi Chen (University of Pennsylvania ); Sidharth Sankhe (University of Pennsylvania); Zhilei Zheng (University of Pennsylvania); Ke Zhong (University of Pennsylvania); Sebastian Angel (University of Pennsylvania); Ang Chen (Rice University); Vincent Liu (University of Pennsylvania); Boon Thau Loo (Univ. of Pennsylvania)"
  • FiGO: Fine-Grained Query Optimization in Video Analytics
    Jiashen Cao (Georgia Tech)*; Karan Sarkar (Georgia Institute of Technology); Ramyad Hadidi (Georiga Tech); Joy Arulraj (Georgia Tech); Hyesoon Kim (Georgia Tech)
  • Representative Query Results by Voting
    Rachel Behar (The Hebrew University of Jerusalem)*; Sara Cohen (The Hebrew University of Jerusalem)
  • Hunting Temporal Bumps in Graphs with Dynamic Vertex Properties
    Yahui Sun (Renmin University of China)*; Shuai Ma (Beihang University); Bin Cui (Peking University)
  • NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access
    Alexander Renz-Wieland (Technische Universität Berlin)*; Rainer Gemulla (Universität Mannheim); Zoi Kaoudi (TU Berlin); Volker Markl (Technische Universität Berlin)
  • Unsupervised Contextual Anomaly Detection for Database Systems
    Sainan Li (Tsinghua University)*; Qilei Yin (Tsinghua University); Guoliang Li (Tsinghua University); Qi Li (Tsinghua University); Zhuotao Liu (Tsinghua University); jinwei zhu (Huawei Technologies Co., Ltd.)
  • A Hierarchical Contraction Scheme for Querying Big Graphs
    Wenfei Fan (Univ. of Edinburgh ); Yuanhao Li (University of Edinburgh)*; Muyang Liu (University of Edinburgh); Can Lu (SICS)
  • Classifier Construction Under Budget Constraints
    Shay Gershtein (Tel Aviv University); Tova Milo (Tel Aviv University); Slava Novgorodov (eBay Research)*; Kathy Razmadze (Tel Aviv University)
  • DataPrism: Exposing Disconnect between Data and Systems
    Sainyam Galhotra (University of Chicago)*; Anna Fariha (Microsoft); Raoni Lourenço (New York University); Juliana Freire (New York University); Alexandra Meliou (University of Massachusetts Amherst); Divesh Srivastava (AT&T Chief Data Office)
  • Rank Aggregation with Proportionate Fairness
    Dong Wei (NJIT); Md Mouinul Islam (New Jersey Institute of Technology ); Baruch Schieber (New Jersey Institute of Technology); Senjuti Basu Roy (NJIT)*
  • Annotating Columns with Pre-trained Language Models
    Yoshihiko Suhara (Megagon Labs)*; Jinfeng Li (Megagon Labs); Yuliang Li (Megagon Labs); Dan Zhang (Megagon Labs); Cagatay Demiralp (Sigma Computing); Chen Chen (Megagon Labs); Wang-Chiew Tan (Facebook AI)
  • Finding Label and Model Errors in Perception Data With Learned Observation Assertions
    Daniel Kang (Stanford University)*; Nikos Arechiga (Toyota Research Institute); Sudeep Pillai (TRI); Peter D Bailis (Stanford University); Matei Zaharia (Stanford and Databricks)
  • AutoMon: Automatic Distributed Monitoring for Arbitrary Multivariate Functions
    Hadar Sivan (Technion); Moshe Gabel (University of Toronto )*; Assaf Schuster (Technion)
  • The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures
    Evgenios Kornaropoulos (George Mason University)*; Silei Ren (Cornell University); Roberto Tamassia (Brown University)
  • Towards Practical Oblivious Join
    Zhao Chang (Xidian University); Dong Xie (Penn State University); Sheng Wang (Alibaba Group); Feifei Li (Alibaba Group)*
  • SPINE: Scaling up Programming-by-Negative-Example for String Filtering and Transformation
    Chaoji Zuo (Rutgers University); Sepehr Assadi (-); Dong Deng (Rutgers Universituy - New Brunswick)*
  • TCUDB: Accelerating Database with Tensor Processors
    Yu-Ching Hu (University of California, Riverside)*; Yuliang Li (Megagon Labs); Hung-Wei Tseng (University of California, Riverside)
  • Domain Adaptation for Deep Entity Resolution
    Jianhong Tu (Renmin University of China); Ju Fan (Renmin University of China)*; Nan Tang (Qatar Computing Research Institute, HBKU); Peng Wang (Renmin University of China); Chengliang Chai (Tsinghua University); Guoliang Li (Tsinghua University); Ruixue Fan (Renmin University of China); Xiaoyong Du (Renmin University of China)
  • Efficient Massively Parallel Join Optimization for Large Queries
    Riccardo Mancini (Scuola Superiore Sant'Anna); Srinivas Karthik Venkatesh (EPFL)*; Bikash Chandra (EPFL); Vasilis Mageirakos (University of Patras); Anastasia Ailamaki (EPFL)
  • Causal Feature Selection for Algorithmic Fairness
    Sainyam Galhotra (University of Chicago)*; Karthikeyan Shanmugam (IBM Research NY); Prasanna Sattigeri (IBM Research); Kush R Varshney (IBM Research)
  • Entity Resolution with Hierarchical Graph Attention Networks
    Dezhong Yao (Huazhong University of Science and Technology)*; Yuhong Gu (Huazhong University of Science and Technology); Gao Cong (Nanyang Technological Univesity); Hai Jin (Huazhong University of Science and Technology); Xinqiao Lv (Huazhong University of Science and Technology)
  • HINT: A Hierarchical Index for Intervals in Main Memory
    George Christodoulou (University of Ioannina); Panagiotis Bouros (Johannes Gutenberg University Mainz)*; Nikos Mamoulis (University of Ioannina)
  • On Scalable Computation of Graph Eccentricities
    Wentao Li (University of Technology Sydney); Miao Qiao (The University of Auckland)*; Lu Qin (UTS); Lijun Chang (The University of Sydney); Ying Zhang (University of Technology Sydney); Xuemin Lin (University of New South Wales)
  • Relative Subboundedness of Contraction Hierarchy and Hierarchical 2-Hop Index in Dynamic Road Networks
    Yikai Zhang (Chinese University of Hong Kong)*; Jeffrey Xu Yu (Chinese University of Hong Kong)
  • GaccO - A GPU-accelerated OLTP DBMS
    Nils Boeschen (TU Darmstadt)*; Carsten Binnig (TU Darmstadt)
  • Redundancy Elimination in Distributed Matrix Computation
    "Zihao Chen (East China Normal University); Baokun Han (East China Normal University); Chen Xu (East China Normal University)*; Weining Qian (East China Normal University); Aoying Zhou (East China Normal University )"
  • PreQR: Pre-training Representation for SQL Understanding
    Xiu Tang (Zhejiang University); Sai Wu (Zhejiang Univ)*; Mingli Song (Zhejiang University); Shanshan Ying (Alibaba); Feifei Li (Alibaba Group); Gang Chen (Zhejiang University)
  • Plor: General Transactions with Predictable, Low Tail Latency
    "Youmin Chen (Tsinghua University)*; Xiangyao Yu (University of Wisconsin-Madison); Paraschos Koutris (University of Wisconsin-Madison); Andrea Arpaci-Dusseau ( University of Wisconsin-Madison); Remzi Arpaci-Dusseau (University of Wisconsin-Madison); Jiwu Shu ("
  • An Efficient Hamming Space Index Based on Augmented Pigeonhole Principle
    Qiyu LIU (Hong Kong University of Science and Technology)*; Yanyan Shen (Shanghai Jiao Tong University); Lei Chen (Hong Kong University of Science and Technology)
  • One Set to Cover All Maximal Cliques Approximately
    Xiaofan Li (Swinburne University of Technology); Rui Zhou (Swinburne University of Technology)*; Lu Chen (Swinburne University of Technology); Chengfei Liu (Swinburne University of Technology); Qiang He (Swinburne University of Technology); Yun Yang (Swinburne University of Technology)
  • HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements
    Baoqing Cai (Huazhong University of Science and Technology)*; Yu Liu (Huazhong University of Science and Technology); Ce Zhang (ETH); Guangyu Zhang (Huazhong University of Science and Technology); Ke Zhou (Huazhong University of Science and Technology); Li Liu (Huazhong University of Science and Technology); Chunhua Li (Huazhong University of Science and Technology); Bin Cheng (Tencent); Jie Yang (Tencent); Jiashu Xing (tencent)
  • BatchHL: Answering Distance Queries on Batch-Dynamic Networks at Scale
    Muhammad Farhan (Australian National University)*; Qing Wang (ANU); Henning Koehler (Massey University)
  • Halo: A Hybrid PMem-DRAM Persistent Hash Index with Fast Recovery
    Daokun Hu (College of Computer Science and Electronic Engineering, Hunan University, China); Zhiwen Chen (Hunan University); cw k (HUNAN university); Jianhua Sun (College of Computer Science and Electronic Engineering, Hunan University, China); Hao Chen (College of Computer Science and Electronic Engineering, Hunan University, China)*
  • Balsa: Learning a Query Optimizer Without Expert Demonstrations
    Zongheng Yang (UC Berkeley)*; Wei-Lin Chiang (UC Berkeley); Sifei Luan (UC Berkeley); Gautam Mittal (UC Berkeley); Michael Luo (UC Berkeley); Ion Stoica (UC Berkeley)
  • Interpretable Data-Based Explanations for Fairness Debugging
    Romila Pradhan (University of California San Diego)*; Jiongli Zhu (University of California San Diego); Boris Glavic (Illinois Institute of Technology); Babak Salimi (Unievristy of California at San Diego)
  • Explaining Link Prediction Systems based on Knowledge Graph Embeddings
    Andrea Rossi (Roma Tre University)*; Donatella Firmani (Roma Tre University); Paolo Merialdo (University Roma Tre); Tommaso Teofili (Roma Tre University)
  • Scalable Time Series Compound Infrastructure
    Noura S Alghamdi (WPI)*; liang zhang (WPI); Elke A Rundensteiner (WPI); Mohamed Y. Eltabakh (Worcester Polytechnic Institute)
  • Efficient Incrementialization of Correlated Nested Aggregate Queries using Relative Partial Aggregate Indexes (RPAI)
    Supun Madusha Bandara Abeysinghe Tennakoon Mudiyanselage (Purdue University)*; Qiyang He (Purdue University); Tiark Rompf (Purdue University)
  • Anchored Densest Subgraph
    Yizhou Dai (University of Auckland); Miao Qiao (The University of Auckland)*; Lijun Chang (The University of Sydney)
  • Leva: Boosting Machine Learning Performance with Relational Embedding Data Augmentation
    Zixuan Zhao (University of Chicago)*; Raul Castro Fernandez (UChicago)
  • Juggler: Autonomous cost optimization and performance prediction of big data applications
    Hani Al-Sayeh (TU Ilmenau)*; Bunjamin Memishi (German Aerospace Center); Muhammad Attahir Jibril (TU Ilmenau); Marcus Paradies (German Aerospace Center); Kai-Uwe Sattler (TU Ilmenau)
  • Sintel: A Machine Learning Framework to Extract Insights from Signals
    Sarah Alnegheimish (MIT)*; Dongyu Liu (MIT); Carles Sala (MIT); Laure Berti-Equille (IRD); Kalyan Veeramachaneni (MIT)
  • Computing Complex Temporal Join Queries Efficiently
    Xiao Hu (Duke University)*; Stavros Sintos (University of Chicago); Junyang Gao (Google); Pankaj K Agarwal (Duke University); Jun Yang (Duke University)
  • Entropy Learned Hashing: Constant Time Hashing with Controllable Uniformity
    Brian N Hentschel (Harvard University)*; Utku Sirin (Harvard University); Stratos Idreos (Harvard)
  • FuseME: Distributed Matrix Computation Engine based on Cuboid-based Fused Operator and Plan Generation
    Donghyoung Han (KAIST)*; Jongwuk Lee (Sungkyunkwan University); Min-Soo Kim (KAIST)
  • Selectivity Functions of Range Queries are Learnable
    Xiao Hu (Duke University)*; Yuxi Liu (Duke University); Haibo Xiu (Duke University); Pankaj K Agarwal (Duke University); Debmalya Panigrahi (Duke University); Sudeepa Roy (Duke University, USA); Jun Yang (Duke University)
  • TASTI: Semantic Indexes for Machine Learning-based Queries over Unstructured Data
    Daniel Kang (Stanford University)*; John Guibas (Stanford University); Peter D Bailis (Stanford University); Tatsunori Hashimoto (Stanford); Matei Zaharia (Stanford and Databricks)
  • Understanding Queries by Conditional Instances
    Amir Gilad (Duke University)*; Zhengjie Miao (Duke University); Sudeepa Roy (Duke University, USA); Jun Yang (Duke University)
  • Controlled Intentional Degradation in Analytical Video Systems
    Wenjia He (University of Michigan)*; Michael Cafarella (University of Michigan)
  • One Size Does Not Fit All: A Bandit-Based Sampler Combination Framework with Theoretical Guarantees
    Jinglin Peng (Simon Fraser University)*; Bolin Ding ("Data Analytics and Intelligence Lab, Alibaba Group"); Jiannan Wang (Simon Fraser University); Kai Zeng (Alibaba Group); Jingren Zhou (Alibaba Group)
  • Neural Subgraph Counting with Wasserstein Estimator
    Hanchen Wang (University Of Technology Sydney)*; Rong Hu (University of Technology Sydney); Ying Zhang (University of Technology Sydney); Lu Qin (UTS); Wei Wang (Hong Kong University of Science and Technology (Guangzhou)); Wenjie Zhang (University of New South Wales)
  • Efficient Evaluation of Arbitrarily-Framed Holistic SQL Aggregates and Window Functions
    Adrian Vogelsgesang (Tableau)*; Thomas Neumann (TUM); Viktor Leis (Friedrich-Alexander-Universität Erlangen-Nürnberg); Alfons Kemper (TUM)
  • DMCS : Density Modularity based Community Search
    Junghoon Kim (Nanyang Technological University)*; Siqiang Luo (Nanyang Technological University); Gao Cong (Nanyang Technological Univesity); Wenyuan Yu (Alibaba Group)
  • MinMax Sampling: A Near-optimal Global Summary for Aggregation in the Wide Area
    Yikai Zhao (Peking University); Yinda Zhang (Peking University); Yuanpeng Li (Peking University); Yi Zhou (Peking University); Chunhui Chen (Peking Univeristy); Tong Yang (Peking University)*; Bin Cui (Peking University)
  • Diva: Making MVCC Systems HTAP-Friendly
    Jongbin Kim (Hanyang University); Jaeseon Yu (Hanyang University); Jaechan Ahn (Hanyang University); Sooyong Kang (Hanyang University); Hyungsoo Jung (Hanyang University)*
  • Avoiding Read Stalls on Flash Storage
    Mijin An (Sungkyunkwan University ); Sang Won Lee (Sungkyunkwan University)*; In-Yeong Song (Hanyang University); Yong Ho Song (Samsung Electronics Co.)
  • Adaptive Hybrid Indexes
    Christoph Anneser (Technical University of Munich)*; Andreas Kipf (MIT); Huanchen Zhang (Tsinghua University); Thomas Neumann (TU Munich); Alfons Kemper (TUM)
  • Ad Hoc Transactions in Web Applications: The Good, the Bad, and the Ugly
    Chuzhe Tang (Shanghai Jiao Tong University); Zhaoguo Wang (Shanghai Jiao Tong University); Xiaodong Zhang (Shanghai Jiao Tong University); Qianmian Yu (Shanghai Jiao Tong University); Binyu Zang (Shanghai Jiao Tong University); Haibing Guan(Shanghai Jiao Tong University); Haibo Chen (Shanghai Jiao Tong University)
  • WeTune: Automatic Discovery and Verification of Query Rewrite Rules
    Zhaoguo Wang (ShangHai Jiao Tong University); Zhou Zhou (ShangHai Jiao Tong University); Yicun Yang (ShangHai Jiao Tong University); Haoran Ding (ShangHai Jiao Tong University); Gansen Hu (ShangHai Jiao Tong University); Ding Ding (ShangHai Jiao Tong University); Chuzhe Tang (ShangHai Jiao Tong University); Haibo Chen (ShangHai Jiao Tong University); Jinyang Li(New York University)
  • Fast Maximal Clique Enumeration on Uncertain Graphs: A Pivot-based Approach
    Qiangqiang Dai (Beijing Institute of Technology); Ronghua Li (Beijing Institute of Technology)*; Meihao Liao (Beijing Institute of Technology); Hongzhi CHEN (ByteDance); Guoren Wang (Beijing Institute of Technology)
  • Efficient Personalized PageRank Computation: A Spanning Forests Sampling Based Approach
    Meihao Liao (Beijing Institute of Technology); Ronghua Li (Beijing Institute of Technology)*; Qiangqiang Dai (Beijing Institute of Technology); Guoren Wang (Beijing Institute of Technology)
  • Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts
    Beibin Li (University of Washington); Yao Lu (Microsoft Research)*; Srikanth Kandula (Microsoft Research)
  • Sommelier: Curating DNN Models for the Masses
    Peizhen Guo (Yale University)*; Bo Hu (Yale University); Wenjun Hu (Yale University)
  • BlindFL: Vertical Federated Machine Learning without Peeking into Your Data
    "Fangcheng Fu (Peking University)*; Huanran Xue (Tencent Inc.); Yong Cheng ( Tencent Inc.); Yangyu Tao (Tencent Inc.); Bin Cui (Peking University)"
  • TimeUnion: An Efficient Architecture with Unified Data Model for Timeseries Management Systems on Hybrid Cloud Storage
    Zhiqi WANG (The Chinese University of HK)*; Zili Shao (The Chinese University of Hong Kong)
  • Materialization and Reuse Optimizations for Production Data Science Pipelines
    Behrouz Derakhshan (DFKI)*; Alireza Rezaei Mahdiraji (AgoroCarbon); Zoi Kaoudi (TU Berlin); Tilmann Rabl (HPI, University of Potsdam); Volker Markl (Technische Universität Berlin)
  • Cooperative Route Planning Framework for Multiple Distributed Assets in Maritime Applications
    Sepideh Nikookar (NJIT); Paras Sakharkar (NJIT); Sathya Somasunder (NJIT); Senjuti Basu Roy (NJIT)*; Adam Bienkowski (University of Connecticut); Matthew Macesker (University of Connecticut); Krishna Pattipati (University of Connecticut); David Sidoti (Navy Research Lab)
  • Towards Dynamic and Safe Configuration Tuning for Cloud Databases
    Xinyi Zhang (Peking University); HONG WU (Alibaba); Yang Li (Peking University); Jian Tan (Alibaba); Feifei Li (Alibaba Group); Bin Cui (Peking University)*
  • SIEVE: A Space-Efficient Algorithm for Viterbi Decoding
    Martino Ciaperoni (Aalto University); Aristides Gionis (KTH Royal Institute of Technology); Athanasios Katsamanis ("ATHENA R.C., Behavioral Signal Technologies"); Panagiotis Karras (Aarhus University)*
  • Network Shuffling: Privacy Amplification via Random Walks
    Seng Pei Liew (LINE Corporation)*; Tsubasa Takahashi (LINE Corporation); Shun Takagi (Kyoto University); Fumiyuki Kato (Kyoto University); Yang Cao (Kyoto University); Masatoshi Yoshikawa (Kyoto University)
  • Efficient Answering of Historical What-if Queries
    Felix S Campbell (Illinois Institute of Technology); Bahareh Sadat Arab (Illinois Institute of Technology); Boris Glavic (Illinois Institute of Technology)*
  • ScaleStore: A Fast and Cost-Efficient Storage Engine using DRAM, NVMe, and RDMA
    Tobias Ziegler (TU Darmstadt)*; Carsten Binnig (TU Darmstadt); Viktor Leis (Friedrich-Alexander-Universität Erlangen-Nürnberg)
  • 𝜏-LevelIndex: Towards Efficient Query Processing in Continuous Preference Space
    JIAHAO ZHANG (The Hong Kong Polytechnic University)*; Bo Tang (Southern University of Science and Technology); Man Lung Yiu (Hong Kong Polytechnic University); Xiao Yan (Southern University of Science and Technology); Keming Li (Southern University of Science and Technology)
  • Tile-based Lightweight Integer Compression in GPU
    Anil Shanbhag (MIT)*; Bobbi W Yogatama (University of Wisconsin-Madison); Xiangyao Yu (University of Wisconsin-Madison); Samuel Madden (MIT)
  • In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle
    Lijie Xu (ETH Zurich)*; Shuang Qiu (University of Chicago); Binhang Yuan (ETH Zurich); Jiawei Jiang (ETH Zurich); Cedric Renggli (ETH Zurich); Shaoduo Gan (ETH Zurich); Kaan Kara (ETHZ); Guoliang Li (Tsinghua University); Ji Liu (Kwai Inc.); Wentao Wu (Microsoft Research); Jieping Ye (Didi Chuxing & University of Michigan); Ce Zhang (ETH)
  • Automated Category Tree Construction in E-Commerce
    Uri Avron (Tel Aviv University); Shay Gershtein (Tel Aviv University); Ido Guy (Meta); Tova Milo (Tel Aviv University); Slava Novgorodov (eBay Research)*
  • CoLES: Contrastive Learning for Event Sequences with Self-Supervision
    Dmitrii Babaev (Sberbank AI Lab)*; Nikita Ovsov (Sberbank AI Lab); Ivan Kireev (Sberbank AI Lab); Gleb Gusev (Sberbank); Maria Ivanova (Sberbank AI Lab); Ivan Nazarov (AIRI Moscow); Alexander Tuzhilin (New York University, USA)
  • PI2: End-to-end Interactive Visualization Interface Generation from Queries
    Yiru Chen (Columbia University); Eugene Wu (Columbia University)*
  • IncShrink: Architecting Efficient Outsourced Databases using Incremental MPC and Differential Privacy
    Chenghong Wang (Duke University)*; Johes Bater (Duke University); Kartik Nayak (DUKE UNIVERSITY); Ashwin Machanavajjhala (Duke)
  • GraphZeppelin: Storage-Friendly Sketching for Connected Components on Dynamic Graph Streams
    David Tench (Stony Brook University)*; Tyler Seip (MongoDB); Martin Farach-Colton (Rutgers University); Michael A Bender (Stony Brook); Abiyaz Chowdhury (Stony Brook University); Evan T West (Stony Brook University); Victor Zhang (Rutgers University); Kenny Zhang (Stony Brook University); J. Ahmed Dellas (Rutgers University)
  • Parallel Query Processing: To Separate Communication from Computation
    Hao Zhang (Chinese University of Hong Kong)*; Jeffrey Xu Yu (Chinese University of Hong Kong); Yikai Zhang (Chinese University of Hong Kong); Kangfei Zhao (The Chinese University of Hong Kong)
  • Hierarchical Entity Resolution using an Oracle
    Sainyam Galhotra (University of Chicago)*; Donatella Firmani (Roma Tre University); Barna Saha (University of California, San Diego); Divesh Srivastava (AT&T Chief Data Office)
  • Budget-aware Index Tuning with Reinforcement Learning
    Wentao Wu (Microsoft Research)*; Chi Wang (Microsoft Research); Tarique Siddiqui (Microsoft Research); Junxiong Wang (Cornell University); Vivek Narasayya (Microsoft); Surajit Chaudhuri (Microsoft); Philip A Bernstein (Microsoft Research)
  • CompressDB: Enabling Efficient Compressed Data Direct Processing for Various Databases
    Weitao Wan (Renmin University of China)*; Feng Zhang (Renmin University of China); Chenyang Zhang (Renmin University of China); Jidong Zhai (Tsinghua University); yunpeng chai (renmin university of china); Haixiang Li (Tencent Inc., China); Xiaoyong Du (Renmin University of China)
  • DLACEP: A Deep-Learning Based Framework for Approximate Complex Event Processing
    Adar Amir (Technion)*; Ilya Kolchinsky (Technion); Assaf Schuster (Technion)
  • NeutronStar: Distributed GNN Training with Hybrid Dependency Management
    Qiange Wang (Northeastern University); Yanfeng Zhang (NorthEastern University)*; Hao Wang (the Ohio State University); Chaoyi Chen (Northeastern University); Xiaodong Zhang (Ohio State U.); Ge Yu (Northeast University)
  • Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process
    Kangfei Zhao (The Chinese University of Hong Kong)*; Jeffrey Xu Yu (Chinese University of Hong Kong); Zongyan He (The Chinese University of Hong Kong); Rui Li (The Chinese University of Hong Kong); Hao Zhang (Chinese University of Hong Kong)
  • Parallel Rule Discovery from Large Datasets by Sampling
    "Wenfei Fan (Univ. of Edinburgh ); Ziyan Han (Beihang University); Yaoshu Wang (Shenzhen Institute of Computing Sciences, Shenzhen University)*; Min Xie (Shenzhen Institute of Computing Sciences )"
  • LearnedSQLGen: Constraint-aware SQL Generation using Reinforcement Learning
    Lixi Zhang (Tsinghua University); Chengliang Chai (Tsinghua University); Xuanhe Zhou (Tsinghua); Guoliang Li (Tsinghua University)*
  • Approximate Range Thresholding
    Zhuo Zhang (University of Melbourne); Junhao Gan (University of Melbourne)*; Zhifeng Bao (RMIT University); Seyed Mohammad Hussein Kazemi (The University of Melbourne ); Guangyong Chen (Shenzhen Institutes of Advanced Technology); Fengyuan Zhu (Kaifeng Investment)
  • LDP-IDS: Local Differential Privacy for Infinite Data Streams
    Xuebin Ren (Xi'an Jiaotong University)*; Liang Shi (Xi'an JiaoTong University); Weiren Yu (University of Warwick); Shusen Yang (Xi'an Jiaotong University); Cong Zhao (‎Imperial College London); Zongben Xu (Xi'an Jiaotong University)
  • Learned Cardinality Estimation: An In-depth Study
    Kyoungmin Kim (POSTECH); Jisung Jeong (Postech); In Seo (POSTECH); Wook-Shin Han (POSTECH)*; Kangwoo Choi (SAP Labs Korea); Jaehyok Chong (SAP)
  • Snapper: A Transaction Library for Actor Systems
    Yijian Liu (University of Copenhagen)*; Yongluan Zhou (University of Copenhagen); Vivek Shah (Independent Researcher); Li Su (Alibaba Group); Marcos Antonio Vaz Salles (University of Copenhagen (DIKU))
  • HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach
    Sainyam Galhotra (University of Chicago); Amir Gilad (Duke University)*; Sudeepa Roy (Duke University, USA); Babak Salimi (Unievristy of California at San Diego)
  • Givens QR Decomposition over Relational Databases
    Dan Olteanu (University of Zurich)*; Nils Vortmeier (University of Zurich); Dorde Zivanovic (University of Oxford)
  • End-to-end Optimization of Machine Learning Prediction Queries
    Kwanghyun Park (Microsoft)*; Karla Saur (Microsoft); Dalitso Banda (Microsoft); Rathijit Sen (Microsoft); Matteo Interlandi (Microsoft); Konstantinos Karanasos (Microsoft)
  • Gloria: Graph-based Sharing Optimizer for Event Trend Aggregation
    Lei Ma (WPI)*; Chuan Lei (Instacart); Olga Poppe (Microsoft); Elke A Rundensteiner (WPI)
  • SAM: Database Generation from Query Workload with Supervised Autoregressive Model
    Jingyi Yang (NTU)*; Peizhi Wu (University of Pennsylvania); Gao Cong (Nanyang Technological Univesity); Tieying Zhang (Carnegie Mellon University); Xiao He (Alibaba Group)
  • EVA: A Symbolic Approach to Accelerating Exploratory Video Analytics with Materialized Views
    Zhuangdi Xu (Georgia Tech)*; Gaurav Tarlok Kakkar (Georgia Institute of Technology); Joy Arulraj (Georgia Tech); Umakishore Ramachandran (Georgia Institute of Technology)
  • ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning
    Tarique Siddiqui (Microsoft Research)*; Saehan Jo (Cornell University); Wentao Wu (Microsoft Research); Chi Wang (Microsoft Research); Vivek Narasayya (Microsoft); Surajit Chaudhuri (Microsoft)
  • Statistical Schema Learning with Occam's Razor
    Daniel Ting (Tableau Software)*; Justin Talbot (Databricks)
  • Adaptive Threshold Sampling
    Daniel Ting (Tableau Software)*
  • Zeus: Efficiently Localizing Actions in Videos using Reinforcement Learning
    Pramod Chunduri (Georgia Institute of Technology)*; Jaeho Bang (Georgia Institute of Technology); Yao Lu (Microsoft Research); Joy Arulraj (Georgia Tech)
  • dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification
    Paul Boniol (Université de Paris)*; Mohammed Meftah (EDF R&D); Emmanuel Remy (EDF R&D); Themis Palpanas (University of Paris)
  • TxtAlign: Efficient Near-Duplicate Text Alignment Search via Bottom-k Sketches for Plagiarism Detection
    Zhizhi Wang (Rutgers University); Chaoji Zuo (Rutgers University); Dong Deng (Rutgers Universituy - New Brunswick)*
  • Skeena: Efficient and Consistent Cross-Engine Transactions
    Jianqiu Zhang (Simon Fraser University); Kaisong Huang (Simon Fraser University)*; Tianzheng Wang (Simon Fraser University); King Lv (Huawei Technologies Co. Ltd.)
  • TSUBASA: Climate Network Construction on Historical and Real-Time Data
    Yunlong Xu (University of Rochester); Jinshu Liu (University of Rochester); Fatemeh Nargesian (University of Rochester)*
  • X-SSD: A Storage System with Native Support for Database Logging and Replication
    Sangjin Lee (Hanyang University); Alberto Lerner (University of Friborug)*; André Ryser (University of Fribourg); Kibin Park (Hanyang University); Chanyoung Jeon (Hanyang University); Jinsub Park (Hanyang University); Yong Ho Song (Hanyang University & Samsung Electronics); Philippe Cudre-Mauroux (Exascale Infolab, Fribourg University)
  • LOCAT: Low-Overhead Online Configuration Auto-Tuning of Spark SQL Applications
    Jinhan Xin (Shenzhen Institutes of Advanced Technology , CAS)*; Kai Hwang (The Chinese University of Hong Kong, Shenzhen); Zhibin Yu (Shenzhen Institutes of Advanced Technology, Chinese Academy of Science)
  • Proteus: A Self-Designing Range Filter
    Eric R Knorr (Harvard)*; Baptiste J Lemaire (Harvard University); Andrew Lim (Harvard University); Huanchen Zhang (Tsinghua University); Siqiang Luo (Nanyang Technological University); Stratos Idreos (Harvard); Michael Mitzenmacher (Harvard)
  • LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems
    Ibrahim Sabek (MIT)*; Tenzin Ukyab (Massachusetts Institute of Technology); Tim Kraska (MIT)
  • How good is my HTAP system?
    Elena Milkai (UW Madison)*; Yannis Chronis (University of Wisconsin Madison); Kevin P Gaffney (University of Wisconsin-Madison); Zhihan Guo (University of Wisconsin-Madison); Jignesh Patel (UW - Madison); Xiangyao Yu (University of Wisconsin-Madison)
  • Natto: Providing Distributed Transaction Prioritization for High-Contention Workloads
    Linguan Yang (University of Waterloo)*; Xinan Yan (University of Waterloo); Bernard Wong (University of Waterloo)

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