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ORCIDTim Kraska
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- affiliation: MIT Cambridge, MA, USA
- affiliation: Brown University, Providence, RI, USA
- affiliation: ETH Zurich, Switzerland
- award: VLDB Early Career Research Contribution Award 2018
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2020 – today
- 2024
[j67]Geoffrey X. Yu, Ziniu Wu, Ferdinand Kossmann, Tianyu Li, Markos Markakis, Amadou Latyr Ngom, Samuel Madden, Tim Kraska:
Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD. Proc. VLDB Endow. 17(11): 3629-3643 (2024)- [j66]Alexander van Renen, Dominik Horn, Pascal Pfeil, Kapil Vaidya, Wenjian Dong, Murali Narayanaswamy, Zhengchun Liu, Gaurav Saxena, Andreas Kipf, Tim Kraska:
Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet. Proc. VLDB Endow. 17(11): 3694-3706 (2024) - [j65]Bradley Barnhart, Marc Brooker, Daniil Chinenkov, Tony Hooper, Jihoun Im, Prakash Chandra Jha, Tim Kraska, Ashok Kurakula, Alexey Kuznetsov, Grant Mcalister, Arjun Muthukrishnan, Aravinthan Narayanan, Douglas Terry, Bhuvan Urgaonkar, Jiaming Yan:
Resource Management in Aurora Serverless. Proc. VLDB Endow. 17(12): 4038-4050 (2024) - [j64]Samuel Madden, Michael J. Cafarella, Michael J. Franklin, Tim Kraska:
Databases Unbound: Querying All of the World's Bytes with AI. Proc. VLDB Endow. 17(12): 4546-4554 (2024) - [c101]Amadou Latyr Ngom
, Tim Kraska:
Mallet: SQL Dialect Translation with LLM Rule Generation. aiDM@SIGMOD 2024: 3:1-3:5 - [c100]Vikramank Y. Singh, Kapil Vaidya, Vinayshekhar Bannihatti Kumar, Sopan Khosla, Balakrishnan Narayanaswamy, Rashmi Gangadharaiah, Tim Kraska:
Panda: Performance Debugging for Databases using LLM Agents. CIDR 2024 - [c99]Jialin Ding, Matt Abrams, Sanghita Bandyopadhyay, Luciano Di Palma, Yanzhu Ji, Davide Pagano, Gopal Paliwal, Panos Parchas, Pascal Pfeil, Orestis Polychroniou, Gaurav Saxena, Aamer Shah, Amina Voloder, Sherry Xiao, Davis Zhang, Tim Kraska:
Automated Multidimensional Data Layouts in Amazon Redshift. SIGMOD Conference Companion 2024: 55-67 - [c98]Vikram Nathan, Vikramank Y. Singh, Zhengchun Liu, Mohammad Rahman, Andreas Kipf, Dominik Horn, Davide Pagano, Gaurav Saxena, Balakrishnan Narayanaswamy, Tim Kraska:
Intelligent Scaling in Amazon Redshift. SIGMOD Conference Companion 2024: 269-279 - [c97]Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska:
Stage: Query Execution Time Prediction in Amazon Redshift. SIGMOD Conference Companion 2024: 280-294 - [c96]Tobias Schmidt, Andreas Kipf, Dominik Horn, Gaurav Saxena, Tim Kraska:
Predicate Caching: Query-Driven Secondary Indexing for Cloud Data Warehouses. SIGMOD Conference Companion 2024: 347-359 - [i69]Ziniu Wu, Ryan Marcus, Zhengchun Liu, Parimarjan Negi, Vikram Nathan, Pascal Pfeil, Gaurav Saxena, Mohammad Rahman, Balakrishnan Narayanaswamy, Tim Kraska:
Stage: Query Execution Time Prediction in Amazon Redshift. CoRR abs/2403.02286 (2024) - [i68]Wenqi Jiang, Shuai Zhang, Boran Han, Jie Wang, Bernie Wang, Tim Kraska:
PipeRAG: Fast Retrieval-Augmented Generation via Algorithm-System Co-design. CoRR abs/2403.05676 (2024) - [i67]Chunwei Liu, Matthew Russo, Michael J. Cafarella, Lei Cao, Peter Baile Chen, Zui Chen, Michael J. Franklin, Tim Kraska, Samuel Madden, Gerardo Vitagliano:
A Declarative System for Optimizing AI Workloads. CoRR abs/2405.14696 (2024) - [i66]Geoffrey X. Yu, Ziniu Wu, Ferdi Kossmann, Tianyu Li, Markos Markakis, Amadou Ngom, Samuel Madden, Tim Kraska:
Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD - Extended Version. CoRR abs/2407.15363 (2024) - 2023
- [j63]Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden:
FactorJoin: A New Cardinality Estimation Framework for Join Queries. Proc. ACM Manag. Data 1(1): 41:1-41:27 (2023) - [j62]Parimarjan Negi, Ziniu Wu, Andreas Kipf, Nesime Tatbul, Ryan Marcus, Sam Madden, Tim Kraska, Mohammad Alizadeh:
Robust Query Driven Cardinality Estimation under Changing Workloads. Proc. VLDB Endow. 16(6): 1520-1533 (2023) - [j61]Ibrahim Sabek, Tim Kraska:
The Case for Learned In-Memory Joins. Proc. VLDB Endow. 16(7): 1749-1762 (2023) - [j60]Ferdinand Kossmann, Ziniu Wu, Eugenie Lai, Nesime Tatbul, Lei Cao, Tim Kraska, Sam Madden:
Extract-Transform-Load for Video Streams. Proc. VLDB Endow. 16(9): 2302-2315 (2023) - [j59]Tim Kraska, Tianyu Li, Samuel Madden, Markos Markakis, Amadou Ngom, Ziniu Wu, Geoffrey X. Yu:
Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes. Proc. VLDB Endow. 16(11): 3293-3301 (2023) - [j58]Tim Kraska:
Technical Perspective for Sherman: A Write-Optimized Distributed B+Tree Index on Disaggregated Memory. SIGMOD Rec. 52(1): 44 (2023) - [c95]Parimarjan Negi, Laurent Bindschaedler, Mohammad Alizadeh, Tim Kraska, Jyoti Leeka, Anja Gruenheid, Matteo Interlandi:
Unshackling Database Benchmarking from Synthetic Workloads. ICDE 2023: 3659-3662 - [c94]Gaurav Saxena, Mohammad Rahman, Naresh Chainani, Chunbin Lin, George Caragea, Fahim Chowdhury, Ryan Marcus, Tim Kraska, Ippokratis Pandis, Balakrishnan (Murali) Narayanaswamy:
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift. SIGMOD Conference Companion 2023: 225-237 - [c93]Xi Lyu, Andreas Kipf, Pascal Pfeil, Dominik Horn, Jana Giceva, Tim Kraska:
CorBit: Leveraging Correlations for Compressing Bitmap Indexes. VLDB Workshops 2023 - [c92]Leonhard F. Spiegelberg, Tim Kraska, Malte Schwarzkopf:
Hyperspecialized Compilation for Serverless Data Analytics. VLDB Workshops 2023 - [i65]Ani Kristo, Tim Kraska:
Parallel External Sorting of ASCII Records Using Learned Models. CoRR abs/2305.05671 (2023) - [i64]Zui Chen, Lei Cao, Sam Madden, Ju Fan, Nan Tang, Zihui Gu, Zeyuan Shang, Chunwei Liu, Michael J. Cafarella, Tim Kraska:
SEED: Simple, Efficient, and Effective Data Management via Large Language Models. CoRR abs/2310.00749 (2023) - [i63]Ferdinand Kossmann, Ziniu Wu, Eugenie Lai, Nesime Tatbul, Lei Cao, Tim Kraska, Samuel Madden:
Extract-Transform-Load for Video Streams. CoRR abs/2310.04830 (2023) - 2022
- [j57]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:
The Seattle report on database research. Commun. ACM 65(8): 72-79 (2022) - [j56]Kapil Vaidya, Tim Kraska, Subarna Chatterjee, Eric R. Knorr, Michael Mitzenmacher, Stratos Idreos:
SNARF: A Learning-Enhanced Range Filter. Proc. VLDB Endow. 15(8): 1632-1644 (2022) - [j55]Jialin Ding, Ryan Marcus, Andreas Kipf, Vikram Nathan, Aniruddha Nrusimha, Kapil Vaidya, Alexander van Renen, Tim Kraska:
SageDB: An Instance-Optimized Data Analytics System. Proc. VLDB Endow. 15(13): 4062-4078 (2022) - [j54]Geoffrey X. Yu, Markos Markakis, Andreas Kipf, Per-Åke Larson, Umar Farooq Minhas, Tim Kraska:
TreeLine: An Update-In-Place Key-Value Store for Modern Storage. Proc. VLDB Endow. 16(1): 99-112 (2022) - [j53]Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Michael Mitzenmacher, Tim Kraska:
Can Learned Models Replace Hash Functions? Proc. VLDB Endow. 16(3): 532-545 (2022) - [j52]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska:
Bao: Making Learned Query Optimization Practical. SIGMOD Rec. 51(1): 6-13 (2022) - [c91]Samuel Madden, Jialin Ding, Tim Kraska, Sivaprasad Sudhir, David E. Cohen, Timothy G. Mattson, Nesime Tatbul:
Self-Organizing Data Containers. CIDR 2022 - [c90]Oscar R. Moll, Favyen Bastani, Sam Madden, Mike Stonebraker, Vijay Gadepally, Tim Kraska:
ExSample: Efficient Searches on Video Repositories through Adaptive Sampling. ICDE 2022: 2956-2968 - [c89]Oscar R. Moll, Favyen Bastani, Sam Madden, Mike Stonebraker, Vijay Gadepally, Tim Kraska:
ExSample: Efficient Searches on Video Repositories through Adaptive Sampling. ICDE 2022: 3065-3077 - [c88]Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska:
LSI: a learned secondary index structure. aiDM@SIGMOD 2022: 4:1-4:5 - [c87]Ibrahim Sabek, Tenzin Samten Ukyab, Tim Kraska:
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems. SIGMOD Conference 2022: 1228-1242 - [e5]El Kindi Rezig, Vijay Gadepally, Timothy G. Mattson, Michael Stonebraker, Tim Kraska, Jun Kong, Gang Luo, Dejun Teng, Fusheng Wang:
Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB Workshops, Poly 2022 and DMAH 2022, Virtual Event, September 9, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13814, Springer 2022, ISBN 978-3-031-23904-5 [contents] - [i62]Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska:
LSI: A Learned Secondary Index Structure. CoRR abs/2205.05769 (2022) - [i61]Ziniu Wu, Parimarjan Negi, Mohammad Alizadeh, Tim Kraska, Samuel Madden:
FactorJoin: A New Cardinality Estimation Framework for Join Queries. CoRR abs/2212.05526 (2022) - 2021
- [j51]Tim Kraska, Umar Farooq Minhas, Thomas Neumann, Olga Papaemmanouil, Jignesh M. Patel, Christopher Ré, Michael Stonebraker:
ML-In-Databases: Assessment and Prognosis. IEEE Data Eng. Bull. 44(1): 3-10 (2021) - [j50]Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh:
Flow-Loss: Learning Cardinality Estimates That Matter. Proc. VLDB Endow. 14(11): 2019-2032 (2021) - [j49]Zeyuan Shang, Emanuel Zgraggen, Benedetto Buratti, Philipp Eichmann, Navid Karimeddiny, Charlie Meyer, Wesley Runnels, Tim Kraska:
Davos: A System for Interactive Data-Driven Decision Making. Proc. VLDB Endow. 14(12): 2893-2905 (2021) - [j48]Tim Kraska:
Towards instance-optimized data systems. Proc. VLDB Endow. 14(12): 3222-3232 (2021) - [j47]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:
DBOS: A DBMS-oriented Operating System. Proc. VLDB Endow. 15(1): 21-30 (2021) - [j46]Erfan Zamanian, Julian Shun, Carsten Binnig, Tim Kraska:
Chiller: Contention-centric Transaction Execution and Data Partitioning for Modern Networks. SIGMOD Rec. 50(1): 15-22 (2021) - [c86]Laurent Bindschaedler, Andreas Kipf, Tim Kraska, Ryan Marcus, Umar Farooq Minhas:
Towards a Benchmark for Learned Systems. ICDE Workshops 2021: 127-133 - [c85]Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska:
Partitioned Learned Bloom Filters. ICLR 2021 - [c84]Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska:
LEA: A Learned Encoding Advisor for Column Stores. aiDM@SIGMOD 2021: 32-35 - [c83]Jialin Ding, Umar Farooq Minhas, Badrish Chandramouli, Chi Wang, Yinan Li, Ying Li, Donald Kossmann, Johannes Gehrke, Tim Kraska:
Instance-Optimized Data Layouts for Cloud Analytics Workloads. SIGMOD Conference 2021: 418-431 - [c82]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska:
Bao: Making Learned Query Optimization Practical. SIGMOD Conference 2021: 1275-1288 - [c81]Leonhard F. Spiegelberg, Rahul Yesantharao, Malte Schwarzkopf, Tim Kraska:
Tuplex: Data Science in Python at Native Code Speed. SIGMOD Conference 2021: 1718-1731 - [c80]Parimarjan Negi, Matteo Interlandi, Ryan Marcus, Mohammad Alizadeh, Tim Kraska, Marc T. Friedman, Alekh Jindal:
Steering Query Optimizers: A Practical Take on Big Data Workloads. SIGMOD Conference 2021: 2557-2569 - [c79]Tim Kraska:
Living in a Candy Store - from being a PhD Student to Working as a Faculty Member on ML for Systems. PhD@VLDB 2021 - [e4]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 2020 and DMAH 2020, Virtual Event, August 31 and September 4, 2020, Revised Selected Papers. Lecture Notes in Computer Science 12633, Springer 2021, ISBN 978-3-030-71054-5 [contents] - [e3]El Kindi Rezig, 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. Lecture Notes in Computer Science 12921, Springer 2021, ISBN 978-3-030-93662-4 [contents] - [i60]Parimarjan Negi, Ryan Marcus, Andreas Kipf, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh:
Flow-Loss: Learning Cardinality Estimates That Matter. CoRR abs/2101.04964 (2021) - [i59]Songtao He, Favyen Bastani, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden:
TagMe: GPS-Assisted Automatic Object Annotation in Videos. CoRR abs/2103.13428 (2021) - [i58]Favyen Bastani, Songtao He, Ziwen Jiang, Osbert Bastani, Michael J. Cafarella, Tim Kraska, Sam Madden:
SkyQuery: An Aerial Drone Video Sensing Platform. CoRR abs/2103.14699 (2021) - [i57]Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska:
LEA: A Learned Encoding Advisor for Column Stores. CoRR abs/2105.08830 (2021) - [i56]Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Tim Kraska:
When Are Learned Models Better Than Hash Functions? CoRR abs/2107.01464 (2021) - [i55]Ani Kristo, Kapil Vaidya, Tim Kraska:
Defeating duplicates: A re-design of the LearnedSort algorithm. CoRR abs/2107.03290 (2021) - [i54]Mihail Stoian, Andreas Kipf, Ryan Marcus, Tim Kraska:
PLEX: Towards Practical Learned Indexing. CoRR abs/2108.05117 (2021) - [i53]Ibrahim Sabek, Tim Kraska:
The Case for Learned In-Memory Joins. CoRR abs/2111.08824 (2021) - [i52]Benjamin Spector, Andreas Kipf, Kapil Vaidya, Chi Wang, Umar Farooq Minhas, Tim Kraska:
Bounding the Last Mile: Efficient Learned String Indexing. CoRR abs/2111.14905 (2021) - 2020
- [j45]Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger:
ARDA: Automatic Relational Data Augmentation for Machine Learning. Proc. VLDB Endow. 13(9): 1373-1387 (2020) - [j44]Ryan Marcus, Andreas Kipf, Alexander van Renen, Mihail Stoian, Sanchit Misra, Alfons Kemper, Thomas Neumann, Tim Kraska:
Benchmarking Learned Indexes. Proc. VLDB Endow. 14(1): 1-13 (2020) - [j43]Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska:
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. Proc. VLDB Endow. 14(2): 74-86 (2020) - [j42]Michael Stonebraker, Timothy G. Mattson, Tim Kraska, Vijay Gadepally:
Poly'19 Workshop Summary: GDPR. SIGMOD Rec. 49(3): 55-58 (2020) - [j41]Yeounoh Chung, Tim Kraska, Neoklis Polyzotis, Ki Hyun Tae, Steven Euijong Whang:
Automated Data Slicing for Model Validation: A Big Data - AI Integration Approach. IEEE Trans. Knowl. Data Eng. 32(12): 2284-2296 (2020) - [c78]Michael J. Cafarella, David J. DeWitt, Vijay Gadepally, Jeremy Kepner, Christos Kozyrakis, Tim Kraska, Michael Stonebraker, Matei Zaharia:
A Polystore Based Database Operating System (DBOS). Poly/DMAH@VLDB 2020: 3-24 - [c77]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:
Big Data Visualization and Analytics: Future Research Challenges and Emerging Applications. EDBT/ICDT Workshops 2020 - [c76]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:
Fast Mapping onto Census Blocks. HPEC 2020: 1-8 - [c75]Parimarjan Negi, Ryan Marcus, Hongzi Mao, Nesime Tatbul, Tim Kraska, Mohammad Alizadeh:
Cost-Guided Cardinality Estimation: Focus Where it Matters. ICDE Workshops 2020: 154-157 - [c74]Andrew Crotty, Alex Galakatos, Tim Kraska:
Getting Swole: Generating Access-Aware Code with Predicate Pullups. ICDE 2020: 1273-1284 - [c73]Songtao He, Favyen Bastani, Arjun Balasingam, Karthik Gopalakrishnan, Ziwen Jiang, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden:
BeeCluster: drone orchestration via predictive optimization. MobiSys 2020: 299-311 - [c72]Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska:
Learned garbage collection. MAPL@PLDI 2020: 38-44 - [c71]Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann:
RadixSpline: a single-pass learned index. aiDM@SIGMOD 2020: 5:1-5:5 - [c70]Matthias Jasny, Tobias Ziegler, Tim Kraska, Uwe Röhm, Carsten Binnig:
DB4ML - An In-Memory Database Kernel with Machine Learning Support. SIGMOD Conference 2020: 159-173 - [c69]Erfan Zamanian, Julian Shun, Carsten Binnig, Tim Kraska:
Chiller: Contention-centric Transaction Execution and Data Partitioning for Modern Networks. SIGMOD Conference 2020: 511-526 - [c68]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:
ALEX: An Updatable Adaptive Learned Index. SIGMOD Conference 2020: 969-984 - [c67]Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska:
Learning Multi-Dimensional Indexes. SIGMOD Conference 2020: 985-1000 - [c66]Ani Kristo, Kapil Vaidya, Ugur Çetintemel, Sanchit Misra, Tim Kraska:
The Case for a Learned Sorting Algorithm. SIGMOD Conference 2020: 1001-1016 - [c65]Philipp Eichmann, Emanuel Zgraggen, Carsten Binnig, Tim Kraska:
IDEBench: A Benchmark for Interactive Data Exploration. SIGMOD Conference 2020: 1555-1569 - [c64]Favyen Bastani, Songtao He, Arjun Balasingam, Karthik Gopalakrishnan, Mohammad Alizadeh, Hari Balakrishnan, Michael J. Cafarella, Tim Kraska, Sam Madden:
MIRIS: Fast Object Track Queries in Video. SIGMOD Conference 2020: 1907-1921 - [c63]Ryan Marcus, Emily Zhang, Tim Kraska:
CDFShop: Exploring and Optimizing Learned Index Structures. SIGMOD Conference 2020: 2789-2792 - [i51]Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger:
ARDA: Automatic Relational Data Augmentation for Machine Learning. CoRR abs/2003.09758 (2020) - [i50]Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Paul Petersen, Jesmin Jahan Tithi, Tim Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich:
Context-Aware Parse Trees. CoRR abs/2003.11118 (2020) - [i49]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Nesime Tatbul, Mohammad Alizadeh, Tim Kraska:
Bao: Learning to Steer Query Optimizers. CoRR abs/2004.03814 (2020) - [i48]Lujing Cen, Ryan Marcus, Hongzi Mao, Justin Gottschlich, Mohammad Alizadeh, Tim Kraska:
Learned Garbage Collection. CoRR abs/2004.13301 (2020) - [i47]Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann:
RadixSpline: A Single-Pass Learned Index. CoRR abs/2004.14541 (2020) - [i46]Jeremy Kepner, Darren Engwirda, Vijay Gadepally, Chris Hill, Tim Kraska, Michael Jones, Andreas Kipf, Lauren Milechin, Navin Vembar:
Fast Mapping onto Census Blocks. CoRR abs/2005.03156 (2020) - [i45]Oscar R. Moll, Favyen Bastani, Sam Madden, Mike Stonebraker, Vijay Gadepally, Tim Kraska:
ExSample: Efficient Searches on Video Repositories through Adaptive Sampling. CoRR abs/2005.09141 (2020) - [i44]Kapil Vaidya, Eric Knorr, Tim Kraska, Michael Mitzenmacher:
Partitioned Learned Bloom Filter. CoRR abs/2006.03176 (2020) - [i43]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:
MISIM: An End-to-End Neural Code Similarity System. CoRR abs/2006.05265 (2020) - [i42]Ryan Marcus, Andreas Kipf, Alexander van Renen, Mihail Stoian, Sanchit Misra, Alfons Kemper, Thomas Neumann, Tim Kraska:
Benchmarking Learned Indexes. CoRR abs/2006.12804 (2020) - [i41]Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska:
Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. CoRR abs/2006.13282 (2020) - [i40]Michael J. Cafarella, David J. DeWitt, Vijay Gadepally, Jeremy Kepner, Christos Kozyrakis, Tim Kraska, Michael Stonebraker, Matei Zaharia:
DBOS: A Proposal for a Data-Centric Operating System. CoRR abs/2007.11112 (2020) - [i39]Vikram Nathan, Jialin Ding, Tim Kraska, Mohammad Alizadeh:
Cortex: Harnessing Correlations to Boost Query Performance. CoRR abs/2012.06683 (2020) - [i38]Hussam Abu-Libdeh, Deniz Altinbüken, Alex Beutel, Ed H. Chi, Lyric Doshi, Tim Kraska, Xiaozhou Li, Andy Ly, Christopher Olston:
Learned Indexes for a Google-scale Disk-based Database. CoRR abs/2012.12501 (2020)
2010 – 2019
- 2019
- [j40]Erfan Zamanian, Xiangyao Yu, Michael Stonebraker, Tim Kraska:
Rethinking Database High Availability with RDMA Networks. Proc. VLDB Endow. 12(11): 1637-1650 (2019) - [j39]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul:
Neo: A Learned Query Optimizer. Proc. VLDB Endow. 12(11): 1705-1718 (2019) - [j38]Leonhard F. Spiegelberg, Tim Kraska:
Tuplex: Robust, Efficient Analytics When Python Rules. Proc. VLDB Endow. 12(12): 1958-1961 (2019) - [j37]Junjay Tan, Thanaa M. Ghanem, Matthew Perron, Xiangyao Yu, Michael Stonebraker, David J. DeWitt, Marco Serafini, Ashraf Aboulnaga, Tim Kraska:
Choosing A Cloud DBMS: Architectures and Tradeoffs. Proc. VLDB Endow. 12(12): 2170-2182 (2019) - [j36]Anastasia Ailamaki, Periklis Chrysogelos, Amol Deshpande, Tim Kraska:
The SIGMOD 2019 Research Track Reviewing System. SIGMOD Rec. 48(2): 47-54 (2019) - [j35]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:
The Seattle Report on Database Research. SIGMOD Rec. 48(4): 44-53 (2019) - [c62]Kevin Zeng Hu, Michiel A. Bakker, Stephen Li, Tim Kraska, César A. Hidalgo:
VizML: A Machine Learning Approach to Visualization Recommendation. CHI 2019: 128 - [c61]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:
VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository. CHI 2019: 662 - [c60]Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan:
SageDB: A Learned Database System. CIDR 2019 - [c59]Lorenzo De Stefani, Leonhard F. Spiegelberg, Eli Upfal, Tim Kraska:
VizCertify: A Framework for Secure Visual Data Exploration. DSAA 2019: 241-251 - [c58]Yeounoh Chung, Tim Kraska, Neoklis Polyzotis, Ki Hyun Tae, Steven Euijong Whang:
Slice Finder: Automated Data Slicing for Model Validation. ICDE 2019: 1550-1553 - [c57]Matthew Perron, Zeyuan Shang, Tim Kraska, Michael Stonebraker:
How I Learned to Stop Worrying and Love Re-optimization. ICDE 2019: 1758-1761 - [c56]Madelon Hulsebos, Kevin Zeng Hu, Michiel A. Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çagatay Demiralp, César A. Hidalgo:
Sherlock: A Deep Learning Approach to Semantic Data Type Detection. KDD 2019: 1500-1508 - [c55]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:
Park: An Open Platform for Learning-Augmented Computer Systems. NeurIPS 2019: 2490-2502 - [c54]Tobias Ziegler, Sumukha Tumkur Vani, Carsten Binnig, Rodrigo Fonseca, Tim Kraska:
Designing Distributed Tree-based Index Structures for Fast RDMA-capable Networks. SIGMOD Conference 2019: 741-758 - [c53]Zeyuan Shang, Emanuel Zgraggen, Benedetto Buratti, Ferdinand Kossmann, Philipp Eichmann, Yeounoh Chung, Carsten Binnig, Eli Upfal, Tim Kraska:
Democratizing Data Science through Interactive Curation of ML Pipelines. SIGMOD Conference 2019: 1171-1188 - [c52]Alex Galakatos, Michael Markovitch, Carsten Binnig, Rodrigo Fonseca, Tim Kraska:
FITing-Tree: A Data-aware Index Structure. SIGMOD Conference 2019: 1189-1206 - [c51]Stratos Idreos, Tim Kraska:
From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems. SIGMOD Conference 2019: 2054-2059 - [c50]Tim Kraska, Michael Stonebraker, Michael L. Brodie, Sacha Servan-Schreiber, Daniel J. Weitzner:
SchengenDB: A Data Protection Database Proposal. Poly/DMAH@VLDB 2019: 24-38 - [e2]Peter A. Boncz, Stefan Manegold, Anastasia Ailamaki, Amol Deshpande, Tim Kraska:
Proceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019, Amsterdam, The Netherlands, June 30 - July 5, 2019. ACM 2019, ISBN 978-1-4503-5643-5 [contents] - [i37]Sacha Servan-Schreiber, Olga Ohrimenko, Tim Kraska, Emanuel Zgraggen:
Custodes: Auditable Hypothesis Testing. CoRR abs/1901.10875 (2019) - [i36]Matthew Perron, Zeyuan Shang, Tim Kraska, Michael Stonebraker:
How I Learned to Stop Worrying and Love Re-optimization. CoRR abs/1902.08291 (2019) - [i35]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 Randall 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:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i34]Ryan Marcus, Parimarjan Negi, Hongzi Mao, Chi Zhang, Mohammad Alizadeh, Tim Kraska, Olga Papaemmanouil, Nesime Tatbul:
Neo: A Learned Query Optimizer. CoRR abs/1904.03711 (2019) - [i33]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:
VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository. CoRR abs/1905.04616 (2019) - [i32]Madelon Hulsebos, Kevin Zeng Hu, Michiel A. Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çagatay Demiralp, César A. Hidalgo:
Sherlock: A Deep Learning Approach to Semantic Data Type Detection. CoRR abs/1905.10688 (2019) - [i31]Darryl Ho, Jialin Ding, Sanchit Misra, Nesime Tatbul, Vikram Nathan, Md. Vasimuddin, Tim Kraska:
LISA: Towards Learned DNA Sequence Search. CoRR abs/1910.04728 (2019) - [i30]Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann:
SOSD: A Benchmark for Learned Indexes. CoRR abs/1911.13014 (2019) - [i29]Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska:
Learning Multi-dimensional Indexes. CoRR abs/1912.01668 (2019) - 2018
- [j34]Yeounoh Chung, Sacha Servan-Schreiber, Emanuel Zgraggen, Tim Kraska:
Towards Quantifying Uncertainty in Data Analysis & Exploration. IEEE Data Eng. Bull. 41(3): 15-27 (2018) - [j33]Tim Kraska:
Northstar: An Interactive Data Science System. Proc. VLDB Endow. 11(12): 2150-2164 (2018) - [j32]Yeounoh Chung, Michael Lind Mortensen, Carsten Binnig, Tim Kraska:
Estimating the Impact of Unknown Unknowns on Aggregate Query Results. ACM Trans. Database Syst. 43(1): 3:1-3:37 (2018) - [c49]Emanuel Zgraggen, Zheguang Zhao, Robert C. Zeleznik, Tim Kraska:
Investigating the Effect of the Multiple Comparisons Problem in Visual Analysis. CHI 2018: 479 - [c48]Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu, Ang Li, Shuaiwen Leon Song, Zenglin Xu, Tim Kraska:
Superneurons: dynamic GPU memory management for training deep neural networks. PPoPP 2018: 41-53 - [c47]Carsten Binnig, Benedetto Buratti, Yeounoh Chung, Cyrus Cousins, Tim Kraska, Zeyuan Shang, Eli Upfal, Robert C. Zeleznik, Emanuel Zgraggen:
Towards Interactive Curation & Automatic Tuning of ML Pipelines. DEEM@SIGMOD 2018: 1:1-1:4 - [c46]Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis:
The Case for Learned Index Structures. SIGMOD Conference 2018: 489-504 - [c45]Xiangyao Yu, Vijay Gadepally, Stan Zdonik, Tim Kraska, Michael Stonebraker:
FastDAWG: Improving Data Migration in the BigDAWG Polystore System. Poly/DMAH@VLDB 2018: 3-15 - [r1]Alex Galakatos, Andrew Crotty, Tim Kraska:
Distributed Machine Learning. Encyclopedia of Database Systems (2nd ed.) 2018 - [i28]Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu, Ang Li, Shuaiwen Leon Song, Zenglin Xu, Tim Kraska:
SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks. CoRR abs/1801.04380 (2018) - [i27]Alex Galakatos, Michael Markovitch, Carsten Binnig, Rodrigo Fonseca, Tim Kraska:
A-Tree: A Bounded Approximate Index Structure. CoRR abs/1801.10207 (2018) - [i26]Philipp Eichmann, Carsten Binnig, Tim Kraska, Emanuel Zgraggen:
IDEBench: A Benchmark for Interactive Data Exploration. CoRR abs/1804.02593 (2018) - [i25]Guillaume Leclerc, Manasi Vartak, Raul Castro Fernandez, Tim Kraska, Samuel Madden:
Smallify: Learning Network Size while Training. CoRR abs/1806.03723 (2018) - [i24]Yeounoh Chung, Tim Kraska, Neoklis Polyzotis, Steven Euijong Whang:
Slice Finder: Automated Data Slicing for Model Validation. CoRR abs/1807.06068 (2018) - [i23]Kevin Zeng Hu, Michiel A. Bakker, Stephen Li, Tim Kraska, César A. Hidalgo:
VizML: A Machine Learning Approach to Visualization Recommendation. CoRR abs/1808.04819 (2018) - [i22]Yeounoh Chung, Peter J. Haas, Eli Upfal, Tim Kraska:
Unknown Examples & Machine Learning Model Generalization. CoRR abs/1808.08294 (2018) - [i21]Lorenzo De Stefani, Leonhard F. Spiegelberg, Tim Kraska, Eli Upfal:
VizRec: A framework for secure data exploration via visual representation. CoRR abs/1811.00602 (2018) - [i20]Erfan Zamanian, Julian Shun, Carsten Binnig, Tim Kraska:
Chiller: Contention-centric Transaction Execution and Data Partitioning for Fast Networks. CoRR abs/1811.12204 (2018) - 2017
- [j31]Tim Kraska:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 40(1): 2 (2017) - [j30]Abdallah Salama, Carsten Binnig, Tim Kraska, Ansgar Scherp, Tobias Ziegler:
Rethinking Distributed Query Execution on High-Speed Networks. IEEE Data Eng. Bull. 40(1): 27-37 (2017) - [j29]Tim Kraska:
Letter from the Special Issue Editor. IEEE Data Eng. Bull. 40(4): 2 (2017) - [j28]Erfan Zamanian, Carsten Binnig, Tim Kraska, Tim Harris:
The End of a Myth: Distributed Transaction Can Scale. Proc. VLDB Endow. 10(6): 685-696 (2017) - [j27]Yeounoh Chung, Sanjay Krishnan, Tim Kraska:
A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets. Proc. VLDB Endow. 10(10): 1094-1105 (2017) - [j26]Alex Galakatos, Andrew Crotty, Emanuel Zgraggen, Carsten Binnig, Tim Kraska:
Revisiting Reuse for Approximate Query Processing. Proc. VLDB Endow. 10(10): 1142-1153 (2017) - [j25]Emanuel Zgraggen, Alex Galakatos, Andrew Crotty, Jean-Daniel Fekete, Tim Kraska:
How Progressive Visualizations Affect Exploratory Analysis. IEEE Trans. Vis. Comput. Graph. 23(8): 1977-1987 (2017) - [c44]Carsten Binnig, Fuat Basik, Benedetto Buratti, Ugur Çetintemel, Yeounoh Chung, Andrew Crotty, Cyrus Cousins, Dylan Ebert, Philipp Eichmann, Alex Galakatos, Benjamin Hättasch, Amir Ilkhechi, Tim Kraska, Zeyuan Shang, Isabella Tromba, Arif Usta, Prasetya Ajie Utama, Eli Upfal, Linnan Wang, Nathaniel Weir, Robert C. Zeleznik, Emanuel Zgraggen:
Towards Interactive Data Exploration. BIRTE (Revised Selected Papers) 2017: 177-190 - [c43]Christoph Pinkel, Carsten Binnig, Ernesto Jiménez-Ruiz, Evgeny Kharlamov, Andriy Nikolov, Andreas Schwarte, Christian Heupel, Tim Kraska:
IncMap: A Journey towards Ontology-based Data Integration. BTW 2017: 145-164 - [c42]Tim Kraska, Elkhan Dadashov, Carsten Binnig:
Spotlytics: How to Use Cloud Market Places for Analytics? BTW 2017: 361-380 - [c41]Carsten Binnig, Lorenzo De Stefani, Tim Kraska, Eli Upfal, Emanuel Zgraggen, Zheguang Zhao:
Toward Sustainable Insights, or Why Polygamy is Bad for You. CIDR 2017 - [c40]Bill Howe, Michael J. Franklin, Laura M. Haas, Tim Kraska, Jeffrey D. Ullman:
Data Science Education: We're Missing the Boat, Again. ICDE 2017: 1473-1474 - [c39]Yue Guo, Carsten Binnig, Tim Kraska:
What you see is not what you get!: Detecting Simpson's Paradoxes during Data Exploration. HILDA@SIGMOD 2017: 2:1-2:5 - [c38]Tim Kraska:
Approximate Query Processing for Interactive Data Science. SIGMOD Conference 2017: 525 - [c37]Zheguang Zhao, Lorenzo De Stefani, Emanuel Zgraggen, Carsten Binnig, Eli Upfal, Tim Kraska:
Controlling False Discoveries During Interactive Data Exploration. SIGMOD Conference 2017: 527-540 - [c36]Kayhan Dursun, Carsten Binnig, Ugur Çetintemel, Tim Kraska:
Revisiting Reuse in Main Memory Database Systems. SIGMOD Conference 2017: 1275-1289 - [c35]Zheguang Zhao, Emanuel Zgraggen, Lorenzo De Stefani, Carsten Binnig, Eli Upfal, Tim Kraska:
Safe Visual Data Exploration. SIGMOD Conference 2017: 1671-1674 - [i19]Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis:
The Case for Learned Index Structures. CoRR abs/1712.01208 (2017) - 2016
- [j24]Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar:
Answering enumeration queries with the crowd. Commun. ACM 59(1): 118-127 (2016) - [j23]Philipp Eichmann, Emanuel Zgraggen, Zheguang Zhao, Carsten Binnig, Tim Kraska:
Towards a Benchmark for Interactive Data Exploration. IEEE Data Eng. Bull. 39(4): 50-61 (2016) - [j22]Carsten Binnig, Andrew Crotty, Alex Galakatos, Tim Kraska, Erfan Zamanian:
The End of Slow Networks: It's Time for a Redesign. Proc. VLDB Endow. 9(7): 528-539 (2016) - [c34]Michael J. Cafarella, Ihab F. Ilyas, Marcel Kornacker, Tim Kraska, Christopher Ré:
Dark Data: Are we solving the right problems? ICDE 2016: 1444-1445 - [c33]Muhammad El-Hindi, Zheguang Zhao, Carsten Binnig, Tim Kraska:
VisTrees: fast indexes for interactive data exploration. HILDA@SIGMOD 2016: 5 - [c32]Andrew Crotty, Alex Galakatos, Emanuel Zgraggen, Carsten Binnig, Tim Kraska:
The case for interactive data exploration accelerators (IDEAs). HILDA@SIGMOD 2016: 11 - [c31]Yeounoh Chung, Michael Lind Mortensen, Carsten Binnig, Tim Kraska:
Estimating the Impact of Unknown Unknowns on Aggregate Query Results. SIGMOD Conference 2016: 861-876 - [c30]Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska:
PrivateClean: Data Cleaning and Differential Privacy. SIGMOD Conference 2016: 937-951 - [c29]Gabriel Lyons, Vinh Tran, Carsten Binnig, Ugur Çetintemel, Tim Kraska:
Making the Case for Query-by-Voice with EchoQuery. SIGMOD Conference 2016: 2129-2132 - [i18]Erfan Zamanian, Carsten Binnig, Tim Kraska, Tim Harris:
The End of a Myth: Distributed Transactions Can Scale. CoRR abs/1607.00655 (2016) - [i17]Kayhan Dursun, Carsten Binnig, Ugur Çetintemel, Tim Kraska:
Revisiting Reuse in Main Memory Database Systems. CoRR abs/1608.05678 (2016) - [i16]Yeounoh Chung, Sanjay Krishnan, Tim Kraska:
A Data Quality Metric (DQM): How to Estimate The Number of Undetected Errors in Data Sets. CoRR abs/1611.04878 (2016) - [i15]Zheguang Zhao, Lorenzo De Stefani, Emanuel Zgraggen, Carsten Binnig, Eli Upfal, Tim Kraska:
Controlling False Discoveries During Interactive Data Exploration. CoRR abs/1612.01040 (2016) - 2015
- [j21]Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska, Tova Milo, Eugene Wu:
SampleClean: Fast and Reliable Analytics on Dirty Data. IEEE Data Eng. Bull. 38(3): 59-75 (2015) - [j20]Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska:
Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views. Proc. VLDB Endow. 8(12): 1370-1381 (2015) - [j19]Andrew Crotty, Alex Galakatos, Kayhan Dursun, Tim Kraska, Carsten Binnig, Ugur Çetintemel, Stan Zdonik:
An Architecture for Compiling UDF-centric Workflows. Proc. VLDB Endow. 8(12): 1466-1477 (2015) - [j18]Aaron J. Elmore, Jennie Duggan, Mike Stonebraker, Magdalena Balazinska, Ugur Çetintemel, Vijay Gadepally, Jeffrey Heer, Bill Howe, Jeremy Kepner, Tim Kraska, Samuel Madden, David Maier, Timothy G. Mattson, Stavros Papadopoulos, Jeff Parkhurst, Nesime Tatbul, Manasi Vartak, Stan Zdonik:
A Demonstration of the BigDAWG Polystore System. Proc. VLDB Endow. 8(12): 1908-1911 (2015) - [j17]Andrew Crotty, Alex Galakatos, Emanuel Zgraggen, Carsten Binnig, Tim Kraska:
Vizdom: Interactive Analytics through Pen and Touch. Proc. VLDB Endow. 8(12): 2024-2027 (2015) - [j16]John Meehan, Nesime Tatbul, Stan Zdonik, Cansu Aslantas, Ugur Çetintemel, Jiang Du, Tim Kraska, Samuel Madden, David Maier, Andrew Pavlo, Michael Stonebraker, Kristin Tufte, Hao Wang:
S-Store: Streaming Meets Transaction Processing. Proc. VLDB Endow. 8(13): 2134-2145 (2015) - [j15]Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar, Venketaram Ramachandran:
Crowdsourcing Enumeration Queries: Estimators and Interfaces. IEEE Trans. Knowl. Data Eng. 27(7): 1796-1809 (2015) - [c28]Andrew Crotty, Alex Galakatos, Kayhan Dursun, Tim Kraska, Ugur Çetintemel, Stanley B. Zdonik:
Tupleware: "Big" Data, Big Analytics, Small Clusters. CIDR 2015 - [c27]Evan Randall Sparks, Ameet Talwalkar, Daniel Haas, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
Automating model search for large scale machine learning. SoCC 2015: 368-380 - [c26]Dalia Kaulakiene, Christian Thomsen, Torben Bach Pedersen, Ugur Çetintemel, Tim Kraska:
SpotADAPT: Spot-Aware (re-)Deployment of Analytical Processing Tasks on Amazon EC2. DOLAP 2015: 59-68 - [c25]Christopher Ré, Divy Agrawal, Magdalena Balazinska, Michael J. Cafarella, Michael I. Jordan, Tim Kraska, Raghu Ramakrishnan:
Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype? SIGMOD Conference 2015: 283-284 - [c24]Abdallah Salama, Carsten Binnig, Tim Kraska, Erfan Zamanian:
Cost-based Fault-tolerance for Parallel Data Processing. SIGMOD Conference 2015: 285-297 - [e1]Irfan Ahmad, Tim Kraska:
7th USENIX Workshop on Hot Topics in Cloud Computing, HotCloud '15, Santa Clara, CA, USA, July 6-7, 2015. USENIX Association 2015 [contents] - [i14]Evan Randall Sparks, Ameet Talwalkar, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries. CoRR abs/1502.00068 (2015) - [i13]John Meehan, Nesime Tatbul, Stanley B. Zdonik, Cansu Aslantas, Ugur Çetintemel, Jiang Du, Tim Kraska, Samuel Madden, David Maier, Andrew Pavlo, Michael Stonebraker, Kristin Tufte, Hao Wang:
S-Store: Streaming Meets Transaction Processing. CoRR abs/1503.01143 (2015) - [i12]Carsten Binnig, Ugur Çetintemel, Andrew Crotty, Alex Galakatos, Tim Kraska, Erfan Zamanian, Stanley B. Zdonik:
The End of Slow Networks: It's Time for a Redesign. CoRR abs/1504.01048 (2015) - [i11]Yeounoh Chung, Michael Lind Mortensen, Carsten Binnig, Tim Kraska:
Estimating the Impact of Unknown Unknowns on Aggregate Query Results. CoRR abs/1507.05591 (2015) - [i10]Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska:
Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views. CoRR abs/1509.07454 (2015) - [i9]Anja Gruenheid, Besmira Nushi, Tim Kraska, Wolfgang Gatterbauer, Donald Kossmann:
Fault-Tolerant Entity Resolution with the Crowd. CoRR abs/1512.00537 (2015) - 2014
- [j14]Andrew Crotty, Alex Galakatos, Tim Kraska:
Tupleware: Distributed Machine Learning on Small Clusters. IEEE Data Eng. Bull. 37(3): 63-76 (2014) - [j13]Elkhan Dadashov, Ugur Çetintemel, Tim Kraska:
Putting Analytics on the Spot: Or How to Lower the Cost for Analytics. IEEE Internet Comput. 18(5): 70-73 (2014) - [j12]Ugur Çetintemel, Jiang Du, Tim Kraska, Samuel Madden, David Maier, John Meehan, Andrew Pavlo, Michael Stonebraker, Erik Sutherland, Nesime Tatbul, Kristin Tufte, Hao Wang, Stanley B. Zdonik:
S-Store: A Streaming NewSQL System for Big Velocity Applications. Proc. VLDB Endow. 7(13): 1633-1636 (2014) - [c23]Gene Pang, Tim Kraska, Michael J. Franklin, Alan D. Fekete:
PLANET: making progress with commit processing in unpredictable environments. SIGMOD Conference 2014: 3-14 - [c22]Jiannan Wang, Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Tim Kraska, Tova Milo:
A sample-and-clean framework for fast and accurate query processing on dirty data. SIGMOD Conference 2014: 469-480 - [c21]Bill Howe, Michael J. Franklin, Juliana Freire, James Frew, Tim Kraska, Raghu Ramakrishnan:
Should we all be teaching "intro to data science" instead of "intro to databases"? SIGMOD Conference 2014: 917-918 - [i8]Andrew Crotty, Alex Galakatos, Kayhan Dursun, Tim Kraska, Ugur Çetintemel, Stanley B. Zdonik:
Tupleware: Redefining Modern Analytics. CoRR abs/1406.6667 (2014) - [i7]Jiannan Wang, Guoliang Li, Tim Kraska, Michael J. Franklin, Jianhua Feng:
Leveraging Transitive Relations for Crowdsourced Joins. CoRR abs/1408.6916 (2014) - [i6]Jiannan Wang, Guoliang Li, Tim Kraska, Michael J. Franklin, Jianhua Feng:
The Expected Optimal Labeling Order Problem for Crowdsourced Joins and Entity Resolution. CoRR abs/1409.7472 (2014) - 2013
- [j11]Tim Kraska:
Finding the Needle in the Big Data Systems Haystack. IEEE Internet Comput. 17(1): 84-86 (2013) - [j10]Tim Kraska, Beth Trushkowsky:
The New Database Architectures. IEEE Internet Comput. 17(3): 72-75 (2013) - [c20]Gianluca Demartini, Beth Trushkowsky, Tim Kraska, Michael J. Franklin:
CrowdQ: Crowdsourced Query Understanding. CIDR 2013 - [c19]Tim Kraska, Ameet Talwalkar, John C. Duchi, Rean Griffith, Michael J. Franklin, Michael I. Jordan:
MLbase: A Distributed Machine-learning System. CIDR 2013 - [c18]Tim Kraska, Gene Pang, Michael J. Franklin, Samuel Madden, Alan D. Fekete:
MDCC: multi-data center consistency. EuroSys 2013: 113-126 - [c17]Sean Goldberg, Daisy Zhe Wang, Tim Kraska:
CASTLE: Crowd-Assisted System for Text Labeling and Extraction. HCOMP 2013: 51-59 - [c16]Beth Trushkowsky, Tim Kraska, Michael J. Franklin:
A Framework for Adaptive Crowd Query Processing. HCOMP (Works in Progress / Demos) 2013 - [c15]Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar:
Crowdsourced enumeration queries. ICDE 2013: 673-684 - [c14]Evan Randall Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph E. Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
MLI: An API for Distributed Machine Learning. ICDM 2013: 1187-1192 - [c13]Jiannan Wang, Guoliang Li, Tim Kraska, Michael J. Franklin, Jianhua Feng:
Leveraging transitive relations for crowdsourced joins. SIGMOD Conference 2013: 229-240 - [c12]Michael Armbrust, Eric Liang, Tim Kraska, Armando Fox, Michael J. Franklin, David A. Patterson:
Generalized scale independence through incremental precomputation. SIGMOD Conference 2013: 625-636 - [c11]Jan Schaffner, Tim Januschowski, Megan Kercher, Tim Kraska, Hasso Plattner, Michael J. Franklin, Dean Jacobs:
RTP: robust tenant placement for elastic in-memory database clusters. SIGMOD Conference 2013: 773-784 - [i5]Evan Randall Sparks, Ameet Talwalkar, Virginia Smith, Jey Kottalam, Xinghao Pan, Joseph E. Gonzalez, Michael J. Franklin, Michael I. Jordan, Tim Kraska:
MLI: An API for Distributed Machine Learning. CoRR abs/1310.5426 (2013) - 2012
- [j9]Jiannan Wang, Tim Kraska, Michael J. Franklin, Jianhua Feng:
CrowdER: Crowdsourcing Entity Resolution. Proc. VLDB Endow. 5(11): 1483-1494 (2012) - [c10]Simon Loesing, Martin Hentschel, Tim Kraska, Donald Kossmann:
Stormy: an elastic and highly available streaming service in the cloud. EDBT/ICDT Workshops 2012: 55-60 - [i4]Beth Trushkowsky, Tim Kraska, Michael J. Franklin, Purnamrita Sarkar:
Getting It All from the Crowd. CoRR abs/1202.2335 (2012) - [i3]Tim Kraska, Gene Pang, Michael J. Franklin, Samuel Madden:
MDCC: Multi-Data Center Consistency. CoRR abs/1203.6049 (2012) - [i2]Jiannan Wang, Tim Kraska, Michael J. Franklin, Jianhua Feng:
CrowdER: Crowdsourcing Entity Resolution. CoRR abs/1208.1927 (2012) - 2011
- [j8]Amber Feng, Michael J. Franklin, Donald Kossmann, Tim Kraska, Samuel Madden, Sukriti Ramesh, Andrew Wang, Reynold Xin:
CrowdDB: Query Processing with the VLDB Crowd. Proc. VLDB Endow. 4(12): 1387-1390 (2011) - [j7]AnHai Doan, Michael J. Franklin, Donald Kossmann, Tim Kraska:
Crowdsourcing Applications and Platforms: A Data Management Perspective. Proc. VLDB Endow. 4(12): 1508-1509 (2011) - [j6]Michael Armbrust, Kristal Curtis, Tim Kraska, Armando Fox, Michael J. Franklin, David A. Patterson:
PIQL: Success-Tolerant Query Processing in the Cloud. Proc. VLDB Endow. 5(3): 181-192 (2011) - [j5]Philippe Bonnet, Stefan Manegold, Matias Bjørling, Wei Cao, Javier González, Joel A. Granados, Nancy Hall, Stratos Idreos, Milena Ivanova, Ryan Johnson, David Koop, Tim Kraska, René Müller, Dan Olteanu, Paolo Papotti, Christine Reilly, Dimitris Tsirogiannis, Cong Yu, Juliana Freire, Dennis E. Shasha:
Repeatability and workability evaluation of SIGMOD 2011. SIGMOD Rec. 40(2): 45-48 (2011) - [c9]Michael J. Franklin, Donald Kossmann, Tim Kraska, Sukriti Ramesh, Reynold Xin:
CrowdDB: answering queries with crowdsourcing. SIGMOD Conference 2011: 61-72 - [i1]Michael Armbrust, Kristal Curtis, Tim Kraska, Armando Fox, Michael J. Franklin, David A. Patterson:
PIQL: Success-Tolerant Query Processing in the Cloud. CoRR abs/1111.7166 (2011) - 2010
- [b1]Tim Kraska:
Building Database Applications in the Cloud. ETH Zurich, Zürich, Switzerland, 2010 - [j4]Donald Kossmann, Tim Kraska:
Data Management in the Cloud: Promises, State-of-the-art, and Open Questions. Datenbank-Spektrum 10(3): 121-129 (2010) - [j3]Donald Kossmann, Tim Kraska, Simon Loesing, Stephan Merkli, Raman Mittal, Flavio Pfaffhauser:
Cloudy: A Modular Cloud Storage System. Proc. VLDB Endow. 3(2): 1533-1536 (2010) - [c8]Donald Kossmann, Tim Kraska, Simon Loesing:
An evaluation of alternative architectures for transaction processing in the cloud. SIGMOD Conference 2010: 579-590
2000 – 2009
- 2009
- [j2]Tim Kraska, Martin Hentschel, Gustavo Alonso, Donald Kossmann:
Consistency Rationing in the Cloud: Pay only when it matters. Proc. VLDB Endow. 2(1): 253-264 (2009) - [j1]Roger Bamford, Vinayak R. Borkar, Matthias Brantner, Peter M. Fischer, Daniela Florescu, David A. Graf, Donald Kossmann, Tim Kraska, Dan Muresan, Sorin Nasoi, Markos Zacharioudaki:
XQuery Reloaded. Proc. VLDB Endow. 2(2): 1342-1353 (2009) - [c7]Carsten Binnig, Donald Kossmann, Tim Kraska, Simon Loesing:
How is the weather tomorrow?: towards a benchmark for the cloud. DBTest 2009 - [c6]Ghislain Fourny, Markus Pilman, Daniela Florescu, Donald Kossmann, Tim Kraska, Darin McBeath:
XQuery in the browser. WWW 2009: 1011-1020 - 2008
- [c5]Matthias Brantner, Daniela Florescu, David A. Graf, Donald Kossmann, Tim Kraska:
Building a database on S3. SIGMOD Conference 2008: 251-264 - [c4]Ghislain Fourny, Donald Kossmann, Tim Kraska, Markus Pilman, Daniela Florescu:
XQuery in the browser. SIGMOD Conference 2008: 1337-1340 - 2007
- [c3]Irina Botan, Peter M. Fischer, Daniela Florescu, Donald Kossmann, Tim Kraska, Rokas Tamosevicius:
Extending XQuery with Window Functions. VLDB 2007: 75-86 - 2006
- [c2]Joshua Wing Kei Ho, Tristan Manwaring, Seok-Hee Hong, Uwe Röhm, David Cho Yau Fung, Kai Xu, Tim Kraska, David Hart:
PathBank: Web-Based Querying and Visualziation of an Integrated Biological Pathway Database. CGIV 2006: 84-89 - [c1]Tim Kraska, Uwe Röhm:
Genea: Schema-Aware Mapping of Ontologies into Relational Databases. COMAD 2006: 92-103
Coauthor Index
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