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- affiliation: Microsoft, USA
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2020 – today
- 2024
[c48]Matteo Paganelli, Paolo Sottovia, Kwanghyun Park, Matteo Interlandi, Francesco Guerra:
Pushing ML Predictions into DBMSs (Extended Abstract). ICDE 2024: 5725-5726- [c47]Bojan Karlas, David Dao, Matteo Interlandi, Sebastian Schelter, Wentao Wu, Ce Zhang:
Data Debugging with Shapley Importance over Machine Learning Pipelines. ICLR 2024 - [c46]Madelon Hulsebos
, Matteo Interlandi, Shreya Shankar:
Eighth Workshop on Data Management for End-to-End Machine Learning (DEEM). SIGMOD Conference Companion 2024: 651-652 - [i20]Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan:
Towards Building Autonomous Data Services on Azure. CoRR abs/2405.01813 (2024) - 2023
- [j23]Chunwei Liu, Anna Pavlenko, Matteo Interlandi, Brandon Haynes:
A Deep Dive into Common Open Formats for Analytical DBMSs. Proc. VLDB Endow. 16(11): 3044-3056 (2023) - [j22]Rui Liu, Kwanghyun Park, Fotis Psallidas, Xiaoyong Zhu, Jinghui Mo, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos, Yuanyuan Tian, Jesús Camacho-Rodríguez:
Optimizing Data Pipelines for Machine Learning in Feature Stores. Proc. VLDB Endow. 16(13): 4230-4239 (2023) - [j21]Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim:
GPU Database Systems Characterization and Optimization. Proc. VLDB Endow. 17(3): 441-454 (2023) - [j20]Matteo Paganelli, Paolo Sottovia, Kwanghyun Park, Matteo Interlandi, Francesco Guerra:
Pushing ML Predictions Into DBMSs. IEEE Trans. Knowl. Data Eng. 35(10): 10295-10308 (2023) - [c45]Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi:
The Tensor Data Platform: Towards an AI-centric Database System. CIDR 2023 - [c44]Wei Cui, Qianxi Zhang, Spyros Blanas, Jesús Camacho-Rodríguez, Brandon Haynes, Yinan Li, Ravi Ramamurthy, Peng Cheng, Rathijit Sen, Matteo Interlandi:
Query Processing on Gaming Consoles. DaMoN 2023: 86-88 - [c43]Parimarjan Negi, Laurent Bindschaedler, Mohammad Alizadeh, Tim Kraska, Jyoti Leeka, Anja Gruenheid, Matteo Interlandi:
Unshackling Database Benchmarking from Synthetic Workloads. ICDE 2023: 3659-3662 - [c42]Matthias Boehm, Matteo Interlandi, Chris Jermaine:
Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques. SIGMOD Conference Companion 2023: 53-59 - [c41]Yiwen Zhu, Yuanyuan Tian, Joyce Cahoon, Subru Krishnan, Ankita Agarwal, Rana Alotaibi, Jesús Camacho-Rodríguez, Bibin Chundatt, Andrew Chung, Niharika Dutta, Andrew Fogarty, Anja Gruenheid, Brandon Haynes, Matteo Interlandi, Minu Iyer, Nick Jurgens, Sumeet Khushalani, Brian Kroth, Manoj Kumar, Jyoti Leeka, Sergiy Matusevych, Minni Mittal, Andreas Müller, Kartheek Muthyala, Harsha Nagulapalli, Yoonjae Park, Hiren Patel, Anna Pavlenko, Olga Poppe, Santhosh Ravindran, Karla Saur, Rathijit Sen, Steve Suh, Arijit Tarafdar, Kunal Waghray, Demin Wang, Carlo Curino, Raghu Ramakrishnan:
Towards Building Autonomous Data Services on Azure. SIGMOD Conference Companion 2023: 217-224 - [i19]Jiashen Cao, Rathijit Sen, Matteo Interlandi, Joy Arulraj, Hyesoon Kim:
Revisiting Query Performance in GPU Database Systems. CoRR abs/2302.00734 (2023) - 2022
- [j19]Dong He, Supun Chathuranga Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi:
Query Processing on Tensor Computation Runtimes. Proc. VLDB Endow. 15(11): 2811-2825 (2022) - [j18]Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi:
Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem. Proc. VLDB Endow. 15(12): 3598-3601 (2022) - [j17]Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Jordan Henkel, Matteo Interlandi, Subru Krishnan, Brian Kroth, K. Venkatesh Emani, Wentao Wu, Ce Zhang, Markus Weimer, Avrilia Floratou, Carlo Curino, Konstantinos Karanasos:
Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. SIGMOD Rec. 51(2): 30-37 (2022) - [c40]Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos:
End-to-end Optimization of Machine Learning Prediction Queries. SIGMOD Conference 2022: 587-601 - [c39]Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc T. Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal:
Deploying a Steered Query Optimizer in Production at Microsoft. SIGMOD Conference 2022: 2299-2311 - [i18]Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi:
Query Processing on Tensor Computation Runtimes. CoRR abs/2203.01877 (2022) - [i17]Bojan Karlas, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang:
Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines. CoRR abs/2204.11131 (2022) - [i16]Kwanghyun Park, Karla Saur, Dalitso Banda, Rathijit Sen, Matteo Interlandi, Konstantinos Karanasos:
End-to-end Optimization of Machine Learning Prediction Queries. CoRR abs/2206.00136 (2022) - [i15]Yuki Asada, Victor Fu, Apurva Gandhi, Advitya Gemawat, Lihao Zhang, Dong He, Vivek Gupta, Ehi Nosakhare, Dalitso Banda, Rathijit Sen, Matteo Interlandi:
Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem. CoRR abs/2209.04579 (2022) - [i14]Wangda Zhang, Matteo Interlandi, Paul Mineiro, Shi Qiao, Nasim Ghazanfari, Karlen Lie, Marc T. Friedman, Rafah Hosn, Hiren Patel, Alekh Jindal:
Deploying a Steered Query Optimizer in Production at Microsoft. CoRR abs/2210.13625 (2022) - [i13]Apurva Gandhi, Yuki Asada, Victor Fu, Advitya Gemawat, Lihao Zhang, Rathijit Sen, Carlo Curino, Jesús Camacho-Rodríguez, Matteo Interlandi:
The Tensor Data Platform: Towards an AI-centric Database System. CoRR abs/2211.02753 (2022) - 2021
- [j16]Dimitrios Koutsoukos, Supun Nakandala, Konstantinos Karanasos, Karla Saur, Gustavo Alonso, Matteo Interlandi:
Tensors: An abstraction for general data processing. Proc. VLDB Endow. 14(10): 1797-1804 (2021) - [j15]Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal:
Phoebe: A Learning-based Checkpoint Optimizer. Proc. VLDB Endow. 14(11): 2505-2518 (2021) - [j14]Alekh Jindal, Matteo Interlandi:
Machine Learning for Cloud Data Systems: the Promise, the Progress, and the Path Forward. Proc. VLDB Endow. 14(12): 3202-3205 (2021) - [j13]Gyeong-In Yu, Saeed Amizadeh, Sehoon Kim, Artidoro Pagnoni, Ce Zhang, Byung-Gon Chun, Markus Weimer, Matteo Interlandi:
WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Modele. Proc. VLDB Endow. 15(1): 11-20 (2021) - [j12]Youfu Li, Matteo Interlandi, Fotis Psallidas, Wei Wang, Carlo Zaniolo:
SEIZE: Runtime Inspection for Parallel Dataflow Systems. IEEE Trans. Parallel Distributed Syst. 32(4): 842-854 (2021) - [c38]Matteo Paganelli, Paolo Sottovia, Antonio Maccioni, Matteo Interlandi, Francesco Guerra:
Using Descriptions for Explaining Entity Matches (Discussion Paper). SEBD 2021: 291-298 - [c37]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 - [c36]Francesco Del Buono, Matteo Paganelli, Paolo Sottovia, Matteo Interlandi, Francesco Guerra:
Transforming ML Predictive Pipelines into SQL with MASQ. SIGMOD Conference 2021: 2696-2700 - [i12]Yiwen Zhu, Matteo Interlandi, Abhishek Roy, Krishnadhan Das, Hiren Patel, Malay Bag, Hitesh Sharma, Alekh Jindal:
Phoebe: A Learning-based Checkpoint Optimizer. CoRR abs/2110.02313 (2021) - 2020
- [j11]Matteo Paganelli, Paolo Sottovia, Antonio Maccioni, Matteo Interlandi, Francesco Guerra:
Explaining data with descriptions. Inf. Syst. 92: 101549 (2020) - [c35]Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu:
Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML. CIDR 2020 - [c34]Konstantinos Karanasos, Matteo Interlandi, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Doris Xin, Supun Nakandala, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino:
Extending Relational Query Processing with ML Inference. CIDR 2020 - [c33]Youfu Li, Matteo Interlandi, Fotis Psallidas, Wei Wang, Carlo Zaniolo:
SEIZE User Desired Moments: Runtime Inspection for Parallel Dataflow Systems. ICDCS 2020: 1199-1200 - [c32]Bojan Karlas, Matteo Interlandi, Cédric Renggli, Wentao Wu, Ce Zhang, Deepak Mukunthu Iyappan Babu, Jordan Edwards, Chris Lauren, Andy Xu, Markus Weimer:
Building Continuous Integration Services for Machine Learning. KDD 2020: 2407-2415 - [c31]Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi:
A Tensor Compiler for Unified Machine Learning Prediction Serving. OSDI 2020: 899-917 - [i11]Supun Nakandala, Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi:
A Tensor Compiler for Unified Machine Learning Prediction Serving. CoRR abs/2010.04804 (2020)
2010 – 2019
- 2019
- [c30]Matteo Paganelli, Paolo Sottovia, Antonio Maccioni, Matteo Interlandi, Francesco Guerra:
Understanding Data in the Blink of an Eye. CIKM 2019: 2885-2888 - [c29]Lana Ramjit, Matteo Interlandi, Eugene Wu, Ravi Netravali:
Acorn: Aggressive Result Caching in Distributed Data Processing Frameworks. SoCC 2019: 206-219 - [c28]Yaoqing Yang, Matteo Interlandi, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer:
Coded Elastic Computing. ISIT 2019: 2654-2658 - [c27]Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu:
Machine Learning at Microsoft with ML.NET. KDD 2019: 2448-2458 - [i10]Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Eric Erhardt, Costin Eseanu, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Shon Katzenberger, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Sarthak Shah, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu:
Machine Learning at Microsoft with ML .NET. CoRR abs/1905.05715 (2019) - [i9]Gyeong-In Yu, Saeed Amizadeh, Artidoro Pagnoni, Byung-Gon Chun, Markus Weimer, Matteo Interlandi:
Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach. CoRR abs/1906.03822 (2019) - [i8]Ashvin Agrawal, Rony Chatterjee, Carlo Curino, Avrilia Floratou, Neha Godwal, Matteo Interlandi, Alekh Jindal, Konstantinos Karanasos, Subru Krishnan, Brian Kroth, Jyoti Leeka, Kwanghyun Park, Hiren Patel, Olga Poppe, Fotis Psallidas, Raghu Ramakrishnan, Abhishek Roy, Karla Saur, Rathijit Sen, Markus Weimer, Travis Wright, Yiwen Zhu:
Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML. CoRR abs/1909.00084 (2019) - [i7]Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandala, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino:
Extending Relational Query Processing with ML Inference. CoRR abs/1911.00231 (2019) - [i6]Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Matteo Interlandi, Avrilia Floratou, Konstantinos Karanasos, Wentao Wu, Ce Zhang, Subru Krishnan, Carlo Curino, Markus Weimer:
Data Science through the looking glass and what we found there. CoRR abs/1912.09536 (2019) - 2018
- [j10]Matteo Interlandi, Tyson Condie:
Supporting Data Provenance in Data-Intensive Scalable Computing Systems. IEEE Data Eng. Bull. 41(1): 63-73 (2018) - [j9]Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Markus Weimer, Matteo Interlandi:
From the Edge to the Cloud: Model Serving in ML.NET. IEEE Data Eng. Bull. 41(4): 46-53 (2018) - [j8]Tyson Condie, Ariyam Das, Matteo Interlandi, Alexander Shkapsky, Mohan Yang, Carlo Zaniolo:
Scaling-up reasoning and advanced analytics on BigData. Theory Pract. Log. Program. 18(5-6): 806-845 (2018) - [j7]Matteo Interlandi, Letizia Tanca:
A datalog-based computational model for coordination-free, data-parallel systems. Theory Pract. Log. Program. 18(5-6): 874-927 (2018) - [j6]Matteo Interlandi, Ari Ekmekji, Kshitij Shah, Muhammad Ali Gulzar, Sai Deep Tetali, Miryung Kim, Todd D. Millstein, Tyson Condie:
Adding data provenance support to Apache Spark. VLDB J. 27(5): 595-615 (2018) - [c26]Carlo Zaniolo, Mohan Yang, Matteo Interlandi, Ariyam Das, Alexander Shkapsky, Tyson Condie:
Declarative BigData Algorithms via Aggregates and Relational Database Dependencies. AMW 2018 - [c25]Youfu Li, Mingda Li, Ling Ding, Matteo Interlandi:
RIOS: Runtime Integrated Optimizer for Spark. SoCC 2018: 275-287 - [c24]Carlo Zaniolo, Mohan Yang, Matteo Interlandi, Ariyam Das, Alexander Shkapsky, Tyson Condie:
Declarative Algorithms in Datalog with Extrema: Their Formal Semantics Simplified. ICLP (Technical Communications) 2018: 9:1-9:3 - [c23]Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Markus Weimer, Matteo Interlandi:
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems. OSDI 2018: 611-626 - [i5]Tyson Condie, Ariyam Das, Matteo Interlandi, Alexander Shkapsky, Mohan Yang, Carlo Zaniolo:
Scaling-Up Reasoning and Advanced Analytics on BigData. CoRR abs/1807.02957 (2018) - [i4]Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Marco Domenico Santambrogio, Markus Weimer, Matteo Interlandi:
PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems. CoRR abs/1810.06115 (2018) - [i3]Yaoqing Yang, Matteo Interlandi, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer:
Coded Elastic Computing. CoRR abs/1812.06411 (2018) - 2017
- [j5]Byung-Gon Chun, Tyson Condie, Yingda Chen, Brian Cho, Andrew Chung, Carlo Curino, Chris Douglas, Matteo Interlandi, Beomyeol Jeon, Joo Seong Jeong, Gyewon Lee, Yunseong Lee, Tony Majestro, Dahlia Malkhi, Sergiy Matusevych, Brandon Myers, Mariia Mykhailova, Shravan M. Narayanamurthy, Joseph Noor, Raghu Ramakrishnan, Sriram Rao, Russell Sears, Beysim Sezgin, Taegeon Um, Julia Wang, Markus Weimer, Youngseok Yang:
Apache REEF: Retainable Evaluator Execution Framework. ACM Trans. Comput. Syst. 35(2): 5:1-5:31 (2017) - [j4]Carlo Zaniolo, Mohan Yang, Ariyam Das, Alexander Shkapsky, Tyson Condie, Matteo Interlandi:
Fixpoint semantics and optimization of recursive Datalog programs with aggregates. Theory Pract. Log. Program. 17(5-6): 1048-1065 (2017) - [c22]Muhammad Ali Gulzar, Matteo Interlandi, Xueyuan Han, Mingda Li, Tyson Condie, Miryung Kim:
Automated debugging in data-intensive scalable computing. SoCC 2017: 520-534 - [c21]Alberto Scolari, Yunseong Lee, Markus Weimer, Matteo Interlandi:
Towards Accelerating Generic Machine Learning Prediction Pipelines. ICCD 2017: 431-434 - [c20]Matteo Interlandi, Julien Lacroix, Omar Boucelma, Francesco Guerra:
Cleaning MapReduce Workflows. HPCS 2017: 74-78 - [c19]Muhammad Ali Gulzar, Matteo Interlandi, Tyson Condie, Miryung Kim:
Debugging Big Data Analytics in Spark with BigDebug. SIGMOD Conference 2017: 1627-1630 - [i2]Carlo Zaniolo, Mohan Yang, Matteo Interlandi, Ariyam Das, Alexander Shkapsky, Tyson Condie:
Fixpoint Semantics and Optimization of Recursive Datalog Programs with Aggregates. CoRR abs/1707.05681 (2017) - 2016
- [j3]Sonia Bergamaschi, Francesco Guerra, Matteo Interlandi, Raquel Trillo Lado, Yannis Velegrakis:
Combining user and database perspective for solving keyword queries over relational databases. Inf. Syst. 55: 1-19 (2016) - [c18]Carlo Zaniolo, Mohan Yang, Ariyam Das, Matteo Interlandi:
The Magic of Pushing Extrema into Recursion: Simple, Powerful Datalog Programs. AMW 2016 - [c17]Muhuan Huang, Di Wu, Cody Hao Yu, Zhenman Fang, Matteo Interlandi, Tyson Condie, Jason Cong:
Programming and Runtime Support to Blaze FPGA Accelerator Deployment at Datacenter Scale. SoCC 2016: 456-469 - [c16]Matteo Interlandi, Sai Deep Tetali, Muhammad Ali Gulzar, Joseph Noor, Tyson Condie, Miryung Kim, Todd D. Millstein:
Optimizing Interactive Development of Data-Intensive Applications. SoCC 2016: 510-522 - [c15]Muhammad Ali Gulzar, Xueyuan Han, Matteo Interlandi, Shaghayegh Mardani, Sai Deep Tetali, Todd D. Millstein, Miryung Kim:
Interactive Debugging for Big Data Analytics. HotCloud 2016 - [c14]Muhammad Ali Gulzar, Matteo Interlandi, Seunghyun Yoo, Sai Deep Tetali, Tyson Condie, Todd D. Millstein, Miryung Kim:
BigDebug: debugging primitives for interactive big data processing in spark. ICSE 2016: 784-795 - [c13]Alexander Shkapsky, Mohan Yang, Matteo Interlandi, Hsuan Chiu, Tyson Condie, Carlo Zaniolo:
Big Data Analytics with Datalog Queries on Spark. SIGMOD Conference 2016: 1135-1149 - [c12]Muhammad Ali Gulzar, Matteo Interlandi, Tyson Condie, Miryung Kim:
BigDebug: interactive debugger for big data analytics in Apache Spark. SIGSOFT FSE 2016: 1033-1037 - 2015
- [j2]Matteo Interlandi, Kshitij Shah, Sai Deep Tetali, Muhammad Ali Gulzar, Seunghyun Yoo, Miryung Kim, Todd D. Millstein, Tyson Condie:
Titian: Data Provenance Support in Spark. Proc. VLDB Endow. 9(3): 216-227 (2015) - [c11]Matteo Interlandi, Letizia Tanca:
On the CALM Principle for BSP Computation. AMW 2015 - [c10]Matteo Interlandi, Nan Tang:
Proof positive and negative in data cleaning. ICDE 2015: 18-29 - 2014
- [c9]Matteo Interlandi, Giovanni Simonini, Sonia Bergamaschi:
Towards Declarative Imperative Data-parallel Systems. SEBD 2014: 97-104 - [i1]Matteo Interlandi, Letizia Tanca:
On the CALM Principle for Bulk Synchronous Parallel Computation. CoRR abs/1405.7264 (2014) - 2013
- [j1]Sonia Bergamaschi, Francesco Guerra, Matteo Interlandi, Raquel Trillo Lado, Yannis Velegrakis:
QUEST: A Keyword Search System for Relational Data based on Semantic and Machine Learning Techniques. Proc. VLDB Endow. 6(12): 1222-1225 (2013) - [c8]Matteo Interlandi, Letizia Tanca, Sonia Bergamaschi:
Datalog in Time and Space, Synchronously. AMW 2013 - [c7]Sonia Bergamaschi, Francesco Guerra, Matteo Interlandi, Silvia Rota, Raquel Trillo, Yannis Velegrakis:
Using a HMM based approach for mapping keyword queries into database terms. SEBD 2013: 239-246 - 2012
- [c6]Matteo Interlandi:
Reasoning about Knowledge in Distributed Systems Using Datalog. Datalog 2012: 99-110 - [c5]Matteo Interlandi:
Knowlog: A Declarative Language for Reasoning about Knowledge in Distributed Systems. ER 2012: 572-577 - [c4]Sonia Bergamaschi, Matteo Interlandi, Mario Longo, Laura Po, Maurizio Vincini:
A Meta-language for MDX Queries in eLog Business Solution. ICDE 2012: 1417-1428 - [c3]Matteo Interlandi:
Enhancing Datalog with Epistemic Operators to Reason About Knowledge in Distributed Systems. SEBD 2012: 265-270 - 2011
- [c2]Sonia Bergamaschi, Fabio Ferrari, Matteo Interlandi, Maurizio Vincini:
MediaPresenter, a Web Platform for Multimedia Content Management. SEBD 2011: 437- - 2010
- [c1]Luca Pazzi, Matteo Interlandi, Marco Pradelli:
Automatic Fault Behavior Detection and Modeling by a State-Based Specification Method. HASE 2010: 166-167
Coauthor Index
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