MetaStore: Analyzing Deep Learning Meta-Data at Scale. Proc. VLDB Endow., 2024
Huayi Zhang, Binwei Yan, Lei Cao, Samuel Madden, Elke A. Rundensteiner
Serverless State Management Systems. CIDR, 2024
Tianyu Li, Badrish Chandramouli, Sebastian Burckhardt, Samuel Madden
Kairos: Efficient Temporal Graph Analytics on a Single Machine. CoRR, 2024
Joana M. F. da Trindade, Julian Shun, Samuel Madden, Nesime Tatbul
Increasing Forest Cover and Connectivity Both Inside and Outside of Protected Areas in Southwestern Costa Rica. Remote. Sens., 2024
Hilary Brumberg, Samuel Furey, Marie G. Bouffard, María José Mata Quirós, Hikari Murayama, Soroush Neyestani, Emily Pauline, Andrew Whitworth, Marguerite Madden
Stage: Query Execution Time Prediction in Amazon Redshift. CoRR, 2024
Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska
Panda: Performance Debugging for Databases using LLM Agents. CIDR, 2024
Vikramank Y. Singh, Kapil Vaidya, Vinayshekhar Bannihatti Kumar, Sopan Khosla, Balakrishnan Narayanaswamy, Rashmi Gangadharaiah, Tim Kraska
PipeRAG: Fast Retrieval-Augmented Generation via Algorithm-System Co-design. CoRR, 2024
Wenqi Jiang, Shuai Zhang, Boran Han, Jie Wang, Bernie Wang, Tim Kraska
DARQ Matter Binds Everything: Performant and Composable Cloud Programming via Resilient Steps. Proc. ACM Manag. Data, 2023
Tianyu Li, Badrish Chandramouli, Sebastian Burckhardt, Samuel Madden
AutoOD: Automatic Outlier Detection. Proc. ACM Manag. Data, 2023
Lei Cao, Yizhou Yan, Yu Wang, Samuel Madden, Elke A. Rundensteiner
Few-shot Text-to-SQL Translation using Structure and Content Prompt Learning. Proc. ACM Manag. Data, 2023
Zihui Gu, Ju Fan, Nan Tang, Lei Cao, Bowen Jia, Sam Madden, Xiaoyong Du
SeeSaw: Interactive Ad-hoc Search Over Image Databases. Proc. ACM Manag. Data, 2023
Oscar R. Moll, Manuel Favela, Samuel Madden, Vijay Gadepally, Michael J. Cafarella
Cackle: Analytical Workload Cost and Performance Stability With Elastic Pools. Proc. ACM Manag. Data, 2023
Matthew Perron, Raul Castro Fernandez, David J. DeWitt, Michael J. Cafarella, Samuel Madden
FactorJoin: A New Cardinality Estimation Framework for Join Queries. Proc. ACM Manag. Data, 2023
Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden
Lingua Manga: A Generic Large Language Model Centric System for Data Curation. Proc. VLDB Endow., 2023
Zui Chen, Lei Cao, Sam Madden
Extract-Transform-Load for Video Streams. Proc. VLDB Endow., 2023
Ferdinand Kossmann, Ziniu Wu, Eugenie Lai, Nesime Tatbul, Lei Cao, Tim Kraska, Sam Madden
Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes. Proc. VLDB Endow., 2023
Tim Kraska, Tianyu Li, Samuel Madden, Markos Markakis, Amadou Ngom, Ziniu Wu, Geoffrey X. Yu
Robust Query Driven Cardinality Estimation under Changing Workloads. Proc. VLDB Endow., 2023
Parimarjan Negi, Ziniu Wu, Andreas Kipf, Nesime Tatbul, Ryan Marcus, Sam Madden, Tim Kraska, Mohammad Alizadeh
Pando: Enhanced Data Skipping with Logical Data Partitioning. Proc. VLDB Endow., 2023
Sivaprasad Sudhir, Wenbo Tao, Nikolay Pavlovich Laptev, Cyrille Habis, Michael J. Cafarella, Samuel Madden
Symphony: Towards Natural Language Query Answering over Multi-modal Data Lakes. CIDR, 2023
Zui Chen, Zihui Gu, Lei Cao, Ju Fan, Samuel Madden, Nan Tang
Future of Database System Architectures. SIGMOD Conference Companion, 2023
Gustavo Alonso, Natassa Ailamaki, Sailesh Krishnamurthy, Sam Madden, Swami Sivasubramanian, Raghu Ramakrishnan
Interpretable Outlier Summarization. CoRR, 2023
Yu Wang, Lei Cao, Yizhou Yan, Samuel Madden
RITA: Group Attention is All You Need for Timeseries Analytics. CoRR, 2023
Jiaming Liang, Lei Cao, Samuel Madden, Zachary G. Ives, Guoliang Li
Interleaving Pre-Trained Language Models and Large Language Models for Zero-Shot NL2SQL Generation. CoRR, 2023
Zihui Gu, Ju Fan, Nan Tang, Songyue Zhang, Yuxin Zhang, Zui Chen, Lei Cao, Guoliang Li, Sam Madden, Xiaoyong Du
RoTaR: Efficient Row-Based Table Representation Learning via Teacher-Student Training. CoRR, 2023
Zui Chen, Lei Cao, Sam Madden
Lingua Manga: A Generic Large Language Model Centric System for Data Curation. CoRR, 2023
Zui Chen, Lei Cao, Sam Madden
SEED: Simple, Efficient, and Effective Data Management via Large Language Models. CoRR, 2023
Zui Chen, Lei Cao, Sam Madden, Ju Fan, Nan Tang, Zihui Gu, Zeyuan Shang, Chunwei Liu, Michael J. Cafarella, Tim Kraska
Extract-Transform-Load for Video Streams. CoRR, 2023
Ferdinand Kossmann, Ziniu Wu, Eugenie Lai, Nesime Tatbul, Lei Cao, Tim Kraska, Samuel Madden
R3: Record-Replay-Retroaction for Database-Backed Applications. Proc. VLDB Endow., 2023
Qian Li, Peter Kraft, Michael J. Cafarella, Çagatay Demiralp, Goetz Graefe, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Xiangyao Yu, Matei Zaharia
Transactions Make Debugging Easy. CIDR, 2023
Qian Li, Peter Kraft, Michael J. Cafarella, Çagatay Demiralp, Goetz Graefe, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Matei Zaharia
PAINE Demo: Optimizing Video Selection Queries With Commonsense Knowledge. Proc. VLDB Endow., 2023
Wenjia He, Ibrahim Sabek, Yuze Lou, Michael J. Cafarella
Causal Data Integration. Proc. VLDB Endow., 2023
Brit Youngmann, Michael J. Cafarella, Babak Salimi, Anna Zeng
On Explaining Confounding Bias. ICDE, 2023
Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi
NEXUS: On Explaining Confounding Bias. SIGMOD Conference Companion, 2023
Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi
Causal Data Integration. CoRR, 2023
Brit Youngmann, Michael J. Cafarella, Babak Salimi, Anna Zeng
Epoxy: ACID Transactions Across Diverse Data Stores. Proc. VLDB Endow., 2023
Peter Kraft, Qian Li, Xinjing Zhou, Peter Bailis, Michael Stonebraker, Xiangyao Yu, Matei Zaharia
Two is Better Than One: The Case for 2-Tree for Skewed Data Sets. CIDR, 2023
Xinjing Zhou, Xiangyao Yu, Goetz Graefe, Michael Stonebraker
Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28 - September 1, 2023. VLDB WorkshopsCEUR Workshop Proceedings, 2023
Rajesh Bordawekar, Cinzia Cappiello, Vasilis Efthymiou, Lisa Ehrlinger, Vijay Gadepally, Sainyam Galhotra, Sandra Geisler, Sven Groppe, Le Gruenwald, Alon Y. Halevy, Hazar Harmouch, Oktie Hassanzadeh, Ihab F. Ilyas, Ernesto Jiménez-Ruiz, Sanjay Krishnan, Tirthankar Lahiri, Guoliang Li, Jiaheng Lu, Wolfgang Mauerer, Umar Farooq Minhas, Felix Naumann, M. Tamer Özsu, El Kindi Rezig, Kavitha Srinivas, Michael Stonebraker, Satyanarayana R. Valluri, Maria-Esther Vidal, Haixun Wang, Jiannan Wang, Yingjun Wu, Xun Xue, Mohamed Zaït, Kai Zeng
Enhancing Computation Pushdown for Cloud OLAP Databases. CoRR, 2023
Yifei Yang, Xiangyao Yu, Marco Serafini, Ashraf Aboulnaga, Michael Stonebraker
The Case for Learned In-Memory Joins. Proc. VLDB Endow., 2023
Ibrahim Sabek, Tim Kraska
Unshackling Database Benchmarking from Synthetic Workloads. ICDE, 2023
Parimarjan Negi, Laurent Bindschaedler, Mohammad Alizadeh, Tim Kraska, Jyoti Leeka, Anja Gruenheid, Matteo Interlandi
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift. SIGMOD Conference Companion, 2023
Gaurav Saxena, Mohammad Rahman, Naresh Chainani, Chunbin Lin, George Caragea, Fahim Chowdhury, Ryan Marcus, Tim Kraska, Ippokratis Pandis, Balakrishnan (Murali) Narayanaswamy
CorBit: Leveraging Correlations for Compressing Bitmap Indexes. VLDB Workshops, 2023
Xi Lyu, Andreas Kipf, Pascal Pfeil, Dominik Horn, Jana Giceva, Tim Kraska
Hyperspecialized Compilation for Serverless Data Analytics. VLDB Workshops, 2023
Leonhard F. Spiegelberg, Tim Kraska, Malte Schwarzkopf
Parallel External Sorting of ASCII Records Using Learned Models. CoRR, 2023
Ani Kristo, Tim Kraska
ExSample: Efficient Searches on Video Repositories through Adaptive Sampling. ICDE, 2022
Oscar R. Moll, Favyen Bastani, Sam Madden, Mike Stonebraker, Vijay Gadepally, Tim Kraska
ExSample: Efficient Searches on Video Repositories through Adaptive Sampling. ICDE, 2022
Oscar R. Moll, Favyen Bastani, Sam Madden, Mike Stonebraker, Vijay Gadepally, Tim Kraska
A Demonstration of AutoOD: A Self-tuning Anomaly Detection System. Proc. VLDB Endow., 2022
Dennis M. Hofmann, Peter M. VanNostrand, Huayi Zhang, Yizhou Yan, Lei Cao, Samuel Madden, Elke A. Rundensteiner
Self-Organizing Data Containers. CIDR, 2022
Samuel Madden, Jialin Ding, Tim Kraska, Sivaprasad Sudhir, David E. Cohen, Timothy G. Mattson, Nesime Tatbul
Performant Almost-Latch-Free Data Structures Using Epoch Protection. DaMoN, 2022
Tianyu Li, Badrish Chandramouli, Samuel Madden
Ad-hoc Searches on Image Databases. Poly/DMAH@VLDB, 2022
Oscar R. Moll Thomae, Sam Madden, Vijay Gadepally
OTIF: Efficient Tracker Pre-processing over Large Video Datasets. SIGMOD Conference, 2022
Favyen Bastani, Samuel Madden
Tile-based Lightweight Integer Compression in GPU. SIGMOD Conference, 2022
Anil Shanbhag, Bobbi W. Yogatama, Xiangyao Yu, Samuel Madden
SeeSaw: interactive ad-hoc search over image databases. CoRR, 2022
Oscar R. Moll, Manuel Favela, Samuel Madden, Vijay Gadepally
FactorJoin: A New Cardinality Estimation Framework for Join Queries. CoRR, 2022
Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden
Nonintrusive Measurements for Detecting Progressive Equipment Faults. IEEE Trans. Instrum. Meas., 2022
Daisy H. Green, Devin W. Quinn, Samuel Madden, Peter A. Lindahl, Steven B. Leeb
A Progress Report on DBOS: A Database-oriented Operating System. CIDR, 2022
Qian Li, Peter Kraft, Kostis Kaffes, Athinagoras Skiadopoulos, Deeptaanshu Kumar, Jason Li, Michael J. Cafarella, Goetz Graefe, Jeremy Kepner, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Matei Zaharia
Apiary: A DBMS-Backed Transactional Function-as-a-Service Framework. CoRR, 2022
Peter Kraft, Qian Li, Kostis Kaffes, Athinagoras Skiadopoulos, Deeptaanshu Kumar, Danny Cho, Jason Li, Robert Redmond, Nathan W. Weckwerth, Brian S. Xia, Peter Bailis, Michael J. Cafarella, Goetz Graefe, Jeremy Kepner, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Xiangyao Yu, Matei Zaharia
Transactions Make Debugging Easy. CoRR, 2022
Qian Li, Peter Kraft, Michael J. Cafarella, Çagatay Demiralp, Goetz Graefe, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Matei Zaharia
Infrastructure for Rapid Open Knowledge Network Development. AI Mag., 2022
Michael J. Cafarella, Michael R. Anderson, Iz Beltagy, Arie Cattan, Sarah E. Chasins, Ido Dagan, Doug Downey, Oren Etzioni, Sergey Feldman, Tian Gao, Tom Hope, Kexin Huang, Sophie Johnson, Daniel King, Kyle Lo, Yuze Lou, Matthew D. Shapiro, Dinghao Shen, Shivashankar Subramanian, Lucy Lu Wang, Yuning Wang, Yitong Wang, Daniel S. Weld, Jenny M. Vo-Phamhi, Anna Zeng, Jiayun Zou
Building a Shared Conceptual Model of Complex, Heterogeneous Data Systems: A Demonstration. CIDR, 2022
Michael R. Anderson, Yuze Lou, Jiayun Zou, Michael J. Cafarella, Sarah E. Chasins, Doug Downey, Tian Gao, Kexin Huang, Dinghao Shen, Jenny M. Vo-Phamhi, Yitong Wang, Yuning Wang, Anna Zeng
Debugging the OmniTable Way. OSDI, 2022
Andrew Quinn, Jason Flinn, Michael J. Cafarella, Baris Kasikci
HILDA'22: The SIGMOD 2022 Workshop on Human-in-the-Loop Data Analytics. SIGMOD Conference, 2022
Azza Abouzied, Dominik Moritz, Michael J. Cafarella
Controlled Intentional Degradation in Analytical Video Systems. SIGMOD Conference, 2022
Wenjia He, Michael J. Cafarella
Enabling useful provenance in scripting languages with a human-in-the-loop. HILDA@SIGMOD, 2022
Yuze Lou, Michael J. Cafarella
On Explaining Confounding Bias. CoRR, 2022
Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi
The Seattle report on database research. Commun. ACM, 2022
Daniel Abadi, Anastasia Ailamaki, David G. Andersen, Peter Bailis, Magdalena Balazinska, Philip A. Bernstein, Peter A. Boncz, Surajit Chaudhuri, Alvin Cheung, AnHai Doan, Luna Dong, Michael J. Franklin, Juliana Freire, Alon Y. Halevy, Joseph M. Hellerstein, Stratos Idreos, Donald Kossmann, Tim Kraska, Sailesh Krishnamurthy, Volker Markl, Sergey Melnik, Tova Milo, C. Mohan, Thomas Neumann, Beng Chin Ooi, Fatma Ozcan, Jignesh M. Patel, Andrew Pavlo, Raluca A. Popa, Raghu Ramakrishnan, Christopher Ré, Michael Stonebraker, Dan Suciu
Applying Machine Learning and Data Fusion to the "Missing Person" Problem. Computer, 2022
K. M. A. Solaiman, Tao Sun, Alina Nesen, Bharat K. Bhargava, Michael Stonebraker
Lotus: Scalable Multi-Partition Transactions on Single-Threaded Partitioned Databases. Proc. VLDB Endow., 2022
Xinjing Zhou, Xiangyao Yu, Goetz Graefe, Michael Stonebraker
Kyrix-J: Visual Discovery of Connected Datasets in a Data Lake. CIDR, 2022
Wenbo Tao, Adam Sah, Leilani Battle, Remco Chang, Michael Stonebraker
Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB Workshops, Poly 2022 and DMAH 2022, Virtual Event, September 9, 2022, Revised Selected Papers Poly/DMAH@VLDBLecture Notes in Computer Science, 2022
El Kindi Rezig, Vijay Gadepally, Timothy G. Mattson, Michael Stonebraker, Tim Kraska, Jun Kong, Gang Luo, Dejun Teng, Fusheng Wang
Machine Learning with DBOS. CoRR, 2022
Robert Redmond, Nathan W. Weckwerth, Brian S. Xia, Qian Li, Peter Kraft, Deeptaanshu Kumar, Çagatay Demiralp, Michael Stonebraker
Research Report: Progress on Building a File Observatory for Secure Parser Development. SP, 2022
Tim Allison, Wayne Burke, Dustin Graf, Chris Mattmann, Anastasija Mensikova, Mike Milano, Philip Southam, Ryan Stonebraker
SageDB: An Instance-Optimized Data Analytics System. Proc. VLDB Endow., 2022
Jialin Ding, Ryan Marcus, Andreas Kipf, Vikram Nathan, Aniruddha Nrusimha, Kapil Vaidya, Alexander van Renen, Tim Kraska
Can Learned Models Replace Hash Functions? Proc. VLDB Endow., 2022
Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Michael Mitzenmacher, Tim Kraska
SNARF: A Learning-Enhanced Range Filter. Proc. VLDB Endow., 2022
Kapil Vaidya, Tim Kraska, Subarna Chatterjee, Eric R. Knorr, Michael Mitzenmacher, Stratos Idreos
TreeLine: An Update-In-Place Key-Value Store for Modern Storage. Proc. VLDB Endow., 2022
Geoffrey X. Yu, Markos Markakis, Andreas Kipf, Per-Åke Larson, Umar Farooq Minhas, Tim Kraska
Bao: Making Learned Query Optimization Practical. SIGMOD Rec., 2022
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
LSI: a learned secondary index structure. aiDM@SIGMOD, 2022
Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems. SIGMOD Conference, 2022
Ibrahim Sabek, Tenzin Samten Ukyab, Tim Kraska
LSI: A Learned Secondary Index Structure. CoRR, 2022
Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska
Inferring and improving street maps with data-driven automation. Commun. ACM, 2021
Favyen Bastani, Songtao He, Satvat Jagwani, Edward Park, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, Mohammad Amin Sadeghi
ATLANTIC: Making Database Differentially Private and Faster with Accuracy Guarantee. Proc. VLDB Endow., 2021
Lei Cao, Dongqing Xiao, Yizhou Yan, Samuel Madden, Guoliang Li
Epoch-based Commit and Replication in Distributed OLTP Databases. Proc. VLDB Endow., 2021
Yi Lu, Xiangyao Yu, Lei Cao, Samuel Madden
Replicated Layout for In-Memory Database Systems. Proc. VLDB Endow., 2021
Sivaprasad Sudhir, Michael J. Cafarella, Samuel Madden
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation. Proc. VLDB Endow., 2021
Nan Tang, Ju Fan, Fangyi Li, Jianhong Tu, Xiaoyong Du, Guoliang Li, Samuel Madden, Mourad Ouzzani
LANCET: Labeling Complex Data at Scale. Proc. VLDB Endow., 2021
Huayi Zhang, Lei Cao, Samuel Madden, Elke A. Rundensteiner
Updating Street Maps using Changes Detected in Satellite Imagery. SIGSPATIAL/GIS, 2021
Favyen Bastani, Songtao He, Satvat Jagwani, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, Mohammad Amin Sadeghi
Beyond Road Extraction: A Dataset for Map Update using Aerial Images. ICCV, 2021
Favyen Bastani, Sam Madden
Inferring high-resolution traffic accident risk maps based on satellite imagery and GPS trajectories. ICCV, 2021
Songtao He, Mohammad Amin Sadeghi, Sanjay Chawla, Mohammad Alizadeh, Hari Balakrishnan, Samuel Madden
ELITE: Robust Deep Anomaly Detection with Meta Gradient. KDD, 2021
Huayi Zhang, Lei Cao, Peter M. VanNostrand, Samuel Madden, Elke A. Rundensteiner
Self-Supervised Multi-Object Tracking with Cross-input Consistency. NeurIPS, 2021
Favyen Bastani, Songtao He, Samuel Madden
SkyQuery: an aerial drone video sensing platform. Onward, 2021
Favyen Bastani, Songtao He, Ziwen Jiang, Osbert Bastani, Sam Madden
Asynchronous Prefix Recoverability for Fast Distributed Stores. SIGMOD Conference, 2021
Tianyu Li, Badrish Chandramouli, Jose M. Faleiro, Samuel Madden, Donald Kossmann
TagMe: GPS-Assisted Automatic Object Annotation in Videos. CoRR, 2021
Songtao He, Favyen Bastani, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden
MultiScope: Efficient Video Pre-processing for Exploratory Video Analytics. CoRR, 2021
Favyen Bastani, Sam Madden
SkyQuery: An Aerial Drone Video Sensing Platform. CoRR, 2021
Favyen Bastani, Songtao He, Ziwen Jiang, Osbert Bastani, Michael J. Cafarella, Tim Kraska, Sam Madden
Beyond Road Extraction: A Dataset for Map Update using Aerial Images. CoRR, 2021
Favyen Bastani, Sam Madden
Updating Street Maps using Changes Detected in Satellite Imagery. CoRR, 2021
Favyen Bastani, Songtao He, Satvat Jagwani, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, Mohammad Amin Sadeghi
Self-Supervised Multi-Object Tracking with Cross-Input Consistency. CoRR, 2021
Favyen Bastani, Songtao He, Sam Madden
DBOS: A DBMS-oriented Operating System. Proc. VLDB Endow., 2021
Athinagoras Skiadopoulos, Qian Li, Peter Kraft, Kostis Kaffes, Daniel Hong, Shana Mathew, David Bestor, Michael J. Cafarella, Vijay Gadepally, Goetz Graefe, Jeremy Kepner, Christos Kozyrakis, Tim Kraska, Michael Stonebraker, Lalith Suresh, Matei Zaharia
Data Governance in a Database Operating System (DBOS). Poly/DMAH@VLDB, 2021
Deeptaanshu Kumar, Qian Li, Jason Li, Peter Kraft, Athinagoras Skiadopoulos, Lalith Suresh, Michael J. Cafarella, Michael Stonebraker
Technical Report on Data Integration and Preparation. CoRR, 2021
El Kindi Rezig, Michael J. Cafarella, Vijay Gadepally
ML-In-Databases: Assessment and Prognosis. IEEE Data Eng. Bull., 2021
Tim Kraska, Umar Farooq Minhas, Thomas Neumann, Olga Papaemmanouil, Jignesh M. Patel, Christopher Ré, Michael Stonebraker
DICE: Data Discovery by Example. Proc. VLDB Endow., 2021
El Kindi Rezig, Anshul Bhandari, Anna Fariha, Benjamin Price, Allan Vanterpool, Vijay Gadepally, Michael Stonebraker
Horizon: Scalable Dependency-driven Data Cleaning. Proc. VLDB Endow., 2021
El Kindi Rezig, Mourad Ouzzani, Walid G. Aref, Ahmed K. Elmagarmid, Ahmed R. Mahmood, Michael Stonebraker
FlexPushdownDB: Hybrid Pushdown and Caching in a Cloud DBMS. Proc. VLDB Endow., 2021
Yifei Yang, Matt Youill, Matthew E. Woicik, Yizhou Liu, Xiangyao Yu, Marco Serafini, Ashraf Aboulnaga, Michael Stonebraker
Kyrix-S: Authoring Scalable Scatterplot Visualizations of Big Data. IEEE Trans. Vis. Comput. Graph., 2021
Wenbo Tao, Xinli Hou, Adam Sah, Leilani Battle, Remco Chang, Michael Stonebraker
DBOS: A Database-Oriented Operating System : Keynote 1. SERVICES, 2021
Michael Stonebraker
Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB Workshops, Poly 2020 and DMAH 2020, Virtual Event, August 31 and September 4, 2020, Revised Selected Papers Poly/DMAH@VLDBLecture Notes in Computer Science, 2021
Vijay Gadepally, Timothy G. Mattson, Michael Stonebraker, Tim Kraska, Fusheng Wang, Gang Luo, Jun Kong, Alevtina Dubovitskaya
Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB Workshops, Poly 2021 and DMAH 2021, Virtual Event, August 20, 2021, Revised Selected Papers Poly/DMAH@VLDBLecture Notes in Computer Science, 2021
El Kindi Rezig, Vijay Gadepally, Timothy G. Mattson, Michael Stonebraker, Tim Kraska, Fusheng Wang, Gang Luo, Jun Kong, Alevtina Dubovitskaya
Flow-Loss: Learning Cardinality Estimates That Matter. Proc. VLDB Endow., 2021
Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Davos: A System for Interactive Data-Driven Decision Making. Proc. VLDB Endow., 2021
Zeyuan Shang, Emanuel Zgraggen, Benedetto Buratti, Philipp Eichmann, Navid Karimeddiny, Charlie Meyer, Wesley Runnels, Tim Kraska
Chiller: Contention-centric Transaction Execution and Data Partitioning for Modern Networks. SIGMOD Rec., 2021
Erfan Zamanian, Julian Shun, Carsten Binnig, Tim Kraska
Traveling Repairperson, Unrelated Machines, and Other Stories About Average Completion Times. ICALP, 2021
Marcin Bienkowski, Artur Kraska, Hsiang-Hsuan Liu
Towards a Benchmark for Learned Systems. ICDE Workshops, 2021
Laurent Bindschaedler, Andreas Kipf, Tim Kraska, Ryan Marcus, Umar Farooq Minhas
Partitioned Learned Bloom Filters. ICLR, 2021
Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska
LEA: A Learned Encoding Advisor for Column Stores. aiDM@SIGMOD, 2021
Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska
Instance-Optimized Data Layouts for Cloud Analytics Workloads. SIGMOD Conference, 2021
Jialin Ding, Umar Farooq Minhas, Badrish Chandramouli, Chi Wang, Yinan Li, Ying Li, Donald Kossmann, Johannes Gehrke, Tim Kraska
Bao: Making Learned Query Optimization Practical. SIGMOD Conference, 2021
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Steering Query Optimizers: A Practical Take on Big Data Workloads. SIGMOD Conference, 2021
Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc T. Friedman, Alekh Jindal
Tuplex: Data Science in Python at Native Code Speed. SIGMOD Conference, 2021
Leonhard F. Spiegelberg, Rahul Yesantharao, Malte Schwarzkopf, Tim Kraska
Flow-Loss: Learning Cardinality Estimates That Matter. CoRR, 2021
Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Traveling Repairperson, Unrelated Machines, and Other Stories About Average Completion Times. CoRR, 2021
Marcin Bienkowski, Artur Kraska, Hsiang-Hsuan Liu
LEA: A Learned Encoding Advisor for Column Stores. CoRR, 2021
Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska
When Are Learned Models Better Than Hash Functions? CoRR, 2021
Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Tim Kraska
Defeating duplicates: A re-design of the LearnedSort algorithm. CoRR, 2021
Ani Kristo, Kapil Vaidya, Tim Kraska
PLEX: Towards Practical Learned Indexing. CoRR, 2021
Mihail Stoian, Andreas Kipf, Ryan Marcus, Tim Kraska
The Case for Learned In-Memory Joins. CoRR, 2021
Ibrahim Sabek, Tim Kraska
Bounding the Last Mile: Efficient Learned String Indexing. CoRR, 2021
Benjamin Spector, Andreas Kipf, Kapil Vaidya, Chi Wang, Umar Farooq Minhas, Tim Kraska
ExSample: Efficient Searches on Video Repositories through Adaptive Sampling. CoRR, 2020
Oscar R. Moll, Favyen Bastani, Sam Madden, Mike Stonebraker, Vijay Gadepally, Tim Kraska
Deductive optimization of relational data storage. Proc. ACM Program. Lang., 2020
John K. Feser, Sam Madden, Nan Tang, Armando Solar-Lezama
Vaas: Video Analytics At Scale. Proc. VLDB Endow., 2020
Favyen Bastani, Oscar R. Moll, Samuel Madden
Aria: A Fast and Practical Deterministic OLTP Database. Proc. VLDB Endow., 2020
Yi Lu, Xiangyao Yu, Lei Cao, Samuel Madden
Debugging Large-Scale Data Science Pipelines using Dagger. Proc. VLDB Endow., 2020
El Kindi Rezig, Ashrita Brahmaroutu, Nesime Tatbul, Mourad Ouzzani, Nan Tang, Timothy G. Mattson, Samuel Madden, Michael Stonebraker
Smartphone Placement Within Vehicles. IEEE Trans. Intell. Transp. Syst., 2020
Johan Wahlström, Isaac Skog, Peter Händel, Bill Bradley, Samuel Madden, Hari Balakrishnan
RoadTagger: Robust Road Attribute Inference with Graph Neural Networks. AAAI, 2020
Songtao He, Favyen Bastani, Satvat Jagwani, Edward Park, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Samuel Madden, Mohammad Amin Sadeghi
Dagger: A Data (not code) Debugger. CIDR, 2020
El Kindi Rezig, Lei Cao, Giovanni Simonini, Maxime Schoemans, Samuel Madden, Nan Tang, Mourad Ouzzani, Michael Stonebraker
Large-scale in-memory analytics on Intel® Optane™ DC persistent memory. DaMoN, 2020
Anil Shanbhag, Nesime Tatbul, David E. Cohen, Samuel Madden
Sat2Graph: Road Graph Extraction Through Graph-Tensor Encoding. ECCV, 2020
Songtao He, Favyen Bastani, Satvat Jagwani, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Mohamed M. Elshrif, Samuel Madden, Mohammad Amin Sadeghi
Kaskade: Graph Views for Efficient Graph Analytics. ICDE, 2020
Joana M. F. da Trindade, Konstantinos Karanasos, Carlo Curino, Samuel Madden, Julian Shun
BeeCluster: drone orchestration via predictive optimization. MobiSys, 2020
Songtao He, Favyen Bastani, Arjun Balasingam, Karthik Gopalakrishnan, Ziwen Jiang, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden
MIRIS: Fast Object Track Queries in Video. SIGMOD Conference, 2020
Favyen Bastani, Songtao He, Arjun Balasingam, Karthik Gopalakrishnan, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden
Human-in-the-loop Outlier Detection. SIGMOD Conference, 2020
Chengliang Chai, Lei Cao, Guoliang Li, Jian Li, Yuyu Luo, Samuel Madden
Starling: A Scalable Query Engine on Cloud Functions. SIGMOD Conference, 2020
Matthew Perron, Raul Castro Fernandez, David J. DeWitt, Samuel Madden
A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics. SIGMOD Conference, 2020
Anil Shanbhag, Samuel Madden, Xiangyao Yu
Continuously Adaptive Similarity Search. SIGMOD Conference, 2020
Huayi Zhang, Lei Cao, Yizhou Yan, Samuel Madden, Elke A. Rundensteiner
Optimizing Query Predicates with Disjunctions for Column Stores. CoRR, 2020
Albert Kim, Atalay Mert Ileri, Sam Madden
A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics (Extended Version). CoRR, 2020
Anil Shanbhag, Samuel Madden, Xiangyao Yu
Unnatural Language Processing: Bridging the Gap Between Synthetic and Natural Language Data. CoRR, 2020
Alana Marzoev, Samuel Madden, M. Frans Kaashoek, Michael J. Cafarella, Jacob Andreas
Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding. CoRR, 2020
Songtao He, Favyen Bastani, Satvat Jagwani, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Mohamed M. Elshrif, Samuel Madden, Mohammad Amin Sadeghi
Relational Pretrained Transformers towards Democratizing Data Preparation [Vision]. CoRR, 2020
Nan Tang, Ju Fan, Fangyi Li, Jianhong Tu, Xiaoyong Du, Guoliang Li, Sam Madden, Mourad Ouzzani
Toward a Harmonized WHO Family of International Classifications Content Model. AMIA, 2020
Samson W. Tu, Csongor Nyulas, Tania Tudorache, Mark A. Musen, Andrea Martinuzzi, Coen H. van Gool, Vincenzo Della Mea, Christopher G. Chute, Lucilla Frattura, Nicholas R. Hardiker, Huib ten Napel, Richard Madden, Ann-Helene Almborg, Jeewani Anupama Ginige, Catherine Sykes, Can Çelik, Robert Jakob
Toward a Harmonized WHO Family of International Classifications Content Model. MIE, 2020
Samson W. Tu, Csongor I. Nyulas, Tania Tudorache, Mark A. Musen, Andrea Martinuzzi, Coen H. van Gool, Vincenzo Della Mea, Christopher G. Chute, Lucilla Frattura, Nick Hardiker, Huib ten Napel, Richard Madden, Ann-Helene Almborg, Jeewani Anupama Ginige, Catherine Sykes, Can Celik, Robert Jakob
A Polystore Based Database Operating System (DBOS). Poly/DMAH@VLDB, 2020
Michael J. Cafarella, David J. DeWitt, Vijay Gadepally, Jeremy Kepner, Christos Kozyrakis, Tim Kraska, Michael Stonebraker, Matei Zaharia
Towards Data Discovery by Example. Poly/DMAH@VLDB, 2020
El Kindi Rezig, Allan Vanterpool, Vijay Gadepally, Benjamin Price, Michael J. Cafarella, Michael Stonebraker
DBOS: A Proposal for a Data-Centric Operating System. CoRR, 2020
Michael J. Cafarella, David J. DeWitt, Vijay Gadepally, Jeremy Kepner, Christos Kozyrakis, Tim Kraska, Michael Stonebraker, Matei Zaharia
Constructing Expressive Relational Queries with Dual-Specification Synthesis. CIDR, 2020
Christopher Baik, Zhongjun Jin, Michael J. Cafarella, H. V. Jagadish
Duoquest: A Dual-Specification System for Expressive SQL Queries. SIGMOD Conference, 2020
Christopher Baik, Zhongjun Jin, Michael J. Cafarella, H. V. Jagadish
A Method for Optimizing Opaque Filter Queries. SIGMOD Conference, 2020
Wenjia He, Michael R. Anderson, Maxwell Strome, Michael J. Cafarella
Duoquest: A Dual-Specification System for Expressive SQL Queries. CoRR, 2020
Christopher Baik, Zhongjun Jin, Michael J. Cafarella, H. V. Jagadish
Winds from Seattle: Database Research Directions. Proc. VLDB Endow., 2020
Peter Bailis, Magda Balazinska, Xin Luna Dong, Juliana Freire, Raghu Ramakrishnan, Michael Stonebraker, Joseph M. Hellerstein
Pattern Functional Dependencies for Data Cleaning. Proc. VLDB Endow., 2020
Abdulhakim Ali Qahtan, Nan Tang, Mourad Ouzzani, Yang Cao, Michael Stonebraker
Poly'19 Workshop Summary: GDPR. SIGMOD Rec., 2020
Michael Stonebraker, Timothy G. Mattson, Tim Kraska, Vijay Gadepally
The Role of Latency and Task Complexity in Predicting Visual Search Behavior. IEEE Trans. Vis. Comput. Graph., 2020
Leilani Battle, R. Jordan Crouser, Audace Nakeshimana, Ananda Montoly, Remco Chang, Michael Stonebraker
Big Data Visualization and Analytics: Future Research Challenges and Emerging Applications. EDBT/ICDT Workshops, 2020
Gennady L. Andrienko, Natalia V. Andrienko, Steven Mark Drucker, Jean-Daniel Fekete, Danyel Fisher, Stratos Idreos, Tim Kraska, Guoliang Li, Kwan-Liu Ma, Jock D. Mackinlay, Antti Oulasvirta, Tobias Schreck, Heidrun Schumann, Michael Stonebraker, David Auber, Nikos Bikakis, Panos K. Chrysanthis, George Papastefanatos, Mohamed A. Sharaf
PushdownDB: Accelerating a DBMS Using S3 Computation. ICDE, 2020
Xiangyao Yu, Matt Youill, Matthew E. Woicik, Abdurrahman Ghanem, Marco Serafini, Ashraf Aboulnaga, Michael Stonebraker
The Next 5 Years: What Opportunities Should the Database Community Seize to Maximize its Impact? SIGMOD Conference, 2020
Magda Balazinska, Surajit Chaudhuri, Anastasia Ailamaki, Juliana Freire, Sailesh Krishnamurthy, Michael Stonebraker
PushdownDB: Accelerating a DBMS using S3 Computation. CoRR, 2020
Xiangyao Yu, Matt Youill, Matthew E. Woicik, Abdurrahman Ghanem, Marco Serafini, Ashraf Aboulnaga, Michael Stonebraker
Kyrix-S: Authoring Scalable Scatterplot Visualizations of Big Data. CoRR, 2020
Wenbo Tao, Xinli Hou, Adam Sah, Leilani Battle, Remco Chang, Michael Stonebraker
Context-Aware Parse Trees. CoRR, 2020
Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Paul Petersen, Jesmin Jahan Tithi, Tim Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich
MISIM: An End-to-End Neural Code Similarity System. CoRR, 2020
Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Nesime Tatbul, Jesmin Jahan Tithi, Paul Petersen, Timothy G. Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich
ARDA: Automatic Relational Data Augmentation for Machine Learning. Proc. VLDB Endow., 2020
Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. Proc. VLDB Endow., 2020
Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska
Benchmarking Learned Indexes. Proc. VLDB Endow., 2020
Ryan Marcus, Andreas Kipf, Alexander van Renen, Mihail Stoian, Sanchit Misra, Alfons Kemper, Thomas Neumann, Tim Kraska
Automated Data Slicing for Model Validation: A Big Data - AI Integration Approach. IEEE Trans. Knowl. Data Eng., 2020
Yeounoh Chung, Tim Kraska, Neoklis Polyzotis, Ki Hyun Tae, Steven Euijong Whang
Fast Mapping onto Census Blocks. HPEC, 2020
Jeremy Kepner, Andreas Kipf, Darren Engwirda, Navin Vembar, Michael Jones, Lauren Milechin, Vijay Gadepally, Chris Hill, Tim Kraska, William Arcand, David Bestor, William Bergeron, Chansup Byun, Matthew Hubbell, Michael Houle, Andrew C. Kirby, Anna Klein, Julie Mullen, Andrew Prout, Albert Reuther, Antonio Rosa, Sid Samsi, Charles Yee, Peter Michaleas
Getting Swole: Generating Access-Aware Code with Predicate Pullups. ICDE, 2020
Andrew Crotty, Alex Galakatos, Tim Kraska
Cost-Guided Cardinality Estimation: Focus Where it Matters. ICDE Workshops, 2020
Parimarjan Negi, Ryan Marcus, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh
Learned garbage collection. MAPL@PLDI, 2020
Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska
ALEX: An Updatable Adaptive Learned Index. SIGMOD Conference, 2020
Jialin Ding, Umar Farooq Minhas, Jia Yu, Chi Wang, Jaeyoung Do, Yinan Li, Hantian Zhang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David B. Lomet, Tim Kraska
IDEBench: A Benchmark for Interactive Data Exploration. SIGMOD Conference, 2020
Philipp Eichmann, Emanuel Zgraggen, Carsten Binnig, Tim Kraska
DB4ML - An In-Memory Database Kernel with Machine Learning Support. SIGMOD Conference, 2020
Matthias Jasny, Tobias Ziegler, Tim Kraska, Uwe Röhm, Carsten Binnig
RadixSpline: a single-pass learned index. aiDM@SIGMOD, 2020
Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann
The Case for a Learned Sorting Algorithm. SIGMOD Conference, 2020
Ani Kristo, Kapil Vaidya, Ugur Çetintemel, Sanchit Misra, Tim Kraska
CDFShop: Exploring and Optimizing Learned Index Structures. SIGMOD Conference, 2020
Ryan Marcus, Emily Zhang, Tim Kraska
Learning Multi-Dimensional Indexes. SIGMOD Conference, 2020
Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska
Chiller: Contention-centric Transaction Execution and Data Partitioning for Modern Networks. SIGMOD Conference, 2020
Erfan Zamanian, Julian Shun, Carsten Binnig, Tim Kraska
ARDA: Automatic Relational Data Augmentation for Machine Learning. CoRR, 2020
Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger
Bao: Learning to Steer Query Optimizers. CoRR, 2020
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska
Learned Garbage Collection. CoRR, 2020
Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska
RadixSpline: A Single-Pass Learned Index. CoRR, 2020
Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann
Fast Mapping onto Census Blocks. CoRR, 2020
Jeremy Kepner, Darren Engwirda, Vijay Gadepally, Chris Hill, Tim Kraska, Michael Jones, Andreas Kipf, Lauren Milechin, Navin Vembar
Partitioned Learned Bloom Filter. CoRR, 2020
Kapil Vaidya, Eric Knorr, Tim Kraska, Michael Mitzenmacher
Benchmarking Learned Indexes. CoRR, 2020
Ryan Marcus, Andreas Kipf, Alexander van Renen, Mihail Stoian, Sanchit Misra, Alfons Kemper, Thomas Neumann, Tim Kraska
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. CoRR, 2020
Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska
Cortex: Harnessing Correlations to Boost Query Performance. CoRR, 2020
Vikram Nathan, Jialin Ding, Tim Kraska, Mohammad Alizadeh
Learned Indexes for a Google-scale Disk-based Database. CoRR, 2020
Hussam Abu-Libdeh, Deniz Altinbüken, Alex Beutel, Ed H. Chi, Lyric Doshi, Tim Kraska, Xiaozhou Li, Andy Ly, Christopher Olston
Towards Multiverse Databases. HotOS, 2019
Alana Marzoev, Lara Timbó Araújo, Malte Schwarzkopf, Samyukta Yagati, Eddie Kohler, Robert Tappan Morris, M. Frans Kaashoek, Sam Madden
Smile: A System to Support Machine Learning on EEG Data at Scale. Proc. VLDB Endow., 2019
Lei Cao, Wenbo Tao, Sungtae An, Jing Jin, Yizhou Yan, Xiaoyu Liu, Wendong Ge, Adam Sah, Leilani Battle, Jimeng Sun, Remco Chang, M. Brandon Westover, Samuel Madden, Michael Stonebraker
Efficient Discovery of Sequence Outlier Patterns. Proc. VLDB Endow., 2019
Lei Cao, Yizhou Yan, Samuel Madden, Elke A. Rundensteiner, Mathan Gopalsamy
STAR: Scaling Transactions through Asymmetric Replication. Proc. VLDB Endow., 2019
Yi Lu, Xiangyao Yu, Samuel Madden
Data Civilizer 2.0: A Holistic Framework for Data Preparation and Analytics. Proc. VLDB Endow., 2019
El Kindi Rezig, Lei Cao, Michael Stonebraker, Giovanni Simonini, Wenbo Tao, Samuel Madden, Mourad Ouzzani, Nan Tang, Ahmed K. Elmagarmid
SageDB: A Learned Database System. CIDR, 2019
Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan
Scalable Kernel Density Estimation-based Local Outlier Detection over Large Data Streams. EDBT, 2019
Xiao Qin, Lei Cao, Elke A. Rundensteiner, Samuel Madden
Unsupervised String Transformation Learning for Entity Consolidation. ICDE, 2019
Dong Deng, Wenbo Tao, Ziawasch Abedjan, Ahmed K. Elmagarmid, Ihab F. Ilyas, Guoliang Li, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang
Lazo: A Cardinality-Based Method for Coupled Estimation of Jaccard Similarity and Containment. ICDE, 2019
Raul Castro Fernandez, Jisoo Min, Demitri Nava, Samuel Madden
Termite: a system for tunneling through heterogeneous data. aiDM@SIGMOD, 2019
Raul Castro Fernandez, Samuel Madden
Raha: A Configuration-Free Error Detection System. SIGMOD Conference, 2019
Mohammad Mahdavi, Ziawasch Abedjan, Raul Castro Fernandez, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang
OLTP through the looking glass, and what we found there. Making Databases Work, 2019
Stavros Harizopoulos, Daniel J. Abadi, Samuel Madden, Michael Stonebraker
Make it happen: the life of Michael Stonebraker. Making Databases Work, 2019
Samuel Madden 0001
Research contributions of Mike Stonebraker: an overview. Making Databases Work, 2019
Samuel Madden 0001
C-store: a column-oriented DBMS. Making Databases Work, 2019
Mike Stonebraker, Daniel J. Abadi, Adam Batkin, Xuedong Chen, Mitch Cherniack, Miguel Ferreira, Edmond Lau, Amerson Lin, Sam Madden, Elizabeth J. O'Neil, Patrick E. O'Neil, Alex Rasin, Nga Tran, Stan Zdonik
The end of an architectural era: it's time for a complete rewrite. Making Databases Work, 2019
Michael Stonebraker, Samuel Madden, Daniel J. Abadi, Stavros Harizopoulos, Nabil Hachem, Pat Helland
SCAR: Strong Consistency using Asynchronous Replication with Minimal Coordination. CoRR, 2019
Yi Lu, Xiangyao Yu, Samuel Madden
Deductive Optimization of Relational Data Storage. CoRR, 2019
John K. Feser, Samuel Madden, Nan Tang, Armando Solar-Lezama
Termite: A System for Tunneling Through Heterogeneous Data. CoRR, 2019
Raul Castro Fernandez, Samuel Madden
SysML: The New Frontier of Machine Learning Systems. CoRR, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan R. Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
Kaskade: Graph Views for Efficient Graph Analytics. CoRR, 2019
Joana M. F. da Trindade, Konstantinos Karanasos, Carlo Curino, Samuel Madden, Julian Shun
Technical Report: Optimizing Human Involvement for Entity Matching and Consolidation. CoRR, 2019
Ji Sun, Dong Deng, Ihab F. Ilyas, Guoliang Li, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang
Machine-Assisted Map Editing. CoRR, 2019
Favyen Bastani, Songtao He, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden
Inferring and Improving Street Maps with Data-Driven Automation. CoRR, 2019
Favyen Bastani, Songtao He, Satvat Jagwani, Edward Park, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden, Mohammad Amin Sadeghi
Starling: A Scalable Query Engine on Cloud Function Services. CoRR, 2019
Matthew Perron, Raul Castro Fernandez, David J. DeWitt, Samuel Madden
Dataset-On-Demand: Automatic View Search and Presentation for Data Discovery. CoRR, 2019
Raul Castro Fernandez, Nan Tang, Mourad Ouzzani, Michael Stonebraker, Samuel Madden
RoadTagger: Robust Road Attribute Inference with Graph Neural Networks. CoRR, 2019
Songtao He, Favyen Bastani, Satvat Jagwani, Edward Park, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Samuel Madden, Mohammad Amin Sadeghi
Context-specific Language Modeling for Human Trafficking Detection from Online Advertisements. ACL, 2019
Saeideh Shahrokh Esfahani, Michael J. Cafarella, Maziyar Baran Pouyan, Gregory J. DeAngelo, Elena Eneva, Andy E. Fano
Demonstration of a Multiresolution Schema Mapping System. CIDR, 2019
Zhongjun Jin, Christopher Baik, Michael J. Cafarella, H. V. Jagadish, Yuze Lou
CLX: Towards verifiable PBE data transformation. EDBT, 2019
Zhongjun Jin, Michael J. Cafarella, H. V. Jagadish, Sean Kandel, Michael Minar, Joseph M. Hellerstein
You can't debug what you can't see: Expanding observability with the OmniTable. HotOS, 2019
Andrew Quinn, Jason Flinn, Michael J. Cafarella
Physical Representation-Based Predicate Optimization for a Visual Analytics Database. ICDE, 2019
Michael R. Anderson, Michael J. Cafarella, Germán Ros, Thomas F. Wenisch
Knowledge Graph Programming with a Human-in-the-Loop: Preliminary Results. HILDA@SIGMOD, 2019
Yuze Lou, Mahfus Uddin, Nathaniel Brown, Michael J. Cafarella
The Seattle Report on Database Research. SIGMOD Rec., 2019
Daniel Abadi, Anastasia Ailamaki, David G. Andersen, Peter Bailis, Magdalena Balazinska, Philip A. Bernstein, Peter A. Boncz, Surajit Chaudhuri, Alvin Cheung, AnHai Doan, Luna Dong, Michael J. Franklin, Juliana Freire, Alon Y. Halevy, Joseph M. Hellerstein, Stratos Idreos, Donald Kossmann, Tim Kraska, Sailesh Krishnamurthy, Volker Markl, Sergey Melnik, Tova Milo, C. Mohan, Thomas Neumann, Beng Chin Ooi, Fatma Ozcan, Jignesh M. Patel, Andrew Pavlo, Raluca A. Popa, Raghu Ramakrishnan, Christopher Ré, Michael Stonebraker, Dan Suciu
Kyrix: Interactive Pan/Zoom Visualizations at Scale. Comput. Graph. Forum, 2019
Wenbo Tao, Xiaoyu Liu, Yedi Wang, Leilani Battle, Çagatay Demiralp, Remco Chang, Michael Stonebraker
Machine Learning and Big Data: What is Important? IEEE Data Eng. Bull., 2019
Michael Stonebraker, El Kindi Rezig
Choosing A Cloud DBMS: Architectures and Tradeoffs. Proc. VLDB Endow., 2019
Junjay Tan, Thanaa M. Ghanem, Matthew Perron, Xiangyao Yu, Michael Stonebraker, David J. DeWitt, Marco Serafini, Ashraf Aboulnaga, Tim Kraska
Rethinking Database High Availability with RDMA Networks. Proc. VLDB Endow., 2019
Erfan Zamanian, Xiangyao Yu, Michael Stonebraker, Tim Kraska
Kyrix: Interactive Visual Data Exploration at Scale. CIDR, 2019
Wenbo Tao, Xiaoyu Liu, Çagatay Demiralp, Remco Chang, Michael Stonebraker
How I Learned to Stop Worrying and Love Re-optimization. ICDE, 2019
Matthew Perron, Zeyuan Shang, Tim Kraska, Michael Stonebraker
ANMAT: Automatic Knowledge Discovery and Error Detection through Pattern Functional Dependencies. SIGMOD Conference, 2019
Abdulhakim Ali Qahtan, Nan Tang, Mourad Ouzzani, Yang Cao, Michael Stonebraker
Towards an End-to-End Human-Centric Data Cleaning Framework. HILDA@SIGMOD, 2019
El Kindi Rezig, Mourad Ouzzani, Ahmed K. Elmagarmid, Walid G. Aref, Michael Stonebraker
SchengenDB: A Data Protection Database Proposal. Poly/DMAH@VLDB, 2019
Tim Kraska, Michael Stonebraker, Michael L. Brodie, Sacha Servan-Schreiber, Daniel J. Weitzner
WIP - SKOD: A Framework for Situational Knowledge on Demand. Poly/DMAH@VLDB, 2019
Servio Palacios, K. M. A. Solaiman, Pelin Angin, Alina Nesen, Bharat K. Bhargava, Zachary Collins, Aaron Sipser, Michael Stonebraker, James MacDonald
The design and implementation of INGRES. Making Databases Work, 2019
Michael Stonebraker, Eugene Wong, Peter Kreps, Gerald Held
The land sharks are on the squawk box. Making Databases Work, 2019
Michael Stonebraker
How to start a company in five (not so) easy steps. Making Databases Work, 2019
Michael Stonebraker
Where good ideas come from and how to exploit them. Making Databases Work, 2019
Michael Stonebraker
Where we have failed. Making Databases Work, 2019
Michael Stonebraker
"One size fits all": an idea whose time has come and gone. Making Databases Work, 2019
Michael Stonebraker, Ugur Çetintemel
The implementation of POSTGRES. Making Databases Work, 2019
Michael Stonebraker, Lawrence A. Rowe, Michael Hirohama
Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB 2018 Workshops, Poly and DMAH, Rio de Janeiro, Brazil, August 31, 2018, Revised Selected Papers Poly/DMAH@VLDBLecture Notes in Computer Science, 2019
Vijay Gadepally, Timothy G. Mattson, Michael Stonebraker, Fusheng Wang, Gang Luo, George Teodoro
Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB 2019 Workshops, Poly and DMAH, Los Angeles, CA, USA, August 30, 2019, Revised Selected Papers Poly/DMAH@VLDBLecture Notes in Computer Science, 2019
Vijay Gadepally, Timothy G. Mattson, Michael Stonebraker, Fusheng Wang, Gang Luo, Yanhui Laing, Alevtina Dubovitskaya
How I Learned to Stop Worrying and Love Re-optimization. CoRR, 2019
Matthew Perron, Zeyuan Shang, Tim Kraska, Michael Stonebraker
Kyrix: Interactive Visual Data Exploration at Scale. CoRR, 2019
Wenbo Tao, Xiaoyu Liu, Çagatay Demiralp, Remco Chang, Michael Stonebraker
Mike Stonebraker speaks out: an interview. Making Databases Work, 2019
Marianne Winslett
Neo: A Learned Query Optimizer. Proc. VLDB Endow., 2019
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul
Tuplex: Robust, Efficient Analytics When Python Rules. Proc. VLDB Endow., 2019
Leonhard F. Spiegelberg, Tim Kraska
The SIGMOD 2019 Research Track Reviewing System. SIGMOD Rec., 2019
Anastasia Ailamaki, Periklis Chrysogelos, Amol Deshpande, Tim Kraska
VizML: A Machine Learning Approach to Visualization Recommendation. CHI, 2019
Kevin Zeng Hu, Michiel A. Bakker, Stephen Li, Tim Kraska, César A. Hidalgo
VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository. CHI, 2019
Kevin Zeng Hu, Snehalkumar (Neil) S. Gaikwad, Madelon Hulsebos, Michiel A. Bakker, Emanuel Zgraggen, César A. Hidalgo, Tim Kraska, Guoliang Li, Arvind Satyanarayan, Çagatay Demiralp
VizCertify: A Framework for Secure Visual Data Exploration. DSAA, 2019
Lorenzo De Stefani, Leonhard F. Spiegelberg, Eli Upfal, Tim Kraska
Slice Finder: Automated Data Slicing for Model Validation. ICDE, 2019
Yeounoh Chung, Tim Kraska, Neoklis Polyzotis, Ki Hyun Tae, Steven Euijong Whang
Sherlock: A Deep Learning Approach to Semantic Data Type Detection. KDD, 2019
Madelon Hulsebos, Kevin Zeng Hu, Michiel A. Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çagatay Demiralp, César A. Hidalgo
Park: An Open Platform for Learning-Augmented Computer Systems. NeurIPS, 2019
Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, Ravichandra Addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh Bojja Venkatakrishnan, Wei-Hung Weng, Song Han, Tim Kraska, Mohammad Alizadeh
Designing Distributed Tree-based Index Structures for Fast RDMA-capable Networks. SIGMOD Conference, 2019
Tobias Ziegler, Sumukha Tumkur Vani, Carsten Binnig, Rodrigo Fonseca, Tim Kraska
FITing-Tree: A Data-aware Index Structure. SIGMOD Conference, 2019
Alex Galakatos, Michael Markovitch, Carsten Binnig, Rodrigo Fonseca, Tim Kraska
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems. SIGMOD Conference, 2019
Stratos Idreos, Tim Kraska
Democratizing Data Science through Interactive Curation of ML Pipelines. SIGMOD Conference, 2019
Zeyuan Shang, Emanuel Zgraggen, Benedetto Buratti, Ferdinand Kossmann, Philipp Eichmann, Yeounoh Chung, Carsten Binnig, Eli Upfal, Tim Kraska
Proceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019, Amsterdam, The Netherlands, June 30 - July 5, 2019. SIGMOD Conference, 2019
Peter A. Boncz, Stefan Manegold, Anastasia Ailamaki, Amol Deshpande, Tim Kraska
Custodes: Auditable Hypothesis Testing. CoRR, 2019
Sacha Servan-Schreiber, Olga Ohrimenko, Tim Kraska, Emanuel Zgraggen
Neo: A Learned Query Optimizer. CoRR, 2019
Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul
VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository. CoRR, 2019
Kevin Zeng Hu, Snehalkumar (Neil) S. Gaikwad, Michiel A. Bakker, Madelon Hulsebos, Emanuel Zgraggen, César A. Hidalgo, Tim Kraska, Guoliang Li, Arvind Satyanarayan, Çagatay Demiralp
Sherlock: A Deep Learning Approach to Semantic Data Type Detection. CoRR, 2019
Madelon Hulsebos, Kevin Zeng Hu, Michiel A. Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çagatay Demiralp, César A. Hidalgo
LISA: Towards Learned DNA Sequence Search. CoRR, 2019
Darryl Ho, Jialin Ding, Sanchit Misra, Nesime Tatbul, Vikram Nathan, Md. Vasimuddin, Tim Kraska
SOSD: A Benchmark for Learned Indexes. CoRR, 2019
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