Publications (by tag | by type )

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Vizualization
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YearTypePublication
2020JournalNadiia Chepurko and Ryan Marcus and Emanuel Zgraggen and Raul Castro Fernandez and Tim Kraska and David Karger (2020). ARDA: Automatic Relational Data Augmentation for Machine Learning. Proc. VLDB Endow., 13(9), pp. 1373–1387. [Tags: Machine Learning] (pdf) (bib) (tweet)
2020JournalJialin Ding and Vikram Nathan and Mohammad Alizadeh and Tim Kraska (2020). Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. Proc. VLDB Endow., -, pp. -. [Tags: Machine Learning for Systems] (bib)
2020JournalAndreas Kipf and Ryan Marcus and Alexander van Renen and Mihail Stoian and Alfons Kemper and Tim Kraska and Thomas Neumann (2020). Benchmarking Learned Indexes (Experiments & Analyses). Proc. VLDB Endow., -, pp. -. [Tags: Machine Learning for Systems] (bib)
2020ConferenceFavyen Bastani and Songtao He and Arjun Balasingam and Karthik Gopalakrishnan and Mohammad Alizadeh and Hari Balakrishnan and Michael J. Cafarella and Tim Kraska and Sam Madden (2020). MIRIS: Fast Object Track Queries in Video. In Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020. [Tags: Video Processing] (link) (bib) (tweet)
2020ConferencePhilipp Eichmann and Emanuel Zgraggen and Carsten Binnig and Tim Kraska (2020). IDEBench: A Benchmark for Interactive Data Exploration. In Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020. [Tags: Interactive Data Science Systems] (link) (bib) (tweet)
2020ConferenceAni Kristo and Kapil Vaidya and Ugur \cCetintemel and Sanchit Misra and Tim Kraska (2020). The Case for a Learned Sorting Algorithm. In Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020ConferenceVikram Nathan and Jialin Ding and Mohammad Alizadeh and Tim Kraska (2020). Learning Multi-Dimensional Indexes. In Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020ConferenceJialin Ding and Umar Farooq Minhas and Jia Yu and Chi Wang and Jaeyoung Do and Yinan Li and Hantian Zhang and Badrish Chandramouli and Johannes Gehrke and Donald Kossmann and David B. Lomet and Tim Kraska (2020). ALEX: An Updatable Adaptive Learned Index. In Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020ConferenceErfan Zamanian and Julian Shun and Carsten Binnig and Tim Kraska (2020). Chiller: Contention-centric Transaction Execution and Data Partitioning for Modern Networks. In Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020. [Tags: Rack-Scale Computing, Transaction Processing] (link) (bib) (tweet)
2020ConferenceMatthias Jasny and Tobias Ziegler and Tim Kraska and Uwe Röhm and Carsten Binnig (2020). DB4ML - An In-Memory Database Kernel with Machine Learning Support. In Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020. [Tags: Machine Learning] (link) (bib) (tweet)
2020ConferenceSongtao He and Favyen Bastani and Arjun Balasingam and Karthik Gopalakrishnan and Ziwen Jiang and Mohammad Alizadeh and Hari Balakrishnan and Michael J. Cafarella and Tim Kraska and Sam Madden (2020). BeeCluster: drone orchestration via predictive optimization. In MobiSys '20: The 18th Annual International Conference on Mobile Systems, Applications, and Services, Toronto, Ontario, Canada, June 15-19, 2020. [Tags: Video Processing] (link) (bib) (tweet)
2020ConferenceAndrew Crotty and Alex Galakatos and Tim Kraska (2020). Getting Swole: Generating Access-Aware Code with Predicate Pullups. In 36th IEEE International Conference on Data Engineering, ICDE 2020, Dallas, TX, USA, April 20-24, 2020. [Tags: Rack-Scale Computing] (link) (bib) (tweet)
2020ConferenceJeremy Kepner and Darren Engwirda and Vijay Gadepally and Chris Hill and Tim Kraska and Michael Jones and Andreas Kipf and Lauren Milechin and Navin Vembar (2020). Fast Mapping onto Census Blocks. In Proceedings of the IEEE High Performance Extreme Computing Conference (HPEC). [Tags: ] (bib)
2020WorkshopAndreas Kipf and Ryan Marcus and Alexander van Renen and Mihail Stoian and Alfons Kemper and Tim Kraska and Thomas Neumann (2020). RadixSpline: a single-pass learned index. In Proceedings of the Third International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, aiDM at SIGMOD 2020, Portland, Oregon, USA, June 19, 2020. [Tags: Machine Learning for Systems] (bib)
2020WorkshopLujing Cen and Ryan Marcus and Hongzi Mao and Justin Gottschlich and Mohammad Alizadeh and Tim Kraska (2020). Learned garbage collection. In Proceedings of the 4th ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, MAPL at PLDI 2020, London, UK, June 15, 2020. [Tags: missing] (bib)
2020WorkshopParimarjan Negi and Ryan Marcus and Hongzi Mao and Nesime Tatbul and Tim Kraska and Mohammad Alizadeh (2020). Cost-Guided Cardinality Estimation: Focus Where it Matters. In 36th IEEE International Conference on Data Engineering Workshops, ICDE Workshops 2020, Dallas, TX, USA, April 20-24, 2020. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020WorkshopGennady L. Andrienko and Natalia V. Andrienko and Steven Mark Drucker and Jean-Daniel Fekete and Danyel Fisher and Stratos Idreos and Tim Kraska and Guoliang Li and Kwan-Liu Ma and Jock D. Mackinlay and Antti Oulasvirta and Tobias Schreck and Heidrun Schumann and Michael Stonebraker and David Auber and Nikos Bikakis and Panos K. Chrysanthis and George Papastefanatos and Mohamed A. Sharaf (2020). Big Data Visualization and Analytics: Future Research Challenges and Emerging Applications. In Proceedings of the Workshops of the EDBT/ICDT 2020 Joint Conference, Copenhagen, Denmark, March 30, 2020. [Tags: ] (pdf) (bib) (tweet)
2020Technical reportMichael J. Cafarella and David J. DeWitt and Vijay Gadepally and Jeremy Kepner and Christos Kozyrakis and Tim Kraska and Michael Stonebraker and Matei Zaharia (2020). DBOS: A Proposal for a Data-Centric Operating System. CoRR, abs/2007.11112. [Tags: ] (link) (bib) (tweet)
2020Technical reportJialin Ding and Vikram Nathan and Mohammad Alizadeh and Tim Kraska (2020). Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads. CoRR, abs/2006.13282. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020Technical reportRyan Marcus and Andreas Kipf and Alexander van Renen and Mihail Stoian and Sanchit Misra and Alfons Kemper and Thomas Neumann and Tim Kraska (2020). Benchmarking Learned Indexes. CoRR, abs/2006.12804. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020Technical reportFangke Ye and Shengtian Zhou and Anand Venkat and Ryan Marcus and Nesime Tatbul and Jesmin Jahan Tithi and Paul Petersen and Timothy G. Mattson and Tim Kraska and Pradeep Dubey and Vivek Sarkar and Justin Gottschlich (2020). MISIM: An End-to-End Neural Code Similarity System. CoRR, abs/2006.05265. [Tags: Video Processing] (link) (bib) (tweet)
2020Technical reportKapil Vaidya and Eric Knorr and Tim Kraska and Michael Mitzenmacher (2020). Partitioned Learned Bloom Filter. CoRR, abs/2006.03176. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020Technical reportOscar Moll and Favyen Bastani and Sam Madden and Mike Stonebraker and Vijay Gadepally and Tim Kraska (2020). ExSample: Efficient Searches on Video Repositories through Adaptive Sampling. CoRR, abs/2005.09141. [Tags: Video Processing] (link) (bib) (tweet)
2020Technical reportJeremy Kepner and Darren Engwirda and Vijay Gadepally and Chris Hill and Tim Kraska and Michael Jones and Andreas Kipf and Lauren Milechin and Navin Vembar (2020). Fast Mapping onto Census Blocks. CoRR, abs/2005.03156. [Tags: ] (link) (bib) (tweet)
2020Technical reportRyan Marcus and Parimarjan Negi and Hongzi Mao and Nesime Tatbul and Mohammad Alizadeh and Tim Kraska (2020). Bao: Learning to Steer Query Optimizers. CoRR, abs/2004.03814. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020Technical reportLujing Cen and Ryan Marcus and Hongzi Mao and Justin Gottschlich and Mohammad Alizadeh and Tim Kraska (2020). Learned Garbage Collection. CoRR, abs/2004.13301. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020Technical reportFangke Ye and Shengtian Zhou and Anand Venkat and Ryan Marcus and Paul Petersen and Jesmin Jahan Tithi and Tim Mattson and Tim Kraska and Pradeep Dubey and Vivek Sarkar and Justin Gottschlich (2020). Context-Aware Parse Trees. CoRR, abs/2003.11118. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2020Technical reportNadiia Chepurko and Ryan Marcus and Emanuel Zgraggen and Raul Castro Fernandez and Tim Kraska and David Karger (2020). ARDA: Automatic Relational Data Augmentation for Machine Learning. CoRR, abs/2003.09758. [Tags: Machine Learning] (link) (bib) (tweet)
2020MiscRyan Marcus and Emily Zhang and Tim Kraska (2020). CDFShop: Exploring and Optimizing Learned Index Structures. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2019JournalErfan Zamanian and Xiangyao Yu and Michael Stonebraker and Tim Kraska (2019). Rethinking Database High Availability with RDMA Networks. Proc. VLDB Endow., 12(11), pp. 1637–1650. [Tags: Rack-Scale Computing] (pdf) (bib) (tweet)
2019JournalRyan C. Marcus and Parimarjan Negi and Hongzi Mao and Chi Zhang and Mohammad Alizadeh and Tim Kraska and Olga Papaemmanouil and Nesime Tatbul (2019). Neo: A Learned Query Optimizer. Proc. VLDB Endow., 12(11), pp. 1705–1718. [Tags: Machine Learning for Systems] (pdf) (bib) (tweet)
2019JournalJunjay Tan and Thanaa Ghanem and Matthew Perron and Xiangyao Yu and Michael Stonebraker and David J. DeWitt and Marco Serafini and Ashraf Aboulnaga and Tim Kraska (2019). Choosing A Cloud DBMS: Architectures and Tradeoffs. Proc. VLDB Endow., 12(12), pp. 2170–2182. [Tags: Cloud Computing] (pdf) (bib) (tweet)
2019JournalAnastasia Ailamaki and Periklis Chrysogelos and Amol Deshpande and Tim Kraska (2019). The SIGMOD 2019 Research Track Reviewing System. SIGMOD Rec., 48(2), pp. 47–54. [Tags: ] (link) (bib) (tweet)
2019JournalDaniel Abadi and Anastasia Ailamaki and David Andersen and Peter Bailis and Magdalena Balazinska and Philip A. Bernstein and Peter A. Boncz and Surajit Chaudhuri and Alvin Cheung and AnHai Doan and Luna Dong and Michael J. Franklin and Juliana Freire and Alon Y. Halevy and Joseph M. Hellerstein and Stratos Idreos and Donald Kossmann and Tim Kraska and Sailesh Krishnamurthy and Volker Markl and Sergey Melnik and Tova Milo and C. Mohan and Thomas Neumann and Beng Chin Ooi and Fatma Ozcan and Jignesh Patel and Andrew Pavlo and Raluca A. Popa and Raghu Ramakrishnan and Christopher Ré and Michael Stonebraker and Dan Suciu (2019). The Seattle Report on Database Research. SIGMOD Rec., 48(4), pp. 44–53. [Tags: ] (link) (bib) (tweet)
2019ConferenceTim Kraska and Mohammad Alizadeh and Alex Beutel and Ed H. Chi and Ani Kristo and Guillaume Leclerc and Samuel Madden and Hongzi Mao and Vikram Nathan (2019). SageDB: A Learned Database System. In CIDR 2019, 9th Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 13-16, 2019, Online Proceedings. [Tags: Machine Learning for Systems] (pdf) (bib) (tweet)
2019ConferenceKevin Hu, Neil Gaikwad, Michiel Bakker, Madelon Hulsebos, Emanual Zgraggen, Cesar Hidalgo, Tim Kraska, G. Li, Cagatay Demiralp (2019). VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository . In ACM Conference on Human Factors in Computing Systems (CHI). [Tags: Interactive Data Science Systems] (bib)
2019ConferenceKevin Z. Hu, Michiel A. Bakker, Stephen Li, Tim Kraska, Caesar A. Hidalgo (2019). VizML: A Machine Learning Approach to Visualization Recommendation . In ACM Conference on Human Factors in Computing Systems (CHI). [Tags: Interactive Data Science Systems, Machine Learning] (bib)
2019ConferenceTobias Ziegler, Sumukha Tumkur Vani, Carsten Binnig, Rodrigo Fonseca, Tim Kraska (2019). Designing Distributed Tree-based Index Structures for fast RDMA-capable Networks. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD). [Tags: Rack-Scale Computing] (bib)
2019ConferenceMatthew Perron, Zeyuan Shang, Tim Kraska, Michael Stonebraker: (2019). How I Learned to Stop Worrying and Love Re-optimization. In Proceedings of the IEEE International Conference on Data Engineering (ICDE). [Tags: Rack-Scale Computing] (bib)
2019ConferenceYeounoh Chung, Tim Kraska, Neoklis Polyzotis, Steven Euijong Whang (2019). Slice Finder: Automated Data Slicing for Model Validation. In Proceedings of the IEEE International Conference on Data Engineering (ICDE). [Tags: Machine Learning] (bib)
2019ConferenceAlex Galakatos, Michael Markovitch, Carsten Binnig, Rodrigo Fonseca, Tim Kraska (2019). FITing-Tree: A Data-aware Index Structure. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD). [Tags: Machine Learning for Systems] (bib)
2019ConferenceZeyuan Shang, Emanuel Zgraggen, Benedetto Buratti, Ferdinand Kossmann, Yeounoh Chung, Philipp Eichmann, Carsten Binnig, Eli Upfal, Tim Kraska (2019). Democratizing Data Science through Interactive Curation of ML Pipelines. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD). [Tags: Machine Learning] (bib)
2019ConferenceStratos Idreos and Tim Kraska (2019). From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems (Tutorial). In Proceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019, Amsterdam, The Netherlands, June 30 - July 5, 2019.. [Tags: Machine Learning for Systems] (pdf) (bib) (tweet)
2019ConferenceHongzi Mao and Parimarjan Negi and Akshay Narayan and Hanrui Wang and Jiacheng Yang and Haonan Wang and Ryan Marcus and Ravichandra Addanki and Mehrdad Khani Shirkoohi and Songtao He and Vikram Nathan and Frank Cangialosi and Shaileshh Venkatakrishnan and Wei-Hung Weng and Song Han and Tim Kraska and Dr.Mohammad Alizadeh (2019). Park: An Open Platform for Learning-Augmented Computer Systems. In Conference on Neural Information Processing Systems (NeurIPS). [Tags: Machine Learning for Systems] (bib)
2019ConferenceLorenzo De Stefani and Leonhard F. Spiegelberg and Eli Upfal and Tim Kraska (2019). VizCertify: A Framework for Secure Visual Data Exploration. In 2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019, Washington, DC, USA, October 5-8, 2019. [Tags: Interactive Data Science Systems] (link) (bib) (tweet)
2019ConferenceMadelon Hulsebos and Kevin Zeng Hu and Michiel A. Bakker and Emanuel Zgraggen and Arvind Satyanarayan and Tim Kraska and \cCagatay Demiralp and César A. Hidalgo (2019). Sherlock: A Deep Learning Approach to Semantic Data Type Detection. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019. [Tags: Data Integration] (link) (bib) (tweet)
2019ConferenceStratos Idreos and Tim Kraska (2019). From Auto-tuning One Size Fits All to Self-designed and Learned Data-intensive Systems. In Proceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019, Amsterdam, The Netherlands, June 30 - July 5, 2019. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2019WorkshopTim Kraska and Michael Stonebraker and Michael Brodie, Sacha Servan-Schreiber, Daniel J. Weitzner (2019). DATUMDB: A Data Protection Database Proposal. In Poly'19 co-located at VLDB 2019. [Tags: Data Integration] (bib)
2019WorkshopAni Kristo and Kapil Vaidya and Ugur Cetintemel and Tim Kraska (2019). The Case for a Learned Sorting Algorithm. In AI Systems Workshop at SOSP 2019. [Tags: Machine Learning for Systems] (bib)
2019WorkshopAndreas Kipf and Ryan Marcus and Alexander van Renen and Mihail Stoian and Alfons Kemper and Tim Kraska and Thomas Neumann (2019). Learning to Search. In NeurIPS 2019 Workshop on Machine Learning for Systems. [Tags: Machine Learning for Systems] (bib)
2019WorkshopVikram Nathan and Jialin Ding and Mohammad Alizadeh and Tim Kraska (2019). Learned Multi-dimensional Indexing. In NeurIPS 2019 Workshop on Machine Learning for Systems. [Tags: Machine Learning for Systems] (bib)
2019WorkshopZeyuan Shang and Emanuel Zgraggen and Philipp Eichmann and Tim Kraska (2019). Niseko: a Large-Scale Meta-Learning Dataset. In NeurIPS 2019 Workshop on Meta-Learning. [Tags: Machine Learning for Systems] (bib)
2019WorkshopDarryl Ho and Jialin Ding and Sanchit Misra and Nesime Tatbul and Vikram Nathan and Vasimuddin Md and Tim Kraska (2019). LISA: Towards Learned DNA Sequence Search. In MLSys: Workshop on Systems for ML. [Tags: Machine Learning for Systems] (bib)
2019WorkshopZeyuan Shang and Emanuel Zgraggen and Tim Kraska (2019). Alpine Meadow: A System for Interactive AutoML. In MLSys: Workshop on Systems for ML. [Tags: Machine Learning for Systems] (bib)
2019WorkshopTim Kraska and Michael Stonebraker and Michael L. Brodie and Sacha Servan-Schreiber and Daniel J. Weitzner (2019). SchengenDB: A Data Protection Database Proposal. In Heterogeneous Data Management, Polystores, and Analytics for Healthcare - VLDB 2019 Workshops, Poly and DMAH, Los Angeles, CA, USA, August 30, 2019, Revised Selected Papers. [Tags: ] (link) (bib) (tweet)
2019Technical reportMatthew Perron and Zeyuan Shang and Tim Kraska and Michael Stonebraker (2019). How I Learned to Stop Worrying and Love Re-optimization. CoRR, abs/1902.08291. [Tags: Rack-Scale Computing] (link) (bib) (tweet)
2019Technical reportSacha Servan-Schreiber and Olga Ohrimenko and Tim Kraska and Emanuel Zgraggen (2019). Custodes: Auditable Hypothesis Testing. CoRR, abs/1901.10875. [Tags: Interactive Data Science Systems] (link) (bib) (tweet)
2019Technical reportMadelon Hulsebos and Kevin Zeng Hu and Michiel A. Bakker and Emanuel Zgraggen and Arvind Satyanarayan and Tim Kraska and \cCagatay Demiralp and César A. Hidalgo (2019). Sherlock: A Deep Learning Approach to Semantic Data Type Detection. CoRR, abs/1905.10688. [Tags: Vizualization, Machine Learning] (link) (bib) (tweet)
2019Technical reportRyan Marcus and Parimarjan Negi and Hongzi Mao and Chi Zhang and Mohammad Alizadeh and Tim Kraska and Olga Papaemmanouil and Nesime Tatbul (2019). Neo: A Learned Query Optimizer. CoRR, abs/1904.03711. [Tags: Machine Learning for Systems, Machine Learning] (link) (bib) (tweet)
2019Technical reportAlexander Ratner and others (2019). SysML: The New Frontier of Machine Learning Systems. CoRR, abs/1904.03257. [Tags: Machine Learning for Systems, Machine Learning] (bib)
2019Technical reportAlexander Ratner and others (2019). SysML: The New Frontier of Machine Learning Systems. CoRR, abs/1904.03257. [Tags: ] (link) (bib) (tweet)
2019Technical reportDarryl Ho and Jialin Ding and Sanchit Misra and Nesime Tatbul and Vikram Nathan and Vasimuddin Md and Tim Kraska (2019). LISA: Towards Learned DNA Sequence Search. CoRR, abs/1910.04728. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2019Technical reportAndreas Kipf and Ryan Marcus and Alexander van Renen and Mihail Stoian and Alfons Kemper and Tim Kraska and Thomas Neumann (2019). SOSD: A Benchmark for Learned Indexes. CoRR, abs/1911.13014. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2019Technical reportVikram Nathan and Jialin Ding and Mohammad Alizadeh and Tim Kraska (2019). Learning Multi-dimensional Indexes. CoRR, abs/1912.01668. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2019MiscLeonhard F. Spiegelberg and Tim Kraska (2019). Tuplex: Robust, Efficient Analytics When Python Rules. [Tags: Rack-Scale Computing, Data Integration] (pdf) (bib) (tweet)
2018JournalYeounoh Chung and Michael Lind Mortensen and Carsten Binnig and Tim Kraska (2018). Estimating the Impact of Unknown Unknowns on Aggregate Query Results. ACM Trans. Database Syst., 43(1), pp. 3:1–3:37. [Tags: Interactive Data Science Systems] (bib)
2018JournalTim Kraska (2018). Northstar: An Interactive Data Science System. PVLDB, 11(12), pp. 2150–2164. [Tags: Interactive Data Science Systems] (bib)
2018JournalYeounoh Chung and Sacha Servan-Schreiber and Emanuel Zgraggen and Tim Kraska (2018). Towards Quantifying Uncertainty in Data Analysis & Exploration. IEEE Data Eng. Bull., 41(3), pp. 15–27. [Tags: Data Integration] (bib)
2018ConferenceLinnan Wang and Jinmian Ye and Yiyang Zhao and Wei Wu and Ang Li and Shuaiwen Leon Song and Zenglin Xu and Tim Kraska (2018). Superneurons: dynamic GPU memory management for training deep neural networks. In Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2018, Vienna, Austria, February 24-28, 2018. [Tags: Machine Learning] (bib)
2018ConferenceTim Kraska and Alex Beutel and Ed H. Chi and Jeffrey Dean and Neoklis Polyzotis (2018). The Case for Learned Index Structures. In Proceedings of the 2018 International Conference on Management of Data, SIGMOD Conference 2018, Houston, TX, USA, June 10-15, 2018. [Tags: Machine Learning for Systems] (link) (bib) (tweet)
2018ConferenceEmanuel Zgraggen and Zheguang Zhao and Robert C. Zeleznik and Tim Kraska (2018). Investigating the Effect of the Multiple Comparisons Problem in Visual Analysis. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems CHI 2018, Montreal, QC, Canada, April 21-26, 2018. [Tags: Data Integration] (bib)
2018WorkshopCarsten Binnig and Benedetto Buratti and Yeounoh Chung and Cyrus Cousins and Tim Kraska and Zeyuan Shang and Eli Upfal and Robert C. Zeleznik and Emanuel Zgraggen (2018). Towards Interactive Curation and Automatic Tuning of ML Pipelines. In Proceedings of the Second Workshop on Data Management for End-To-End Machine Learning, DEEM at SIGMOD 2018, Houston, TX, USA, June 15, 2018. [Tags: Interactive Data Science Systems, Machine Learning] (bib)
2018Technical reportLinnan Wang and Jinmian Ye and Yiyang Zhao and Wei Wu and Ang Li and Shuaiwen Leon Song and Zenglin Xu and Tim Kraska (2018). SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks. CoRR, abs/1801.04380. [Tags: Machine Learning] (link) (bib) (tweet)
2018Technical reportErfan Zamanian and Julian Shun and Carsten Binnig and Tim Kraska (2018). Chiller: Contention-centric Transaction Execution and Data Partitioning for Fast Networks. CoRR, abs/1811.12204. [Tags: Rack-Scale Computing, Transaction Processing] (link) (bib) (tweet)
2018Technical reportLorenzo De Stefani and Leonhard F. Spiegelberg and Tim Kraska and Eli Upfal (2018). VizRec: A framework for secure data exploration via visual representation. CoRR, abs/1811.00602. [Tags: Interactive Data Science Systems, Machine Learning] (link) (bib) (tweet)
2018Technical reportAlex Galakatos and Michael Markovitch and Carsten Binnig and Rodrigo Fonseca and Tim Kraska (2018). A-Tree: A Bounded Approximate Index Structure. CoRR, abs/1801.10207. [Tags: Interactive Data Science Systems, Machine Learning] (link) (bib) (tweet)
2018Technical reportYeounoh Chung and Peter J. Haas and Eli Upfal and Tim Kraska (2018). Unknown Examples & Machine Learning Model Generalization. CoRR, abs/1808.08294. [Tags: Machine Learning] (link) (bib) (tweet)
2018Technical reportGuillaume Leclerc and Manasi Vartak and Raul Castro Fernandez and Tim Kraska and Samuel Madden (2018). Smallify: Learning Network Size while Training. CoRR, abs/1806.03723. [Tags: Machine Learning] (link) (bib) (tweet)
2018Technical reportPhilipp Eichmann and Carsten Binnig and Tim Kraska and Emanuel Zgraggen (2018). IDEBench: A Benchmark for Interactive Data Exploration. CoRR, abs/1804.02593. [Tags: Interactive Data Science Systems] (link) (bib) (tweet)
2018Technical reportKevin Zeng Hu and Michiel A. Bakker and Stephen Li and Tim Kraska and César A. Hidalgo (2018). VizML: A Machine Learning Approach to Visualization Recommendation. CoRR, abs/1808.04819. [Tags: Interactive Data Science Systems] (link) (bib) (tweet)
2018Technical reportYeounoh Chung and Tim Kraska and Neoklis Polyzotis and Steven Euijong Whang (2018). Slice Finder: Automated Data Slicing for Model Validation. CoRR, abs/1807.06068. [Tags: Interactive Data Science Systems, Machine Learning] (link) (bib) (tweet)
2017JournalErfan Zamanian and Carsten Binnig and Tim Kraska and Tim Harris (2017). The End of a Myth: Distributed Transaction Can Scale. PVLDB, 10(6), pp. 685–696. [Tags: Rack-Scale Computing, Transaction Processing] (bib)
2017JournalEmanuel Zgraggen and Alex Galakatos and Andrew Crotty and Jean-Daniel Fekete and Tim Kraska (2017). How Progressive Visualizations Affect Exploratory Analysis. IEEE Trans. Vis. Comput. Graph., 23(8), pp. 1977–1987. [Tags: Interactive Data Science Systems] (bib)
2017JournalAlex Galakatos and Andrew Crotty and Emanuel Zgraggen and Carsten Binnig and Tim Kraska (2017). Revisiting Reuse for Approximate Query Processing. PVLDB, 10(10), pp. 1142–1153. [Tags: Interactive Data Science Systems] (bib)
2017JournalYeounoh Chung and Sanjay Krishnan and Tim Kraska (2017). A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets. PVLDB, 10(10), pp. 1094–1105. [Tags: Data Integration, Crowd Computing] (bib)
2017JournalErfan Zamanian and Carsten Binnig and Tim Kraska and Tim Harris (2017). The End of a Myth: Distributed Transaction Can Scale. PVLDB, 10(6), pp. 685–696. [Tags: Transaction Processing, Rack-Scale Computing] (bib)
2017JournalAbdallah Salama and Carsten Binnig and Tim Kraska and Ansgar Scherp and Tobias Ziegler (2017). Rethinking Distributed Query Execution on High-Speed Networks. IEEE Data Eng. Bull., 40(1), pp. 27–37. [Tags: Rack-Scale Computing] (bib)
2017JournalTim Kraska (2017). Letter from the Special Issue Editor. IEEE Data Eng. Bull., 40(4), pp. 2. [Tags: Transaction Processing] (pdf) (bib) (tweet)
2017JournalTim Kraska (2017). Letter from the Special Issue Editor. IEEE Data Eng. Bull., 40(1), pp. 2. [Tags: Transaction Processing] (bib)
2017ConferenceTim Kraska (2017). Approximate Query Processing for Interactive Data Science. In Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14-19, 2017. [Tags: Interactive Data Science Systems, Rack-Scale Computing] (bib)
2017ConferenceChristoph Pinkel and Carsten Binnig and Ernesto Jiménez-Ruiz and Evgeny Kharlamov and Andriy Nikolov and Andreas Schwarte and Christian Heupel and Tim Kraska (2017). IncMap: A Journey towards Ontology-based Data Integration. In Datenbanksysteme f\"ur Business, Technologie und Web (BTW 2017), 17. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 6.-10. März 2017, Stuttgart, Germany, Proceedings. [Tags: Data Integration] (bib)
2017ConferenceCarsten Binnig and Lorenzo De Stefani and Tim Kraska and Eli Upfal and Emanuel Zgraggen and Zheguang Zhao (2017). Toward Sustainable Insights, or Why Polygamy is Bad for You. In CIDR 2017, 8th Biennial Conference on Innovative Data Systems Research, Chaminade, CA, USA, January 8-11, 2017, Online Proceedings. [Tags: Interactive Data Science Systems] (bib)
2017ConferenceZheguang Zhao and Emanuel Zgraggen and Lorenzo De Stefani and Carsten Binnig and Eli Upfal and Tim Kraska (2017). Safe Visual Data Exploration. In Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14-19, 2017. [Tags: Interactive Data Science Systems] (bib)
2017ConferenceZheguang Zhao and Lorenzo De Stefani and Emanuel Zgraggen and Carsten Binnig and Eli Upfal and Tim Kraska (2017). Controlling False Discoveries During Interactive Data Exploration. In Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 14-19, 2017. [Tags: Interactive Data Science Systems] (bib)
2017ConferenceTim Kraska and Elkhan Dadashov and Carsten Binnig (2017). Spotlytics: How to Use Cloud Market Places for Analytics?. In Datenbanksysteme f\"ur Business, Technologie und Web (BTW 2017), 17. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 6.-10. März 2017, Stuttgart, Germany, Proceedings. [Tags: Cloud Computing] (bib)
2017ConferenceChristoph Pinkel and Carsten Binnig and Ernesto Jiménez-Ruiz and Evgeny Kharlamov and Andriy Nikolov and Andreas Schwarte and Christian Heupel and Tim Kraska (2017). IncMap: A Journey towards Ontology-based Data Integration. In Datenbanksysteme f\"ur Business, Technologie und Web (BTW 2017), 17. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 6.-10. März 2017, Stuttgart, Germany, Proceedings. [Tags: Data Integration] (bib)
2017WorkshopYue Guo and Carsten Binnig and Tim Kraska (2017). What you see is not what you get!: Detecting Simpson's Paradoxes during Data Exploration. In Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics, HILDA SIGMOD 2017, Chicago, IL, USA, May 14, 2017. [Tags: Interactive Data Science Systems] (bib)
2017Technical reportTim Kraska and Alex Beutel and Ed H. Chi and Jeffrey Dean and Neoklis Polyzotis (2017). The Case for Learned Index Structures. CoRR, abs/1712.01208. [Tags: Machine Learning] (bib)
2016JournalBeth Trushkowsky and Tim Kraska and Michael J. Franklin, Purnamrita Sarkar (2016). Answering Enumeration Queries with the Crowd. Commun. ACM, 59(1), pp. 118–127. [Tags: Crowd Computing] (bib)
2016JournalBeth Trushkowsky and Tim Kraska and Michael J. Franklin and Purnamrita Sarkar (2016). Answering enumeration queries with the crowd. Commun. ACM, 59(1), pp. 118–127. [Tags: Data Integration, Crowd Computing] (bib)
2016JournalCarsten Binnig and Andrew Crotty and Alex Galakatos and Tim Kraska and Erfan Zamanian (2016). The End of Slow Networks: It's Time for a Redesign. PVLDB, 9(7), pp. 528–539. [Tags: Rack-Scale Computing, Transaction Processing] (bib)
2016JournalPhilipp Eichmann and Emanuel Zgraggen and Zheguang Zhao and Carsten Binnig and Tim Kraska (2016). Towards a Benchmark for Interactive Data Exploration. IEEE Data Eng. Bull., 39(4), pp. 50–61. [Tags: ] (bib)
2016ConferenceYeounoh Chung and Michael Lind Mortensen and Carsten Binnig and Tim Kraska (2016). Estimating the Impact of Unknown Unknowns on Aggregate Query Results. In SIGMOD 2016. [Tags: Interactive Data Science Systems] (link) (bib) (tweet)
2016ConferenceSanjay Krishnan and Jiannan Wang and Michael J. Franklin and Ken Goldberg and Tim Kraska (2016). PrivateClean: Data Cleaning and Differential Privacy. In SIGMOD. [Tags: Data Integration] (bib)
2016ConferenceMichael J. Cafarella and Ihab F. Ilyas and Marcel Kornacker and Tim Kraska and Christopher Ré (2016). Dark Data: Are we solving the right problems?. In 32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki, Finland, May 16-20, 2016. [Tags: Machine Learning] (bib)
2016WorkshopMuhammad El-Hindi and Zheguang Zhao and Carsten Binnig and Tim Kraska (2016). VisTrees: fast indexes for interactive data exploration. In Workshop on Human-In-the-Loop Data Analytics (HILDA) at SIGMOD. [Tags: Interactive Data Science Systems] (bib)
2016WorkshopAndrew Crotty and Alex Galakatos and Emanuel Zgraggen and Carsten Binnig and Tim Kraska (2016). The case for interactive data exploration accelerators (IDEAs). In Workshop on Human-In-the-Loop Data Analytics (HILDA) at SIGMOD. [Tags: Interactive Data Science Systems, Machine Learning] (bib)
2016Technical reportErfan Zamanian and Carsten Binnig and Tim Kraska and Tim Harris (2016). The End of a Myth: Distributed Transactions Can Scale. CoRR, abs/1607.00655. [Tags: Rack-Scale Computing, Transaction Processing] (link) (bib) (tweet)
2016Technical reportKayhan Dursun and Carsten Binnig and Ugur \cCetintemel and Tim Kraska (2016). Revisiting Reuse in Main Memory Database Systems. CoRR, abs/1608.05678. [Tags: Interactive Data Science Systems, Rack-Scale Computing] (link) (bib) (tweet)
2016Technical reportYeounoh Chung and Sanjay Krishnan and Tim Kraska (2016). A Data Quality Metric (DQM): How to Estimate The Number of Undetected Errors in Data Sets. CoRR, abs/1611.04878. [Tags: Data Integration, Crowd Computing] (link) (bib) (tweet)
2016MiscGabriel Lyons and Vinh Tran and Carsten Binnig and Ugur \cCetintemel and Tim Kraska (2016). Making the Case for Query-by-Voice with EchoQuery. [Tags: Interactive Data Science Systems] (bib)
2015JournalBeth Trushkowsky and Tim Kraska and Michael J. Franklin and Purnamrita Sarkar and Venketaram Ramachandran (2015). Crowdsourcing Enumeration Queries: Estimators and Interfaces. IEEE Trans. Knowl. Data Eng., 27(7), pp. 1796–1809. [Tags: Crowd Computing] (link) (bib) (tweet)
2015JournalJohn Meehan and Nesime Tatbul and Stan Zdonik and Cansu Aslantas and Ugur Cetintemel and Jiang Du and Tim Kraska and Samuel Madden and David Maier and Andrew Pavlo and Michael Stonebraker and Kristin Tufte and Hao Wang (2015). S-Store: Streaming Meets Transaction Processing. PVLDB, 8(13), pp. 2134–2145. [Tags: Stream Processing, Transaction Processing] (pdf) (bib) (tweet)
2015JournalAndrew Crotty and Alex Galakatos and Kayhan Dursun and Tim Kraska and Carsten Binnig and Ugur Cetintemel and Stan Zdonik (2015). An Architecture for Compiling UDF-centric Workflows. PVLDB, 8(12), pp. 1466–1477. [Tags: Interactive Data Science Systems, Machine Learning, Rack-Scale Computing] (pdf) (bib) (tweet)
2015JournalSanjay Krishnan and Jiannan Wang and Michael J. Franklin and Ken Goldberg and Tim Kraska (2015). Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views. PVLDB, 8(12), pp. 1370–1381. [Tags: Cloud Computing] (pdf) (bib) (tweet)
2015ConferenceAbdallah Salama and Carsten Binnig and Tim Kraska and Erfan Zamanian (2015). Cost-based Fault-tolerance for Parallel Data Processing. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31 - June 4, 2015. [Tags: Cloud Computing] (link) (bib) (tweet)
2015ConferenceChristopher Ré and Divy Agrawal and Magdalena Balazinska and Michael I. Cafarella and Michael I. Jordan and Tim Kraska and Raghu Ramakrishnan (2015). Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype?. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31 - June 4, 2015. [Tags: Machine Learning] (link) (bib) (tweet)
2015ConferenceEvan R. Sparks and Ameet Talwalkar and Daniel Haas and Michael J. Franklin and Michael I. Jordan and Tim Kraska (2015). Automating model search for large scale machine learning. In Proceedings of the Sixth ACM Symposium on Cloud Computing, SoCC 2015, Kohala Coast, Hawaii, USA, August 27-29, 2015. [Tags: Machine Learning] (link) (bib) (tweet)
2015ConferenceAndrew Crotty and Alex Galakatos and Kayhan Dursun and Tim Kraska and Ugur Cetintemel and Stanley B. Zdonik (2015). Tupleware: "Big" Data, Big Analytics, Small Clusters. In CIDR 2015, Seventh Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 4-7, 2015, Online Proceedings. [Tags: Machine Learning, Rack-Scale Computing] (pdf) (bib) (tweet)
2015WorkshopDalia Kaulakiene and Christian Thomsen and Torben Bach Pedersen and Ugur Cetintemel and Tim Kraska (2015). SpotADAPT: Spot-Aware (re-)Deployment of Analytical Processing Tasks on Amazon EC2. In Proceedings of the ACM Eighteenth International Workshop on Data Warehousing and OLAP, DOLAP 2015, Melbourne, VIC, Australia, October 19-23, 2015. [Tags: Cloud Computing] (link) (bib) (tweet)
2015Technical reportSanjay Krishnan and Jiannan Wang and Michael J. Franklin and Ken Goldberg and Tim Kraska (2015). Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views. CoRR, abs/1509.07454. [Tags: Cloud Computing] (link) (bib) (tweet)
2015Technical reportYeounoh Chung and Michael Lind Mortensen and Carsten Binnig and Tim Kraska (2015). Estimating the Impact of Unknown Unknowns on Aggregate Query Results. CoRR, abs/1507.05591. [Tags: Data Integration] (link) (bib) (tweet)
2015Technical reportCarsten Binnig and Ugur Cetintemel and Andrew Crotty and Alex Galakatos and Tim Kraska and Erfan Zamanian and Stanley B. Zdonik (2015). The End of Slow Networks: It's Time for a Redesign. CoRR, abs/1504.01048. [Tags: Rack-Scale Computing, Transaction Processing] (link) (bib) (tweet)
2015Technical reportJohn Meehan and Nesime Tatbul and Stanley B. Zdonik and Cansu Aslantas and Ugur Cetintemel and Jiang Du and Tim Kraska and Samuel Madden and David Maier and Andrew Pavlo and Michael Stonebraker and Kristin Tufte and Hao Wang (2015). S-Store: Streaming Meets Transaction Processing. CoRR, abs/1503.01143. [Tags: Stream Processing, Transaction Processing] (link) (bib) (tweet)
2015Technical reportEvan R. Sparks and Ameet Talwalkar and Michael J. Franklin and Michael I. Jordan and Tim Kraska (2015). TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries. CoRR, abs/1502.00068. [Tags: Machine Learning] (link) (bib) (tweet)
2015MiscAndrew Crotty and Alex Galakatos and Emanuel Zgraggen and Carsten Binnig and Tim Kraska (2015). Vizdom: Interactive Analytics through Pen and Touch. [Tags: Interactive Data Science Systems] (pdf) (bib) (tweet)
2015MiscAaron J. Elmore and Jennie Duggan and Mike Stonebraker and Magdalena Balazinska and Ugur Cetintemel and Vijay Gadepally and J. Heer and Bill Howe and Jeremy Kepner and Tim Kraska and Samuel Madden and David Maier and Timothy G. Mattson and S. Papadopoulos and J. Parkhurst and Nesime Tatbul and Manasi Vartak and Stan Zdonik (2015). A Demonstration of the BigDAWG Polystore System. [Tags: Data Integration] (pdf) (bib) (tweet)
2014JournalAndrew Crotty and Alex Galakatos and Tim Kraska (2014). Tupleware: Distributed Machine Learning on Small Clusters. IEEE Data Eng. Bull., 37(3), pp. 63–76. [Tags: Interactive Data Science Systems, Machine Learning, Rack-Scale Computing] (pdf) (bib) (tweet)
2014ConferenceBill Howe and Michael J. Franklin and Juliana Freire and James Frew and Tim Kraska and Raghu Ramakrishnan (2014). Should we all be teaching "intro to data science" instead of "intro to databases"?. In International Conference on Management of Data, SIGMOD 2014, Snowbird, UT, USA, June 22-27, 2014. [Tags: Interactive Data Science Systems, Machine Learning] (link) (bib) (tweet)
2014ConferenceJiannan Wang and Sanjay Krishnan and Michael J. Franklin and Ken Goldberg and Tim Kraska and Tova Milo (2014). A sample-and-clean framework for fast and accurate query processing on dirty data. In International Conference on Management of Data, SIGMOD 2014, Snowbird, UT, USA, June 22-27, 2014. [Tags: Data Integration] (link) (bib) (tweet)
2014ConferenceGene Pang and Tim Kraska and Michael J. Franklin and Alan Fekete (2014). PLANET: making progress with commit processing in unpredictable environments. In International Conference on Management of Data, SIGMOD 2014, Snowbird, UT, USA, June 22-27, 2014. [Tags: Cloud Computing, Transaction Processing] (link) (bib) (tweet)
2014Technical reportJiannan Wang and Guoliang Li and Tim Kraska and Michael J. Franklin and Jianhua Feng (2014). The Expected Optimal Labeling Order Problem for Crowdsourced Joins and Entity Resolution. CoRR, abs/1409.7472. [Tags: Data Integration, Crowd Computing] (link) (bib) (tweet)
2014Technical reportJiannan Wang and Guoliang Li and Tim Kraska and Michael J. Franklin and Jianhua Feng (2014). Leveraging Transitive Relations for Crowdsourced Joins. CoRR, abs/1408.6916. [Tags: Data Integration, Crowd Computing] (link) (bib) (tweet)
2014Technical reportAndrew Crotty and Alex Galakatos and Kayhan Dursun and Tim Kraska and Ugur Cetintemel and Stanley B. Zdonik (2014). Tupleware: Redefining Modern Analytics. CoRR, abs/1406.6667. [Tags: Machine Learning, Rack-Scale Computing] (link) (bib) (tweet)
2014MiscUgur Cetintemel and Jiang Du and Tim Kraska and Samuel Madden and David Maier and John Meehan and Andrew Pavlo and Michael Stonebraker and Erik Sutherland and Nesime Tatbul and Kristin Tufte and Hao Wang and Stanley B. Zdonik (2014). S-Store: A Streaming NewSQL System for Big Velocity Applications. [Tags: Stream Processing, Transaction Processing] (pdf) (bib) (tweet)
2014MiscElkhan Dadashov and Ugur Cetintemel and Tim Kraska (2014). Putting Analytics on the Spot: Or How to Lower the Cost for Analytics. [Tags: Cloud Computing] (link) (bib) (tweet)
2013ConferenceJan Schaffner and Tim Januschowski and Megan Kercher and Tim Kraska and Hasso Plattner and Michael J. Franklin and Dean Jacobs (2013). RTP: robust tenant placement for elastic in-memory database clusters. In Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2013, New York, NY, USA, June 22-27, 2013. [Tags: Cloud Computing] (link) (bib) (tweet)
2013ConferenceMichael Armbrust and Eric Liang and Tim Kraska and Armando Fox and Michael J. Franklin and David A. Patterson (2013). Generalized scale independence through incremental precomputation. In Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2013, New York, NY, USA, June 22-27, 2013. [Tags: Cloud Computing] (link) (bib) (tweet)
2013ConferenceJiannan Wang and Guoliang Li and Tim Kraska and Michael J. Franklin and Jianhua Feng (2013). Leveraging transitive relations for crowdsourced joins. In Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2013, New York, NY, USA, June 22-27, 2013. [Tags: Crowd Computing] (link) (bib) (tweet)
2013ConferenceEvan R. Sparks and Ameet Talwalkar and Virginia Smith and Jey Kottalam and Xinghao Pan and Joseph E. Gonzalez and Michael J. Franklin and Michael I. Jordan and Tim Kraska (2013). MLI: An API for Distributed Machine Learning. In 2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013. [Tags: Machine Learning] (link) (bib) (tweet)
2013ConferenceBeth Trushkowsky and Tim Kraska and Michael J. Franklin and Purnamrita Sarkar (2013). Crowdsourced enumeration queries. In 29th IEEE International Conference on Data Engineering, ICDE 2013, Brisbane, Australia, April 8-12, 2013. [Tags: Crowd Computing] (link) (bib) (tweet)
2013ConferenceBeth Trushkowsky and Tim Kraska and Michael J. Franklin (2013). A Framework for Adaptive Crowd Query Processing. In Human Computation and Crowdsourcing: Works in Progress and Demonstration Abstracts, An Adjunct to the Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, November 7-9, 2013, Palm Springs, CA, USA. [Tags: Crowd Computing] (link) (bib) (tweet)
2013ConferenceSean Louis Goldberg and Daisy Zhe Wang and Tim Kraska (2013). CASTLE: Crowd-Assisted System for Text Labeling and Extraction. In Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2013, November 7-9, 2013, Palm Springs, CA, USA. [Tags: Data Integration, Crowd Computing] (link) (bib) (tweet)
2013ConferenceTim Kraska and Gene Pang and Michael J. Franklin and Samuel Madden and Alan Fekete (2013). MDCC: multi-data center consistency. In Eighth Eurosys Conference 2013, EuroSys '13, Prague, Czech Republic, April 14-17, 2013. [Tags: Cloud Computing, Transaction Processing] (link) (bib) (tweet)
2013ConferenceTim Kraska and Ameet Talwalkar and John C. Duchi and Rean Griffith and Michael J. Franklin and Michael I. Jordan (2013). MLbase: A Distributed Machine-learning System. In CIDR 2013, Sixth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 6-9, 2013, Online Proceedings. [Tags: Machine Learning] (pdf) (bib) (tweet)
2013ConferenceGianluca Demartini and Beth Trushkowsky and Tim Kraska and Michael J. Franklin (2013). CrowdQ: Crowdsourced Query Understanding. In CIDR 2013, Sixth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 6-9, 2013, Online Proceedings. [Tags: Crowd Computing] (pdf) (bib) (tweet)
2013Technical reportEvan R. Sparks and Ameet Talwalkar and Virginia Smith and Jey Kottalam and Xinghao Pan and Joseph E. Gonzalez and Michael J. Franklin and Michael I. Jordan and Tim Kraska (2013). MLI: An API for Distributed Machine Learning. CoRR, abs/1310.5426. [Tags: Machine Learning] (link) (bib) (tweet)
2013MiscTim Kraska and Beth Trushkowsky (2013). The New Database Architectures. [Tags: Cloud Computing] (link) (bib) (tweet)
2013MiscTim Kraska (2013). Finding the Needle in the Big Data Systems Haystack. [Tags: Machine Learning, Cloud Computing] (link) (bib) (tweet)
2012JournalJiannan Wang and Tim Kraska and Michael J. Franklin and Jianhua Feng (2012). CrowdER: Crowdsourcing Entity Resolution. PVLDB, 5(11), pp. 1483–1494. [Tags: Crowd Computing] (pdf) (bib) (tweet)
2012WorkshopSimon Loesing and Martin Hentschel and Tim Kraska and Donald Kossmann (2012). Stormy: an elastic and highly available streaming service in the cloud. In Proceedings of the 2012 Joint EDBT/ICDT Workshops, Berlin, Germany, March 30, 2012. [Tags: Cloud Computing] (link) (bib) (tweet)
2012Technical reportJiannan Wang and Tim Kraska and Michael J. Franklin and Jianhua Feng (2012). CrowdER: Crowdsourcing Entity Resolution. CoRR, abs/1208.1927. [Tags: Crowd Computing, Data Integration] (link) (bib) (tweet)
2012Technical reportTim Kraska and Gene Pang and Michael J. Franklin and Samuel Madden (2012). MDCC: Multi-Data Center Consistency. CoRR, abs/1203.6049. [Tags: Transaction Processing, Cloud Computing] (link) (bib) (tweet)
2012Technical reportBeth Trushkowsky and Tim Kraska and Michael J. Franklin and Purnamrita Sarkar (2012). Getting It All from the Crowd. CoRR, abs/1202.2335. [Tags: Crowd Computing] (link) (bib) (tweet)
2011JournalPhilippe Bonnet and Stefan Manegold and Matias Bj\orling and Wei Cao and Javier Gonzalez and Joel A. Granados and Nancy Hall and Stratos Idreos and Milena Ivanova and Ryan Johnson and David Koop and Tim Kraska and René M\"uller and Dan Olteanu and Paolo Papotti and Christine Reilly and Dimitris Tsirogiannis and Cong Yu and Juliana Freire and Dennis Shasha (2011). Repeatability and workability evaluation of SIGMOD 2011. SIGMOD Record, 40(2), pp. 45–48. [Tags: Undefined] (link) (bib) (tweet)
2011JournalMichael Armbrust and Kristal Curtis and Tim Kraska and Armando Fox and Michael J. Franklin and David A. Patterson (2011). PIQL: Success-Tolerant Query Processing in the Cloud. PVLDB, 5(3), pp. 181–192. [Tags: Cloud Computing] (pdf) (bib) (tweet)
2011JournalAnHai Doan and Michael J. Franklin and Donald Kossmann and Tim Kraska (2011). Crowdsourcing Applications and Platforms: A Data Management Perspective. PVLDB, 4(12), pp. 1508–1509. [Tags: Crowd Computing] (pdf) (bib) (tweet)
2011ConferenceMichael J. Franklin and Donald Kossmann and Tim Kraska and Sukriti Ramesh and Reynold Xin (2011). CrowdDB: answering queries with crowdsourcing. In Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2011, Athens, Greece, June 12-16, 2011. [Tags: Crowd Computing] (link) (bib) (tweet)
2011Technical reportMichael Armbrust and Kristal Curtis and Tim Kraska and Armando Fox and Michael J. Franklin and David A. Patterson (2011). PIQL: Success-Tolerant Query Processing in the Cloud. CoRR, abs/1111.7166. [Tags: Cloud Computing] (link) (bib) (tweet)
2011MiscAmber Feng and Michael J. Franklin and Donald Kossmann and Tim Kraska and Samuel Madden and Sukriti Ramesh and Andrew Wang and Reynold Xin (2011). CrowdDB: Query Processing with the VLDB Crowd. [Tags: Crowd Computing] (pdf) (bib) (tweet)
2010JournalDonald Kossmann and Tim Kraska and Simon Loesing and Stephan Merkli and Raman Mittal and Flavio Pfaffhauser (2010). Cloudy: A Modular Cloud Storage System. PVLDB, 3(2), pp. 1533–1536. [Tags: Cloud Computing] (pdf) (bib) (tweet)
2010JournalDonald Kossmann and Tim Kraska (2010). Data Management in the Cloud: Promises, State-of-the-art, and Open Questions. Datenbank-Spektrum, 10(3), pp. 121–129. [Tags: Cloud Computing] (link) (bib) (tweet)
2010ConferenceDonald Kossmann and Tim Kraska and Simon Loesing (2010). An evaluation of alternative architectures for transaction processing in the cloud. In Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2010, Indianapolis, Indiana, USA, June 6-10, 2010. [Tags: Cloud Computing, Transaction Processing] (link) (bib) (tweet)
2009JournalRoger Bamford and Vinayak R. Borkar and Matthias Brantner and Peter M. Fischer and Daniela Florescu and David A. Graf and Donald Kossmann and Tim Kraska and Dan Muresan and Sorin Nasoi and Markos Zacharioudaki (2009). XQuery Reloaded. PVLDB, 2(2), pp. 1342–1353. [Tags: Semi-Structured Data] (pdf) (bib) (tweet)
2009JournalTim Kraska and Martin Hentschel and Gustavo Alonso and Donald Kossmann (2009). Consistency Rationing in the Cloud: Pay only when it matters. PVLDB, 2(1), pp. 253–264. [Tags: Cloud Computing, Transaction Processing] (pdf) (bib) (tweet)
2009ConferenceGhislain Fourny and Markus Pilman and Daniela Florescu and Donald Kossmann and Tim Kraska and Darin McBeath (2009). XQuery in the browser. In Proceedings of the 18th International Conference on World Wide Web, WWW 2009, Madrid, Spain, April 20-24, 2009. [Tags: Semi-Structured Data] (link) (bib) (tweet)
2009WorkshopCarsten Binnig and Donald Kossmann and Tim Kraska and Simon Loesing (2009). How is the weather tomorrow?: towards a benchmark for the cloud. In Proceedings of the 2nd International Workshop on Testing Database Systems, DBTest 2009, Providence, Rhode Island, USA, June 29, 2009. [Tags: Cloud Computing] (link) (bib) (tweet)
2008ConferenceGhislain Fourny and Donald Kossmann and Tim Kraska and Markus Pilman and Daniela Florescu (2008). XQuery in the browser. In Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2008, Vancouver, BC, Canada, June 10-12, 2008. [Tags: Semi-Structured Data] (link) (bib) (tweet)
2008ConferenceMatthias Brantner and Daniela Florescu and David A. Graf and Donald Kossmann and Tim Kraska (2008). Building a database on S3. In Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2008, Vancouver, BC, Canada, June 10-12, 2008. [Tags: Cloud Computing] (link) (bib) (tweet)
2007ConferenceIrina Botan and Peter M. Fischer and Daniela Florescu and Donald Kossmann and Tim Kraska and Rokas Tamosevicius (2007). Extending XQuery with Window Functions. In Proceedings of the 33rd International Conference on Very Large Data Bases, University of Vienna, Austria, September 23-27, 2007. [Tags: Semi-Structured Data, Stream Processing] (pdf) (bib) (tweet)
2006ConferenceTim Kraska and Uwe Röhm (2006). Genea: Schema-Aware Mapping of Ontologies into Relational Databases. In Proceedings of the 13th International Conference on Management of Data, December 14-16, 2006, Delhi, India. [Tags: Semi-Structured Data] (pdf) (bib) (tweet)
2006ConferenceJoshua Wing Kei Ho and Tristan Manwaring and Seok-Hee Hong and Uwe Röhm and David Cho Yau Fung and Kai Xu and Tim Kraska and David Hart (2006). PathBank: Web-Based Querying and Visualziation of an Integrated Biological Pathway Database. In Third International Conference on Computer Graphics, Imaging and Visualization (CGIV 2006), 26-28 July 2006, Sydney, Australia. [Tags: Semi-Structured Data] (link) (bib) (tweet)
Showing 1 to 172 of 172 entries

Note that the default author ordering at ETH is alphabetically.