Arun Kumar - RankMe

82 papers A 3Misc 1Journal 53Unranked 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MICRO: A Lightweight Middleware for Optimizing Cross-store Cross-model Graph-Relation Joins [Technical Report]. CoRR Xiuwen Zheng, Arun Kumar, Amarnath Gupta
2025	J	`jnl`	SNAILS: Schema Naming Assessments for Improved LLM-Based SQL Inference. Proc. ACM Manag. Data Kyle Luoma, Arun Kumar
2025	J	`jnl`	The Cambridge Report on Database Research. CoRR Anastasia Ailamaki, Samuel Madden, Daniel Abadi, Gustavo Alonso, Sihem Amer-Yahia, Magdalena Balazinska, Philip A. Bernstein, Peter Boncz, Michael J. Cafarella, Surajit Chaudhuri, Susan B. Davidson, David J. DeWitt, Yanlei Diao, Xin Luna Dong, Michael J. Franklin, Juliana Freire, Johannes Gehrke, Alon Y. Halevy, Joseph M. Hellerstein, Mark D. Hill, Stratos Idreos, Yannis E. Ioannidis, Christoph Koch, Donald Kossmann, Tim Kraska, Arun Kumar, Guoliang Li, Volker Markl, Renée J. Miller, C. Mohan, Thomas Neumann, Beng Chin Ooi, Fatma Ozcan, Aditya G. Parameswaran, Ippokratis Pandis, Jignesh M. Patel, Andrew Pavlo, Danica Porobic, Viktor Sanca, Michael Stonebraker, Julia Stoyanovich, Dan Suciu, Wang-Chiew Tan, Shivaram Venkataraman, Matei Zaharia, Stanley B. Zdonik
2024	A	`conf`	Generating Cross-model Analytics Workloads Using LLMs. CIKM Xiuwen Zheng, Arun Kumar, Amarnath Gupta
2024	J	`jnl`	How do Categorical Duplicates Affect ML? A New Benchmark and Empirical Analyses. Proc. VLDB Endow. Vraj Shah, Thomas J. Parashos, Arun Kumar
2024	—	`ed.`	Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), Bangalore, India, January 4-7, 2024 COMAD/CODS Sriraam Natarajan, Indrajit Bhattacharya, Richa Singh, Arun Kumar, Sayan Ranu, Kalika Bali, Abinaya K.
2023	J	`jnl`	An Optimized Tri-store System for Multi-model Data Analytics. CoRR Xiuwen Zheng, Subhasis Dasgupta, Arun Kumar, Amarnath Gupta
2023	Misc	`conf`	Database-Aware ASR Error Correction for Speech-to-SQL Parsing. ICASSP Yutong Shao, Arun Kumar, Ndapa Nakashole
2023	J	`jnl`	Lotan: Bridging the Gap between GNNs and Scalable Graph Analytics Engines. Proc. VLDB Endow. Yuhao Zhang, Arun Kumar
2023	J	`jnl`	Saturn: An Optimized Data System for Large Model Deep Learning Workloads. CoRR Kabir Nagrecha, Arun Kumar
2023	J	`jnl`	Saturn: An Optimized Data System for Multi-Large-Model Deep Learning Workloads. Proc. VLDB Endow. Kabir Nagrecha, Arun Kumar
2023	J	`jnl`	Saturn: Efficient Multi-Large-Model Deep Learning. CoRR Kabir Nagrecha, Arun Kumar
2022	J	`jnl`	Database Education at UC San Diego. SIGMOD Rec. Arun Kumar, Alin Deutsch, Amarnath Gupta, Yannis Papakonstantinou, Babak Salimi, Victor Vianu
2022	J	`jnl`	Diversity and Inclusion Activities in Database Conferences: A 2021 Report. SIGMOD Rec. Sihem Amer-Yahia, Yael Amsterdamer, Sourav S. Bhowmick, Angela Bonifati, Philippe Bonnet, Renata Borovica-Gajic, Barbara Catania, Tania Cerquitelli, Silvia Chiusano, Panos K. Chrysanthis, Carlo Curino, Jérôme Darmont, Amr El Abbadi, Avrilia Floratou, Juliana Freire, Alekh Jindal, Vana Kalogeraki, Georgia Koutrika, Arun Kumar, Sujaya Maiyya, Alexandra Meliou, Madhulika Mohanty, Felix Naumann, Nele Sina Noack, Fatma Özcan, Liat Peterfreund, Wenny Rahayu, Wang-Chiew Tan, Yuanyuan Tian, Pinar Tözün, Genoveva Vargas-Solar, Neeraja J. Yadwadkar, Meihui Zhang
2022	—	`conf`	Nautilus: An Optimized System for Deep Transfer Learning over Evolving Training Datasets. SIGMOD Conference Supun Nakandala, Arun Kumar
2022	J	`jnl`	Structured Data Representation in Natural Language Interfaces. IEEE Data Eng. Bull. Yutong Shao, Arun Kumar, Ndapa Nakashole
2022	J	`jnl`	VLDB Scalable Data Science Category: The Inaugural Year. SIGMOD Rec. Arun Kumar, Alon Y. Halevy, Nesime Tatbul
2021	—	`conf`	Automation of Data Prep, ML, and Data Science: New Cure or Snake Oil? SIGMOD Conference Arun Kumar
2021	A	`conf`	Cerebro: A Layered Data Platform for Scalable Deep Learning. CIDR Arun Kumar, Supun Nakandala, Yuhao Zhang, Side Li, Advitya Gemawat, Kabir Nagrecha
2021	J	`jnl`	Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches. Proc. VLDB Endow. Yuhao Zhang, Frank Mcquillan, Nandish Jayaram, Nikhil Kak, Ekta Khanna, Orhan Kislal, Domino Valdano, Arun Kumar
2021	J	`jnl`	Errata for "Cerebro: A Data System for Optimized Deep Learning Model Selection". Proc. VLDB Endow. Supun Nakandala, Yuhao Zhang, Arun Kumar
2021	J	`jnl`	Front Matter. Proc. VLDB Endow. Arun Kumar, Alon Y. Halevy, Nesime Tatbul
2021	J	`jnl`	Hydra: A System for Large Multi-Model Deep Learning. CoRR Kabir Nagrecha, Arun Kumar
2021	J	`jnl`	Intermittent Human-in-the-Loop Model Selection using Cerebro: A Demonstration. Proc. VLDB Endow. Liangde Li, Supun Chathuranga Nakandala, Arun Kumar
2021	J	`jnl`	Letter from the Rising Star Award Winner. IEEE Data Eng. Bull. Arun Kumar
2021	J	`jnl`	Processing Analytical Queries in the AWESOME Polystore [Information Systems Architectures]. CoRR Xiuwen Zheng, Subhasis Dasgupta, Arun Kumar, Amarnath Gupta
2021	J	`jnl`	Towards A Polyglot Framework for Factorized ML. Proc. VLDB Endow. David Justo, Shaoqing Yi, Lukas Stadler, Nadia Polikarpova, Arun Kumar
2021	—	`conf`	Towards Benchmarking Feature Type Inference for AutoML Platforms. SIGMOD Conference Vraj Shah, Jonathan Lacanlale, Premanand Kumar, Kevin Yang, Arun Kumar
2021	J	`jnl`	Towards an Optimized GROUP BY Abstraction for Large-Scale Machine Learning. Proc. VLDB Endow. Side Li, Arun Kumar
2021	J	`jnl`	VLDB Panel Summary: "The Future of Data(base) Education: Is the Cow Book Dead?". SIGMOD Rec. Zack Ives, Johannes Gehrke, Jana Giceva, Arun Kumar, Rachel Pottinger
2020	J	`jnl`	Cerebro: A Data System for Optimized Deep Learning Model Selection. Proc. VLDB Endow. Supun Nakandala, Yuhao Zhang, Arun Kumar
2020	J	`jnl`	Incremental and Approximate Computations for Accelerating Deep CNN Inference. ACM Trans. Database Syst. Supun Nakandala, Kabir Nagrecha, Arun Kumar, Yannis Papakonstantinou
2020	J	`jnl`	Query Optimization for Faster Deep CNN Explanations. SIGMOD Rec. Supun Nakandala, Arun Kumar, Yannis Papakonstantinou
2020	—	`conf`	SpeakQL: Towards Speech-driven Multimodal Querying of Structured Data. SIGMOD Conference Vraj Shah, Side Li, Arun Kumar, Lawrence K. Saul
2020	J	`jnl`	Understanding and Benchmarking the Impact of GDPR on Database Systems. Proc. VLDB Endow. Supreeth Shastri, Vinay Banakar, Melissa Wasserman, Arun Kumar, Vijay Chidambaram
2020	—	`conf`	Vista: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale. SIGMOD Conference Supun Nakandala, Arun Kumar
2019	—	`conf`	Cerebro: Efficient and Reproducible Model Selection on Deep Learning Systems. DEEM@SIGMOD Supun Nakandala, Yuhao Zhang, Arun Kumar
2019	—	`book`	Data Management in Machine Learning Systems Matthias Boehm, Arun Kumar, Jun Yang
2019	J	`jnl`	Demonstration of Krypton: Optimized CNN Inference for Occlusion-based Deep CNN Explanations. Proc. VLDB Endow. Allen Ordookhanians, Xin Li, Supun Nakandala, Arun Kumar
2019	—	`conf`	Demonstration of Nimbus: Model-based Pricing for Machine Learning in a Data Marketplace. SIGMOD Conference Lingjiao Chen, Hongyi Wang, Leshang Chen, Paraschos Koutris, Arun Kumar
2019	—	`conf`	Demonstration of SpeakQL: Speech-driven Multimodal Querying of Structured Data. SIGMOD Conference Vraj Shah, Side Li, Kevin Yang, Arun Kumar, Lawrence K. Saul
2019	—	`conf`	Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra. SIGMOD Conference Side Li, Lingjiao Chen, Arun Kumar
2019	J	`jnl`	Guest Editors' Introduction to the Special Section on the 33rd International Conference on Data Engineering (ICDE 2017). IEEE Trans. Knowl. Data Eng. Wolfgang Gatterbauer, Arun Kumar
2019	—	`conf`	Incremental and Approximate Inference for Faster Occlusion-based Deep CNN Explanations. SIGMOD Conference Supun Nakandala, Arun Kumar, Yannis Papakonstantinou
2019	J	`jnl`	Panorama: A Data System for Unbounded Vocabulary Querying over Video. Proc. VLDB Endow. Yuhao Zhang, Arun Kumar
2019	J	`jnl`	Predicting Eating Events in Free Living Individuals - A Technical Report. CoRR Jiayi Wang, Jiue-An Yang, Supun Nakandala, Arun Kumar, Marta M. Jankowska
2019	—	`conf`	Predicting Eating Events in Free Living Individuals. eScience Jiue-An Yang, Jiayi Wang, Supun Nakandala, Arun Kumar, Marta M. Jankowska
2019	—	`conf`	Predicting Eating Events in Free Living Individuals. eScience Jiue-An Yang, Jiayi Wang, Supun Nakandala, Arun Kumar, Marta M. Jankowska
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR 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 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
2019	—	`conf`	The ML Data Prep Zoo: Towards Semi-Automatic Data Preparation for ML. DEEM@SIGMOD Vraj Shah, Arun Kumar
2019	—	`conf`	Towards Model-based Pricing for Machine Learning in a Data Marketplace. SIGMOD Conference Lingjiao Chen, Paraschos Koutris, Arun Kumar
2019	—	`conf`	Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent. SIGMOD Conference Fengan Li, Lingjiao Chen, Yijing Zeng, Arun Kumar, Xi Wu, Jeffrey F. Naughton, Jignesh M. Patel
2019	J	`jnl`	Understanding and Benchmarking the Impact of GDPR on Database Systems. CoRR Supreeth Shastri, Vinay Banakar, Melissa Wasserman, Arun Kumar, Vijay Chidambaram
2018	J	`jnl`	In-RDBMS Hardware Acceleration of Advanced Analytics. CoRR Divya Mahajan, Joon Kyung Kim, Jacob Sacks, Adel Ardalan, Arun Kumar, Hadi Esmaeilzadeh
2018	J	`jnl`	In-RDBMS Hardware Acceleration of Advanced Analytics. Proc. VLDB Endow. Divya Mahajan, Joon Kyung Kim, Jacob Sacks, Adel Ardalan, Arun Kumar, Hadi Esmaeilzadeh
2018	J	`jnl`	Model-based Pricing for Machine Learning in a Data Marketplace. CoRR Lingjiao Chen, Paraschos Koutris, Arun Kumar
2017	J	`jnl`	Are Key-Foreign Key Joins Safe to Avoid when Learning High-Capacity Classifiers? Proc. VLDB Endow. Vraj Shah, Arun Kumar, Xiaojin Zhu
2017	—	`conf`	Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics. SIGMOD Conference Xi Wu, Fengan Li, Arun Kumar, Kamalika Chaudhuri, Somesh Jha, Jeffrey F. Naughton
2017	—	`conf`	Data Management in Machine Learning: Challenges, Techniques, and Systems. SIGMOD Conference Arun Kumar, Matthias Boehm, Jun Yang
2017	—	`conf`	Model-based Pricing: Do Not Pay for More than What You Learn! DEEM@SIGMOD Lingjiao Chen, Paraschos Koutris, Arun Kumar
2017	—	`conf`	SpeakQL: Towards Speech-driven Multi-modal Querying. HILDA@SIGMOD Dharmil Chandarana, Vraj Shah, Arun Kumar, Lawrence K. Saul
2017	J	`jnl`	Stop That Join! Discarding Dimension Tables when Learning High Capacity Classifiers. CoRR Vraj Shah, Arun Kumar, Xiaojin Zhu
2017	J	`jnl`	Towards Linear Algebra over Normalized Data. Proc. VLDB Endow. Lingjiao Chen, Arun Kumar, Jeffrey F. Naughton, Jignesh M. Patel
2017	J	`jnl`	When Lempel-Ziv-Welch Meets Machine Learning: A Case Study of Accelerating Machine Learning using Coding. CoRR Fengan Li, Lingjiao Chen, Arun Kumar, Jeffrey F. Naughton, Jignesh M. Patel, Xi Wu
2016	J	`jnl`	Differentially Private Stochastic Gradient Descent for in-RDBMS Analytics. CoRR Xi Wu, Arun Kumar, Kamalika Chaudhuri, Somesh Jha, Jeffrey F. Naughton
2016	J	`jnl`	Materialization Optimizations for Feature Selection Workloads. ACM Trans. Database Syst. Ce Zhang, Arun Kumar, Christopher Ré
2016	—	`conf`	To Join or Not to Join?: Thinking Twice about Joins before Feature Selection. SIGMOD Conference Arun Kumar, Jeffrey F. Naughton, Jignesh M. Patel, Xiaojin Zhu
2016	J	`jnl`	Towards Linear Algebra over Normalized Data. CoRR Lingjiao Chen, Arun Kumar, Jeffrey F. Naughton, Jignesh M. Patel
2015	J	`jnl`	Demonstration of Santoku: Optimizing Machine Learning over Normalized Data. Proc. VLDB Endow. Arun Kumar, Mona Jalal, Boqun Yan, Jeffrey F. Naughton, Jignesh M. Patel
2015	—	`conf`	Learning Generalized Linear Models Over Normalized Data. SIGMOD Conference Arun Kumar, Jeffrey F. Naughton, Jignesh M. Patel
2015	J	`jnl`	Model Selection Management Systems: The Next Frontier of Advanced Analytics. SIGMOD Rec. Arun Kumar, Robert McCann, Jeffrey F. Naughton, Jignesh M. Patel
2014	—	`conf`	Materialization optimizations for feature selection workloads. SIGMOD Conference Ce Zhang, Arun Kumar, Christopher Ré
2013	A	`conf`	Brainwash: A Data System for Feature Engineering. CIDR Michael R. Anderson, Dolan Antenucci, Victor Bittorf, Matthew Burgess, Michael J. Cafarella, Arun Kumar, Feng Niu, Yongjoo Park, Christopher Ré, Ce Zhang
2013	J	`jnl`	Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System. Proc. VLDB Endow. Pradap Konda, Arun Kumar, Christopher Ré, Vaishnavi Sashikanth
2013	J	`jnl`	Hazy: Making it Easier to Build and Maintain Big-data Analytics. ACM Queue Arun Kumar, Feng Niu, Christopher Ré
2013	J	`jnl`	Hazy: making it easier to build and maintain big-data analytics. Commun. ACM Arun Kumar, Feng Niu, Christopher Ré
2012	J	`jnl`	The MADlib Analytics Library or MAD Skills, the SQL CoRR Joseph M. Hellerstein, Christopher Ré, Florian Schoppmann, Daisy Zhe Wang, Eugene Fratkin, Aleksander Gorajek, Kee Siong Ng, Caleb Welton, Xixuan Feng, Kun Li, Arun Kumar
2012	J	`jnl`	The MADlib Analytics Library or MAD Skills, the SQL. Proc. VLDB Endow. Joseph M. Hellerstein, Christopher Ré, Florian Schoppmann, Daisy Zhe Wang, Eugene Fratkin, Aleksander Gorajek, Kee Siong Ng, Caleb Welton, Xixuan Feng, Kun Li, Arun Kumar
2012	J	`jnl`	Towards a Unified Architecture for in-RDBMS Analytics CoRR Xixuan Feng, Arun Kumar, Ben Recht, Christopher Ré
2012	—	`conf`	Towards a unified architecture for in-RDBMS analytics. SIGMOD Conference Xixuan Feng, Arun Kumar, Benjamin Recht, Christopher Ré
2011	J	`jnl`	Probabilistic Management of OCR Data using an RDBMS CoRR Arun Kumar, Christopher Ré
2011	J	`jnl`	Probabilistic Management of OCR Data using an RDBMS. Proc. VLDB Endow. Arun Kumar, Christopher Ré