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ORCIDMatei Zaharia
Matei A. Zaharia
Person information
- affiliation: Stanford University, CA, USA
- award (2019): Presidential Early Career Award for Scientists and Engineers
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2020 – today
- 2024
[j42]Liana Patel
, Peter Kraft, Carlos Guestrin, Matei Zaharia:
ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data. Proc. ACM Manag. Data 2(3): 120 (2024)- [j41]Maryann Xue, Yingyi Bu, Abhishek Somani, Wenchen Fan, Ziqi Liu, Steven Chen, Herman Van Hovell, Bart Samwel, Mostafa Mokhtar, Rk Korlapati, Andy Lam, Yunxiao Ma, Vuk Ercegovac, Jiexing Li, Alexander Behm, Yuanjian Li, Xiao Li, Sriram Krishnamurthy, Amit Shukla, Michalis Petropoulos, Sameer Paranjpye, Reynold Xin, Matei Zaharia:
Adaptive and Robust Query Execution for Lakehouses At Scale. Proc. VLDB Endow. 17(12): 3947-3959 (2024) - [c106]Krista Opsahl-Ong, Michael J. Ryan, Josh Purtell, David Broman, Christopher Potts, Matei Zaharia, Omar Khattab:
Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs. EMNLP 2024: 9340-9366 - [c105]Keshav Santhanam, Deepti Raghavan, Muhammad Shahir Rahman, Thejas Venkatesh, Neha Kunjal, Pratiksha Thaker, Philip Alexander Levis, Matei Zaharia:
ALTO: An Efficient Network Orchestrator for Compound AI Systems. EuroMLSys@EuroSys 2024: 117-125 - [c104]Hao Liu, Matei Zaharia, Pieter Abbeel:
RingAttention with Blockwise Transformers for Near-Infinite Context. ICLR 2024 - [c103]Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, Christopher Potts:
DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines. ICLR 2024 - [c102]Jiwon Park, Shadaj Laddad, Dev Bali, Wen Zhang, Scott Shenker, Matei Zaharia:
Everything Everywhere All At Once: Efficient Cross-Service Program Analysis with OverSeer. ASE Workshops 2024: 82-87 - [c101]Jon Saad-Falcon, Omar Khattab, Christopher Potts, Matei Zaharia:
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems. NAACL-HLT 2024: 338-354 - [c100]Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto:
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. SP (Workshops) 2024: 132-143 - [i87]Hao Liu, Wilson Yan, Matei Zaharia, Pieter Abbeel:
World Model on Million-Length Video And Language With Blockwise RingAttention. CoRR abs/2402.08268 (2024) - [i86]Lingjiao Chen, Jared Quincy Davis, Boris Hanin, Peter Bailis, Ion Stoica, Matei Zaharia, James Zou:
Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems. CoRR abs/2403.02419 (2024) - [i85]Keshav Santhanam, Deepti Raghavan, Muhammad Shahir Rahman, Thejas Venkatesh, Neha Kunjal, Pratiksha Thaker, Philip Alexander Levis, Matei Zaharia:
ALTO: An Efficient Network Orchestrator for Compound AI Systems. CoRR abs/2403.04311 (2024) - [i84]Liana Patel, Peter Kraft, Carlos Guestrin, Matei Zaharia:
ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data. CoRR abs/2403.04871 (2024) - [i83]Shu Liu, Asim Biswal, Audrey Cheng, Xiangxi Mo, Shiyi Cao, Joseph E. Gonzalez, Ion Stoica, Matei Zaharia:
Optimizing LLM Queries in Relational Workloads. CoRR abs/2403.05821 (2024) - [i82]Tianjun Zhang, Shishir G. Patil, Naman Jain, Sheng Shen, Matei Zaharia, Ion Stoica, Joseph E. Gonzalez:
RAFT: Adapting Language Model to Domain Specific RAG. CoRR abs/2403.10131 (2024) - [i81]Karim Elmaaroufi, Devan Shanker, Ana Cismaru, Marcell Vazquez-Chanlatte, Alberto L. Sangiovanni-Vincentelli, Matei Zaharia, Sanjit A. Seshia:
Generating Probabilistic Scenario Programs from Natural Language. CoRR abs/2405.03709 (2024) - [i80]Krista Opsahl-Ong, Michael J. Ryan, Josh Purtell, David Broman, Christopher Potts, Matei Zaharia, Omar Khattab:
Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs. CoRR abs/2406.11695 (2024) - [i79]Liana Patel, Siddharth Jha, Carlos Guestrin, Matei Zaharia:
LOTUS: Enabling Semantic Queries with LLMs Over Tables of Unstructured and Structured Data. CoRR abs/2407.11418 (2024) - [i78]Jared Quincy Davis, Boris Hanin, Lingjiao Chen, Peter Bailis, Ion Stoica, Matei Zaharia:
Networks of Networks: Complexity Class Principles Applied to Compound AI Systems Design. CoRR abs/2407.16831 (2024) - [i77]Asim Biswal, Liana Patel, Siddarth Jha, Amog Kamsetty, Shu Liu, Joseph E. Gonzalez, Carlos Guestrin, Matei Zaharia:
Text2SQL is Not Enough: Unifying AI and Databases with TAG. CoRR abs/2408.14717 (2024) - [i76]Wilson Yan, Matei Zaharia, Volodymyr Mnih, Pieter Abbeel, Aleksandra Faust, Hao Liu:
ElasticTok: Adaptive Tokenization for Image and Video. CoRR abs/2410.08368 (2024) - [i75]Jinhao Zhu, Liana Patel, Matei Zaharia, Raluca Ada Popa:
Compass: Encrypted Semantic Search with High Accuracy. IACR Cryptol. ePrint Arch. 2024: 1255 (2024) - 2023
- [j40]Peter Kraft, Qian Li, Xinjing Zhou, Peter Bailis, Michael Stonebraker, Xiangyao Yu, Matei Zaharia:
Epoxy: ACID Transactions Across Diverse Data Stores. Proc. VLDB Endow. 16(11): 2742-2754 (2023) - [j39]Matthew Russo, Tatsunori Hashimoto, Daniel Kang, Yi Sun, Matei Zaharia:
Accelerating Aggregation Queries on Unstructured Streams of Data. Proc. VLDB Endow. 16(11): 2897-2910 (2023) - [j38]Qian Li, Peter Kraft, Michael J. Cafarella, Çagatay Demiralp, Goetz Graefe, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Xiangyao Yu, Matei Zaharia:
R3: Record-Replay-Retroaction for Database-Backed Applications. Proc. VLDB Endow. 16(11): 3085-3097 (2023) - [c99]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Huamin Qu, Christopher Ré, Matei Zaharia, James Zou:
HAPI Explorer: Comprehension, Discovery, and Explanation on History of ML APIs. AAAI 2023: 16416-16418 - [c98]Keshav Santhanam, Jon Saad-Falcon, Martin Franz, Omar Khattab, Avi Sil, Radu Florian, Md. Arafat Sultan, Salim Roukos, Matei Zaharia, Christopher Potts:
Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking. ACL (Findings) 2023: 11613-11628 - [c97]Paras Jain, Peter Kraft, Conor Power, Tathagata Das, Ion Stoica, Matei Zaharia:
Analyzing and Comparing Lakehouse Storage Systems. CIDR 2023 - [c96]Qian Li, Peter Kraft, Michael J. Cafarella, Çagatay Demiralp, Goetz Graefe, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Matei Zaharia:
Transactions Make Debugging Easy. CIDR 2023 - [c95]Pratiksha Thaker, Matei Zaharia, Tatsunori Hashimoto:
Congestion Control Safety via Comparative Statics. INFOCOM 2023: 1-10 - [c94]Trevor Gale, Deepak Narayanan, Cliff Young, Matei Zaharia:
MegaBlocks: Efficient Sparse Training with Mixture-of-Experts. MLSys 2023 - [c93]Deepti Raghavan, Shreya Ravi, Gina Yuan, Pratiksha Thaker, Sanjari Srivastava, Micah Murray, Pedro Henrique Penna, Amy Ousterhout, Philip Alexander Levis, Matei Zaharia, Irene Zhang:
Cornflakes: Zero-Copy Serialization for Microsecond-Scale Networking. SOSP 2023: 200-215 - [i74]Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto:
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. CoRR abs/2302.05733 (2023) - [i73]Francisco Romero, Caleb Winston, Johann Hauswald, Matei Zaharia, Christos Kozyrakis:
Zelda: Video Analytics using Vision-Language Models. CoRR abs/2305.03785 (2023) - [i72]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance. CoRR abs/2305.05176 (2023) - [i71]Lingjiao Chen, Matei Zaharia, James Zou:
How is ChatGPT's behavior changing over time? CoRR abs/2307.09009 (2023) - [i70]Matthew Russo, Tatsunori Hashimoto, Daniel Kang, Yi Sun, Matei Zaharia:
Accelerating Aggregation Queries on Unstructured Streams of Data. CoRR abs/2308.09157 (2023) - [i69]Hao Liu, Matei Zaharia, Pieter Abbeel:
Ring Attention with Blockwise Transformers for Near-Infinite Context. CoRR abs/2310.01889 (2023) - [i68]Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, Christopher Potts:
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines. CoRR abs/2310.03714 (2023) - [i67]Hao Liu, Matei Zaharia, Pieter Abbeel:
Exploration with Principles for Diverse AI Supervision. CoRR abs/2310.08899 (2023) - [i66]Jon Saad-Falcon, Omar Khattab, Christopher Potts, Matei Zaharia:
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems. CoRR abs/2311.09476 (2023) - [i65]Lingjiao Chen, Bilge Acun, Newsha Ardalani, Yifan Sun, Feiyang Kang, Hanrui Lyu, Yongchan Kwon, Ruoxi Jia, Carole-Jean Wu, Matei Zaharia, James Zou:
Data Acquisition: A New Frontier in Data-centric AI. CoRR abs/2311.13712 (2023) - [i64]Zhiling Zheng, Zhiguo He, Omar Khattab, Nakul Rampal, Matei A. Zaharia, Christian Borgs, Jennifer T. Chayes, Omar M. Yaghi:
Image and Data Mining in Reticular Chemistry Using GPT-4V. CoRR abs/2312.05468 (2023) - [i63]Arnav Singhvi, Manish Shetty, Shangyin Tan, Christopher Potts, Koushik Sen, Matei Zaharia, Omar Khattab:
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines. CoRR abs/2312.13382 (2023) - 2022
- [j37]Mihai Budiu, Pratiksha Thaker, Parikshit Gopalan, Udi Wieder, Matei Zaharia:
Overlook: Differentially Private Exploratory Visualization for Big Data. J. Priv. Confidentiality 12(1) (2022) - [j36]Akshay Agrawal, Stephen P. Boyd, Deepak Narayanan, Fiodar Kazhamiaka, Matei Zaharia:
Allocation of fungible resources via a fast, scalable price discovery method. Math. Program. Comput. 14(3): 593-622 (2022) - [j35]Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mach. Intell. 4(8): 669-677 (2022) - [j34]Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou:
Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mac. Intell. 4(10): 904 (2022) - [j33]Magdalena Balazinska, Surajit Chaudhuri, AnHai Doan, Joseph M. Hellerstein, Hanuma Kodavalla, Ippokratis Pandis, Matei Zaharia:
Cloud Data Systems: What are the Opportunities for the Database Research Community? Proc. VLDB Endow. 15(12): 3826-3827 (2022) - [j32]Francisco Romero, Johann Hauswald, Aditi Partap, Daniel Kang, Matei Zaharia, Christos Kozyrakis:
Optimizing Video Analytics with Declarative Model Relationships. Proc. VLDB Endow. 16(3): 447-460 (2022) - [j31]Nirvik Baruah, Peter Kraft, Fiodar Kazhamiaka, Peter Bailis, Matei Zaharia:
Parallelism-Optimizing Data Placement for Faster Data-Parallel Computations. Proc. VLDB Endow. 16(4): 760-771 (2022) - [c92]Cody Coleman, Edward Chou, Julian Katz-Samuels, Sean Culatana, Peter Bailis, Alexander C. Berg, Robert D. Nowak, Roshan Sumbaly, Matei Zaharia, I. Zeki Yalniz:
Similarity Search for Efficient Active Learning and Search of Rare Concepts. AAAI 2022: 6402-6410 - [c91]Qian Li, Peter Kraft, Kostis Kaffes, Athinagoras Skiadopoulos, Deeptaanshu Kumar, Jason Li, Michael J. Cafarella, Goetz Graefe, Jeremy Kepner, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Matei Zaharia:
A Progress Report on DBOS: A Database-oriented Operating System. CIDR 2022 - [c90]Daniel Kang, Francisco Romero, Peter D. Bailis, Christos Kozyrakis, Matei Zaharia:
VIVA: An End-to-End System for Interactive Video Analytics. CIDR 2022 - [c89]Keshav Santhanam, Omar Khattab, Christopher Potts, Matei Zaharia:
PLAID: An Efficient Engine for Late Interaction Retrieval. CIKM 2022: 1747-1756 - [c88]Lingjiao Chen, Matei Zaharia, James Zou:
How Did the Model Change? Efficiently Assessing Machine Learning API Shifts. ICLR 2022 - [c87]Ashwin Paranjape, Omar Khattab, Christopher Potts, Matei Zaharia, Christopher D. Manning:
Hindsight: Posterior-guided training of retrievers for improved open-ended generation. ICLR 2022 - [c86]Lingjiao Chen, Matei Zaharia, James Zou:
Efficient Online ML API Selection for Multi-Label Classification Tasks. ICML 2022: 3716-3746 - [c85]Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, Matei Zaharia:
ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction. NAACL-HLT 2022: 3715-3734 - [c84]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Christopher Ré, Matei Zaharia, James Y. Zou:
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. NeurIPS 2022 - [c83]Lingjiao Chen, Matei Zaharia, James Y. Zou:
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. NeurIPS 2022 - [c82]Peter Kraft, Fiodar Kazhamiaka, Peter Bailis, Matei Zaharia:
Data-Parallel Actors: A Programming Model for Scalable Query Serving Systems. NSDI 2022: 1059-1074 - [c81]Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter D. Bailis, Matei Zaharia:
Finding Label and Model Errors in Perception Data With Learned Observation Assertions. SIGMOD Conference 2022: 496-505 - [c80]Daniel Kang, John Guibas, Peter D. Bailis, Tatsunori Hashimoto, Matei Zaharia:
TASTI: Semantic Indexes for Machine Learning-based Queries over Unstructured Data. SIGMOD Conference 2022: 1934-1947 - [c79]Alexander Behm, Shoumik Palkar, Utkarsh Agarwal, Timothy Armstrong, David Cashman, Ankur Dave, Todd Greenstein, Shant Hovsepian, Ryan Johnson, Arvind Sai Krishnan, Paul Leventis, Ala Luszczak, Prashanth Menon, Mostafa Mokhtar, Gene Pang, Sameer Paranjpye, Greg Rahn, Bart Samwel, Tom van Bussel, Herman Van Hovell, Maryann Xue, Reynold Xin, Matei Zaharia:
Photon: A Fast Query Engine for Lakehouse Systems. SIGMOD Conference 2022: 2326-2339 - [i62]Daniel Kang, Nikos Aréchiga, Sudeep Pillai, Peter Bailis, Matei Zaharia:
Finding Label and Model Errors in Perception Data With Learned Observation Assertions. CoRR abs/2201.05797 (2022) - [i61]Gina Yuan, David Mazières, Matei Zaharia:
Extricating IoT Devices from Vendor Infrastructure with Karl. CoRR abs/2204.13737 (2022) - [i60]Keshav Santhanam, Omar Khattab, Christopher Potts, Matei Zaharia:
PLAID: An Efficient Engine for Late Interaction Retrieval. CoRR abs/2205.09707 (2022) - [i59]Peter Kraft, Qian Li, Kostis Kaffes, Athinagoras Skiadopoulos, Deeptaanshu Kumar, Danny Cho, Jason Li, Robert Redmond, Nathan W. Weckwerth, Brian S. Xia, Peter Bailis, Michael J. Cafarella, Goetz Graefe, Jeremy Kepner, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Xiangyao Yu, Matei Zaharia:
Apiary: A DBMS-Backed Transactional Function-as-a-Service Framework. CoRR abs/2208.13068 (2022) - [i58]Lingjiao Chen, Matei Zaharia, James Zou:
Estimating and Explaining Model Performance When Both Covariates and Labels Shift. CoRR abs/2209.08436 (2022) - [i57]Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Christopher Ré, Matei Zaharia, James Zou:
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. CoRR abs/2209.08443 (2022) - [i56]Trevor Gale, Deepak Narayanan, Cliff Young, Matei Zaharia:
MegaBlocks: Efficient Sparse Training with Mixture-of-Experts. CoRR abs/2211.15841 (2022) - [i55]Keshav Santhanam, Jon Saad-Falcon, Martin Franz, Omar Khattab, Avirup Sil, Radu Florian, Md. Arafat Sultan, Salim Roukos, Matei Zaharia, Christopher Potts:
Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking. CoRR abs/2212.01340 (2022) - [i54]Omar Khattab, Keshav Santhanam, Xiang Lisa Li, David Hall, Percy Liang, Christopher Potts, Matei Zaharia:
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP. CoRR abs/2212.14024 (2022) - [i53]Qian Li, Peter Kraft, Michael J. Cafarella, Çagatay Demiralp, Goetz Graefe, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Matei Zaharia:
Transactions Make Debugging Easy. CoRR abs/2212.14161 (2022) - 2021
- [j30]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Accelerating Approximate Aggregation Queries with Expensive Predicates. Proc. VLDB Endow. 14(11): 2341-2354 (2021) - [j29]Matei Zaharia:
Designing Production-Friendly Machine Learning. Proc. VLDB Endow. 14(13): 3420 (2021) - [j28]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) - [j27]Omar Khattab, Christopher Potts, Matei Zaharia:
Relevance-guided Supervision for OpenQA with ColBERT. Trans. Assoc. Comput. Linguistics 9: 929-944 (2021) - [j26]Firas Abuzaid, Peter Kraft, Sahaana Suri, Edward Gan, Eric Xu, Atul Shenoy, Asvin Ananthanarayan, John Sheu, Erik Meijer, Xi Wu, Jeffrey F. Naughton, Peter Bailis, Matei Zaharia:
DIFF: a relational interface for large-scale data explanation. VLDB J. 30(1): 45-70 (2021) - [c78]Fiodar Kazhamiaka, Matei Zaharia, Peter Bailis:
Challenges and Opportunities for Autonomous Vehicle Query Systems. CIDR 2021 - [c77]Matei Zaharia, Ali Ghodsi, Reynold Xin, Michael Armbrust:
Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics. CIDR 2021 - [c76]Pratiksha Thaker, Hudson Ayers, Deepti Raghavan, Ning Niu, Philip Alexander Levis, Matei Zaharia:
Clamor: Extending Functional Cluster Computing Frameworks with Fine-Grained Remote Memory Access. SoCC 2021: 654-669 - [c75]Pratiksha Thaker, Matei Zaharia, Tatsunori Hashimoto:
Don't Hate the Player, Hate the Game: Safety and Utility in Multi-Agent Congestion Control. HotNets 2021: 140-146 - [c74]Deepti Raghavan, Philip Alexander Levis, Matei Zaharia, Irene Zhang:
Breakfast of champions: towards zero-copy serialization with NIC scatter-gather. HotOS 2021: 199-205 - [c73]Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia:
Memory-Efficient Pipeline-Parallel DNN Training. ICML 2021: 7937-7947 - [c72]Omar Khattab, Christopher Potts, Matei A. Zaharia:
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval. NeurIPS 2021: 27670-27682 - [c71]Firas Abuzaid, Srikanth Kandula, Behnaz Arzani, Ishai Menache, Matei Zaharia, Peter Bailis:
Contracting Wide-area Network Topologies to Solve Flow Problems Quickly. NSDI 2021: 175-200 - [c70]Deepak Narayanan, Mohammad Shoeybi, Jared Casper, Patrick LeGresley, Mostofa Patwary, Vijay Korthikanti, Dmitri Vainbrand, Prethvi Kashinkunti, Julie Bernauer, Bryan Catanzaro, Amar Phanishayee, Matei Zaharia:
Efficient large-scale language model training on GPU clusters using megatron-LM. SC 2021: 58 - [c69]Deepak Narayanan, Fiodar Kazhamiaka, Firas Abuzaid, Peter Kraft, Akshay Agrawal, Srikanth Kandula, Stephen P. Boyd, Matei Zaharia:
Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP. SOSP 2021: 521-537 - [c68]Saba Eskandarian, Henry Corrigan-Gibbs, Matei Zaharia, Dan Boneh:
Express: Lowering the Cost of Metadata-hiding Communication with Cryptographic Privacy. USENIX Security Symposium 2021: 1775-1792 - [i52]Omar Khattab, Christopher Potts, Matei Zaharia:
Baleen: Robust Multi-Hop Reasoning at Scale via Condensed Retrieval. CoRR abs/2101.00436 (2021) - [i51]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalMCT: Efficient Online ML API Selection for Multi-Label Classification Tasks. CoRR abs/2102.09127 (2021) - [i50]Akshay Agrawal, Stephen P. Boyd, Deepak Narayanan, Fiodar Kazhamiaka, Matei Zaharia:
Allocation of Fungible Resources via a Fast, Scalable Price Discovery Method. CoRR abs/2104.00282 (2021) - [i49]Deepak Narayanan, Mohammad Shoeybi, Jared Casper, Patrick LeGresley, Mostofa Patwary, Vijay Korthikanti, Dmitri Vainbrand, Prethvi Kashinkunti, Julie Bernauer, Bryan Catanzaro, Amar Phanishayee, Matei Zaharia:
Efficient Large-Scale Language Model Training on GPU Clusters. CoRR abs/2104.04473 (2021) - [i48]Deepak Narayanan, Fiodar Kazhamiaka, Firas Abuzaid, Peter Kraft, Matei Zaharia:
Don't Give Up on Large Optimization Problems; POP Them! CoRR abs/2104.06513 (2021) - [i47]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Proof: Accelerating Approximate Aggregation Queries with Expensive Predicates. CoRR abs/2107.12525 (2021) - [i46]Lingjiao Chen, Tracy Cai, Matei Zaharia, James Zou:
Did the Model Change? Efficiently Assessing Machine Learning API Shifts. CoRR abs/2107.14203 (2021) - [i45]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Yi Sun, Matei Zaharia:
Accelerating Approximate Aggregation Queries with Expensive Predicates. CoRR abs/2108.06313 (2021) - [i44]Ashwin Paranjape, Omar Khattab, Christopher Potts, Matei Zaharia, Christopher D. Manning:
Hindsight: Posterior-guided training of retrievers for improved open-ended generation. CoRR abs/2110.07752 (2021) - [i43]Deepak Narayanan, Fiodar Kazhamiaka, Firas Abuzaid, Peter Kraft, Akshay Agrawal, Srikanth Kandula, Stephen P. Boyd, Matei Zaharia:
Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP. CoRR abs/2110.11927 (2021) - [i42]Keshav Santhanam, Siddharth Krishna, Ryota Tomioka, Tim Harris, Matei Zaharia:
DistIR: An Intermediate Representation and Simulator for Efficient Neural Network Distribution. CoRR abs/2111.05426 (2021) - [i41]Yuezhou Sun, Wenlong Zhao, Lijun Zhang, Xiao Liu, Hui Guan, Matei Zaharia:
Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression. CoRR abs/2111.10320 (2021) - [i40]Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, Matei Zaharia:
ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction. CoRR abs/2112.01488 (2021) - [i39]Neoklis Polyzotis, Matei Zaharia:
What can Data-Centric AI Learn from Data and ML Engineering? CoRR abs/2112.06439 (2021) - 2020
- [j25]Daniel Kang, Edward Gan, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Approximate Selection with Guarantees using Proxies. Proc. VLDB Endow. 13(11): 1990-2003 (2020) - [j24]Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia:
A Demonstration of Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. Proc. VLDB Endow. 13(12): 2833-2836 (2020) - [j23]Michael Armbrust, Tathagata Das, Sameer Paranjpye, Reynold Xin, Shixiong Zhu, Ali Ghodsi, Burak Yavuz, Mukul Murthy, Joseph Torres, Liwen Sun, Peter A. Boncz, Mostafa Mokhtar, Herman Van Hovell, Adrian Ionescu, Alicja Luszczak, Michal Switakowski, Takuya Ueshin, Xiao Li, Michal Szafranski, Pieter Senster, Matei Zaharia:
Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores. Proc. VLDB Endow. 13(12): 3411-3424 (2020) - [j22]Daniel Kang, Ankit Mathur, Teja Veeramacheneni, Peter Bailis, Matei Zaharia:
Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics. Proc. VLDB Endow. 14(2): 87-100 (2020) - [j21]Deepti Raghavan, Sadjad Fouladi, Philip Alexander Levis, Matei Zaharia:
Posh: A Data-Aware Shell. login Usenix Mag. 45(4) (2020) - [c67]James Thomas, Pat Hanrahan, Matei Zaharia:
Fleet: A Framework for Massively Parallel Streaming on FPGAs. ASPLOS 2020: 639-651 - [c66]Benyu Zhang, Matei Zaharia, Shouling Ji, Raluca Ada Popa, Guofei Gu:
PPMLP 2020: Workshop on Privacy-Preserving Machine Learning In Practice. CCS 2020: 2139-2140 - [c65]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 - [c64]Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia:
Selection via Proxy: Efficient Data Selection for Deep Learning. ICLR 2020 - [c63]Zhihao Jia, Sina Lin, Mingyu Gao, Matei Zaharia, Alex Aiken:
Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc. MLSys 2020 - [c62]Daniel Kang, Deepti Raghavan, Peter Bailis, Matei Zaharia:
Model Assertions for Monitoring and Improving ML Models. MLSys 2020 - [c61]Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia:
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. MLSys 2020 - [c60]Peter Mattson, Christine Cheng, Gregory F. Diamos, Cody Coleman, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debo Dutta, Udit Gupta, Kim M. Hazelwood, Andy Hock, Xinyuan Huang, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia:
MLPerf Training Benchmark. MLSys 2020 - [c59]Lingjiao Chen, Matei Zaharia, James Y. Zou:
FrugalML: How to use ML Prediction APIs more accurately and cheaply. NeurIPS 2020 - [c58]Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka, Amar Phanishayee, Matei Zaharia:
Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads. OSDI 2020: 481-498 - [c57]Trevor Gale, Matei Zaharia, Cliff Young, Erich Elsen:
Sparse GPU kernels for deep learning. SC 2020: 17 - [c56]Omar Khattab, Matei Zaharia:
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT. SIGIR 2020: 39-48 - [c55]Andrew Chen, Andy Chow, Aaron Davidson, Arjun DCunha, Ali Ghodsi, Sue Ann Hong, Andy Konwinski, Clemens Mewald, Siddharth Murching, Tomas Nykodym, Paul Ogilvie, Mani Parkhe, Avesh Singh, Fen Xie, Matei Zaharia, Richard Zang, Juntai Zheng, Corey Zumar:
Developments in MLflow: A System to Accelerate the Machine Learning Lifecycle. DEEM@SIGMOD 2020: 5:1-5:4 - [c54]Saachi Jain, Matei Zaharia:
Spectral Lower Bounds on the I/O Complexity of Computation Graphs. SPAA 2020: 329-338 - [c53]Gina Yuan, Shoumik Palkar, Deepak Narayanan, Matei Zaharia:
Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads. USENIX ATC 2020: 293-306 - [c52]Deepti Raghavan, Sadjad Fouladi, Philip Alexander Levis, Matei Zaharia:
POSH: A Data-Aware Shell. USENIX ATC 2020: 617-631 - [e2]Benyu Zhang, Raluca Ada Popa, Matei Zaharia, Guofei Gu, Shouling Ji:
PPMLP'20: Proceedings of the 2020 Workshop on Privacy-Preserving Machine Learning in Practice, Virtual Event, USA, November, 2020. ACM 2020, ISBN 978-1-4503-8088-1 [contents] - [i38]Daniel Kang, Deepti Raghavan, Peter Bailis, Matei Zaharia:
Model Assertions for Monitoring and Improving ML Models. CoRR abs/2003.01668 (2020) - [i37]Daniel Kang, Edward Gan, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Approximate Selection with Guarantees using Proxies. CoRR abs/2004.00827 (2020) - [i36]Omar Khattab, Matei Zaharia:
ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT. CoRR abs/2004.12832 (2020) - [i35]Lingjiao Chen, Matei Zaharia, James Zou:
FrugalML: How to Use ML Prediction APIs More Accurately and Cheaply. CoRR abs/2006.07512 (2020) - [i34]Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia:
Memory-Efficient Pipeline-Parallel DNN Training. CoRR abs/2006.09503 (2020) - [i33]Trevor Gale, Matei Zaharia, Cliff Young, Erich Elsen:
Sparse GPU Kernels for Deep Learning. CoRR abs/2006.10901 (2020) - [i32]Pratiksha Thaker, Mihai Budiu, Parikshit Gopalan, Udi Wieder, Matei Zaharia:
Overlook: Differentially Private Exploratory Visualization for Big Data. CoRR abs/2006.12018 (2020) - [i31]Cody Coleman, Edward Chou, Sean Culatana, Peter Bailis, Alexander C. Berg, Roshan Sumbaly, Matei Zaharia, I. Zeki Yalniz:
Similarity Search for Efficient Active Learning and Search of Rare Concepts. CoRR abs/2007.00077 (2020) - [i30]Omar Khattab, Christopher Potts, Matei Zaharia:
Relevance-guided Supervision for OpenQA with ColBERT. CoRR abs/2007.00814 (2020) - [i29]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) - [i28]Daniel Kang, Ankit Mathur, Teja Veeramacheneni, Peter Bailis, Matei Zaharia:
Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics. CoRR abs/2007.13005 (2020) - [i27]Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka, Amar Phanishayee, Matei Zaharia:
Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads. CoRR abs/2008.09213 (2020) - [i26]Daniel Kang, John Guibas, Peter Bailis, Tatsunori Hashimoto, Matei Zaharia:
Task-agnostic Indexes for Deep Learning-based Queries over Unstructured Data. CoRR abs/2009.04540 (2020)
2010 – 2019
- 2019
- [j20]Saba Eskandarian, Matei Zaharia:
ObliDB: Oblivious Query Processing for Secure Databases. Proc. VLDB Endow. 13(2): 169-183 (2019) - [j19]Daniel Kang, Peter Bailis, Matei Zaharia:
BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics. Proc. VLDB Endow. 13(4): 533-546 (2019) - [j18]Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Christopher Ré, Matei Zaharia:
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. ACM SIGOPS Oper. Syst. Rev. 53(1): 14-25 (2019) - [j17]Sadjad Fouladi, Francisco Romero, Dan Iter, Qian Li, Alex Ozdemir, Shuvo Chatterjee, Matei Zaharia, Christos Kozyrakis, Keith Winstein:
Outsourcing Everyday Jobs to Thousands of Cloud Functions with gg. login Usenix Mag. 44(3) (2019) - [c51]Daniel Kang, Peter Bailis, Matei Zaharia:
Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine. CIDR 2019 - [c50]Matei Zaharia:
Lessons from Large-Scale Software as a Service at Databricks. SoCC 2019: 101 - [c49]Firas Abuzaid, Geet Sethi, Peter Bailis, Matei Zaharia:
To Index or Not to Index: Optimizing Exact Maximum Inner Product Search. ICDE 2019: 1250-1261 - [c48]Animesh Koratana, Daniel Kang, Peter Bailis, Matei Zaharia:
LIT: Learned Intermediate Representation Training for Model Compression. ICML 2019: 3509-3518 - [c47]Zhihao Jia, James Thomas, Todd Warszawski, Mingyu Gao, Matei Zaharia, Alex Aiken:
Optimizing DNN Computation with Relaxed Graph Substitutions. SysML 2019 - [c46]Zhihao Jia, Matei Zaharia, Alex Aiken:
Beyond Data and Model Parallelism for Deep Neural Networks. SysML 2019 - [c45]Deepak Narayanan, Aaron Harlap, Amar Phanishayee, Vivek Seshadri, Nikhil R. Devanur, Gregory R. Ganger, Phillip B. Gibbons, Matei Zaharia:
PipeDream: generalized pipeline parallelism for DNN training. SOSP 2019: 1-15 - [c44]Zhihao Jia, Oded Padon, James Thomas, Todd Warszawski, Matei Zaharia, Alex Aiken:
TASO: optimizing deep learning computation with automatic generation of graph substitutions. SOSP 2019: 47-62 - [c43]Shoumik Palkar, Matei Zaharia:
Optimizing data-intensive computations in existing libraries with split annotations. SOSP 2019: 291-305 - [c42]Sadjad Fouladi, Francisco Romero, Dan Iter, Qian Li, Shuvo Chatterjee, Christos Kozyrakis, Matei Zaharia, Keith Winstein:
From Laptop to Lambda: Outsourcing Everyday Jobs to Thousands of Transient Functional Containers. USENIX ATC 2019: 475-488 - [e1]Ameet Talwalkar, Virginia Smith, Matei Zaharia:
Proceedings of the Second Conference on Machine Learning and Systems, SysML 2019, Stanford, CA, USA, March 31 - April 2, 2019. mlsys.org 2019 [contents] - [i25]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) - [i24]Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia:
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference. CoRR abs/1906.01974 (2019) - [i23]Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia:
Selection Via Proxy: Efficient Data Selection For Deep Learning. CoRR abs/1906.11829 (2019) - [i22]Saachi Jain, Matei Zaharia:
Automated Lower Bounds on the I/O Complexity of Computation Graphs. CoRR abs/1909.09791 (2019) - [i21]Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim M. Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia:
MLPerf Training Benchmark. CoRR abs/1910.01500 (2019) - [i20]Saba Eskandarian, Henry Corrigan-Gibbs, Matei Zaharia, Dan Boneh:
Express: Lowering the Cost of Metadata-hiding Communication with Cryptographic Privacy. CoRR abs/1911.09215 (2019) - 2018
- [j16]Matei Zaharia, Andrew Chen, Aaron Davidson, Ali Ghodsi, Sue Ann Hong, Andy Konwinski, Siddharth Murching, Tomas Nykodym, Paul Ogilvie, Mani Parkhe, Fen Xie, Corey Zumar:
Accelerating the Machine Learning Lifecycle with MLflow. IEEE Data Eng. Bull. 41(4): 39-45 (2018) - [j15]Shoumik Palkar, James Thomas, Deepak Narayanan, Pratiksha Thaker, Rahul Palamuttam, Parimarjan Negi, Anil Shanbhag, Malte Schwarzkopf, Holger Pirk, Saman P. Amarasinghe, Samuel Madden, Matei Zaharia:
Evaluating End-to-End Optimization for Data Analytics Applications in Weld. Proc. VLDB Endow. 11(9): 1002-1015 (2018) - [j14]Shoumik Palkar, Firas Abuzaid, Peter Bailis, Matei Zaharia:
Filter Before You Parse: Faster Analytics on Raw Data with Sparser. Proc. VLDB Endow. 11(11): 1576-1589 (2018) - [j13]Firas Abuzaid, Peter Kraft, Sahaana Suri, Edward Gan, Eric Xu, Atul Shenoy, Asvin Anathanaraya, John Sheu, Erik Meijer, Xi Wu, Jeffrey F. Naughton, Peter Bailis, Matei Zaharia:
DIFF: A Relational Interface for Large-Scale Data Explanation. Proc. VLDB Endow. 12(4): 419-432 (2018) - [c41]Michael Armbrust, Tathagata Das, Joseph Torres, Burak Yavuz, Shixiong Zhu, Reynold Xin, Ali Ghodsi, Ion Stoica, Matei Zaharia:
Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark. SIGMOD Conference 2018: 601-613 - [c40]Manasi Vartak, Joana M. F. da Trindade, Samuel Madden, Matei Zaharia:
MISTIQUE: A System to Store and Query Model Intermediates for Model Diagnosis. SIGMOD Conference 2018: 1285-1300 - [r1]Volker Markl, Vinayak R. Borkar, Matei Zaharia, Till Westmann, Alexander Alexandrov:
Big Data Platforms for Data Analytics. Encyclopedia of Database Systems (2nd ed.) 2018 - [i19]Daniel Kang, Peter Bailis, Matei Zaharia:
BlazeIt: Fast Exploratory Video Queries using Neural Networks. CoRR abs/1805.01046 (2018) - [i18]Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Christopher Ré, Matei Zaharia:
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. CoRR abs/1806.01427 (2018) - [i17]Zhihao Jia, Matei Zaharia, Alex Aiken:
Beyond Data and Model Parallelism for Deep Neural Networks. CoRR abs/1807.05358 (2018) - [i16]Animesh Koratana, Daniel Kang, Peter Bailis, Matei Zaharia:
LIT: Block-wise Intermediate Representation Training for Model Compression. CoRR abs/1810.01937 (2018) - [i15]Shoumik Palkar, Matei Zaharia:
Splitability Annotations: Optimizing Black-Box Function Composition in Existing Libraries. CoRR abs/1810.12297 (2018) - 2017
- [j12]Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia:
NoScope: Optimizing Deep CNN-Based Queries over Video Streams at Scale. Proc. VLDB Endow. 10(11): 1586-1597 (2017) - [c39]Yunming Zhang, Vladimir Kiriansky, Charith Mendis, Saman P. Amarasinghe, Matei Zaharia:
Making caches work for graph analytics. IEEE BigData 2017: 293-302 - [c38]Shoumik Palkar, James Thomas, Anil Shanbhag, Deepak Narayanan, Holger Pirk, Malte Schwarzkopf, Saman P. Amarasinghe, Matei Zaharia:
A Common Runtime for High Performance Data Analysis. CIDR 2017 - [c37]Shoumik Palkar, Matei Zaharia:
DIY Hosting for Online Privacy. HotNets 2017: 1-7 - [c36]Frank Wang, Catherine Yun, Shafi Goldwasser, Vinod Vaikuntanathan, Matei Zaharia:
Splinter: Practical Private Queries on Public Data. NSDI 2017: 299-313 - [c35]Nirvan Tyagi, Yossi Gilad, Derek Leung, Matei Zaharia, Nickolai Zeldovich:
Stadium: A Distributed Metadata-Private Messaging System. SOSP 2017: 423-440 - [i14]Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia:
Optimizing Deep CNN-Based Queries over Video Streams at Scale. CoRR abs/1703.02529 (2017) - [i13]Peter Bailis, Kunle Olukotun, Christopher Ré, Matei Zaharia:
Infrastructure for Usable Machine Learning: The Stanford DAWN Project. CoRR abs/1705.07538 (2017) - [i12]Firas Abuzaid, Geet Sethi, Peter Bailis, Matei Zaharia:
SimDex: Exploiting Model Similarity in Exact Matrix Factorization Recommendations. CoRR abs/1706.01449 (2017) - [i11]Shoumik Palkar, James Thomas, Deepak Narayanan, Anil Shanbhag, Rahul Palamuttam, Holger Pirk, Malte Schwarzkopf, Saman P. Amarasinghe, Samuel Madden, Matei Zaharia:
Weld: Rethinking the Interface Between Data-Intensive Applications. CoRR abs/1709.06416 (2017) - [i10]Saba Eskandarian, Matei Zaharia:
An Oblivious General-Purpose SQL Database for the Cloud. CoRR abs/1710.00458 (2017) - 2016
- [j11]Matei Zaharia, Reynold S. Xin, Patrick Wendell, Tathagata Das, Michael Armbrust, Ankur Dave, Xiangrui Meng, Josh Rosen, Shivaram Venkataraman, Michael J. Franklin, Ali Ghodsi, Joseph Gonzalez, Scott Shenker, Ion Stoica:
Apache Spark: a unified engine for big data processing. Commun. ACM 59(11): 56-65 (2016) - [j10]Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan Randall Sparks, Shivaram Venkataraman, Davies Liu, Jeremy Freeman, D. B. Tsai, Manish Amde, Sean Owen, Doris Xin, Reynold Xin, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar:
MLlib: Machine Learning in Apache Spark. J. Mach. Learn. Res. 17: 34:1-34:7 (2016) - [j9]Holger Pirk, Oscar R. Moll, Matei Zaharia, Sam Madden:
Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware. Proc. VLDB Endow. 9(14): 1707-1718 (2016) - [c34]Ankur Dave, Alekh Jindal, Li Erran Li, Reynold Xin, Joseph Gonzalez, Matei Zaharia:
GraphFrames: an integrated API for mixing graph and relational queries. GRADES 2016: 2 - [c33]Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan Randall Sparks, Aaron Staple, Matei Zaharia:
Matrix Computations and Optimization in Apache Spark. KDD 2016: 31-38 - [c32]Firas Abuzaid, Joseph K. Bradley, Feynman T. Liang, Andrew Feng, Lee Yang, Matei Zaharia, Ameet Talwalkar:
Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale. NIPS 2016: 3810-3818 - [c31]Qifan Pu, Haoyuan Li, Matei Zaharia, Ali Ghodsi, Ion Stoica:
FairRide: Near-Optimal, Fair Cache Sharing. NSDI 2016: 393-406 - [c30]Manasi Vartak, Harihar Subramanyam, Wei-En Lee, Srinidhi Viswanathan, Saadiyah Husnoo, Samuel Madden, Matei Zaharia:
ModelDB: a system for machine learning model management. HILDA@SIGMOD 2016: 14 - [c29]Shivaram Venkataraman, Zongheng Yang, Davies Liu, Eric Liang, Hossein Falaki, Xiangrui Meng, Reynold Xin, Ali Ghodsi, Michael J. Franklin, Ion Stoica, Matei Zaharia:
SparkR: Scaling R Programs with Spark. SIGMOD Conference 2016: 1099-1104 - [c28]Michael Armbrust, Doug Bateman, Reynold Xin, Matei Zaharia:
Introduction to Spark 2.0 for Database Researchers. SIGMOD Conference 2016: 2193-2194 - [i9]Yunming Zhang, Vladimir Kiriansky, Charith Mendis, Matei Zaharia, Saman P. Amarasinghe:
Optimizing Cache Performance for Graph Analytics. CoRR abs/1608.01362 (2016) - [i8]Nirvan Tyagi, Yossi Gilad, Matei Zaharia, Nickolai Zeldovich:
Stadium: A Distributed Metadata-Private Messaging System. IACR Cryptol. ePrint Arch. 2016: 943 (2016) - [i7]Frank Wang, Catherine Yun, Shafi Goldwasser, Vinod Vaikuntanathan, Matei Zaharia:
Splinter: Practical Private Queries on Public Data. IACR Cryptol. ePrint Arch. 2016: 1148 (2016) - 2015
- [j8]Michael Armbrust, Tathagata Das, Aaron Davidson, Ali Ghodsi, Andrew Or, Josh Rosen, Ion Stoica, Patrick Wendell, Reynold Xin, Matei Zaharia:
Scaling Spark in the Real World: Performance and Usability. Proc. VLDB Endow. 8(12): 1840-1843 (2015) - [c27]Michael Armbrust, Reynold S. Xin, Cheng Lian, Yin Huai, Davies Liu, Joseph K. Bradley, Xiangrui Meng, Tomer Kaftan, Michael J. Franklin, Ali Ghodsi, Matei Zaharia:
Spark SQL: Relational Data Processing in Spark. SIGMOD Conference 2015: 1383-1394 - [c26]Jelle van den Hooff, David Lazar, Matei Zaharia, Nickolai Zeldovich:
Vuvuzela: scalable private messaging resistant to traffic analysis. SOSP 2015: 137-152 - [i6]Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan Randall Sparks, Shivaram Venkataraman, Davies Liu, Jeremy Freeman, D. B. Tsai, Manish Amde, Sean Owen, Doris Xin, Reynold Xin, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar:
MLlib: Machine Learning in Apache Spark. CoRR abs/1505.06807 (2015) - [i5]Reza Bosagh Zadeh, Xiangrui Meng, Burak Yavuz, Aaron Staple, Li Pu, Shivaram Venkataraman, Evan Randall Sparks, Alexander Ulanov, Matei Zaharia:
linalg: Matrix Computations in Apache Spark. CoRR abs/1509.02256 (2015) - 2014
- [c25]Haoyuan Li, Ali Ghodsi, Matei Zaharia, Scott Shenker, Ion Stoica:
Tachyon: Reliable, Memory Speed Storage for Cluster Computing Frameworks. SoCC 2014: 6:1-6:15 - 2013
- [b1]Matei A. Zaharia:
An Architecture for and Fast and General Data Processing on Large Clusters. University of California, Berkeley, USA, 2013 - [j7]Timothy Hunter, Tathagata Das, Matei Zaharia, Pieter Abbeel, Alexandre M. Bayen:
Large-Scale Estimation in Cyberphysical Systems Using Streaming Data: A Case Study With Arterial Traffic Estimation. IEEE Trans Autom. Sci. Eng. 10(4): 884-898 (2013) - [c24]Ali Ghodsi, Matei Zaharia, Scott Shenker, Ion Stoica:
Choosy: max-min fair sharing for datacenter jobs with constraints. EuroSys 2013: 365-378 - [c23]Reynold S. Xin, Josh Rosen, Matei Zaharia, Michael J. Franklin, Scott Shenker, Ion Stoica:
Shark: SQL and rich analytics at scale. SIGMOD Conference 2013: 13-24 - [c22]Kay Ousterhout, Patrick Wendell, Matei Zaharia, Ion Stoica:
Sparrow: distributed, low latency scheduling. SOSP 2013: 69-84 - [c21]Matei Zaharia, Tathagata Das, Haoyuan Li, Timothy Hunter, Scott Shenker, Ion Stoica:
Discretized streams: fault-tolerant streaming computation at scale. SOSP 2013: 423-438 - 2012
- [j6]Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, James Murphy McCauley, Michael J. Franklin, Scott Shenker, Ion Stoica:
Fast and Interactive Analytics over Hadoop Data with Spark. login Usenix Mag. 37(4) (2012) - [c20]Anna N. Rafferty, Matei Zaharia, Thomas L. Griffiths:
Optimally Designing Games for Cognitive Science Research. CogSci 2012 - [c19]Matei Zaharia, Tathagata Das, Haoyuan Li, Scott Shenker, Ion Stoica:
Discretized Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large Clusters. HotCloud 2012 - [c18]Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauly, Michael J. Franklin, Scott Shenker, Ion Stoica:
Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. NSDI 2012: 15-28 - [c17]Ali Ghodsi, Vyas Sekar, Matei Zaharia, Ion Stoica:
Multi-resource fair queueing for packet processing. SIGCOMM 2012: 1-12 - [c16]Cliff Engle, Antonio Lupher, Reynold Xin, Matei Zaharia, Michael J. Franklin, Scott Shenker, Ion Stoica:
Shark: fast data analysis using coarse-grained distributed memory. SIGMOD Conference 2012: 689-692 - [c15]Lorenzo Martignoni, Pongsin Poosankam, Matei Zaharia, Jun Han, Stephen McCamant, Dawn Song, Vern Paxson, Adrian Perrig, Scott Shenker, Ion Stoica:
Cloud Terminal: Secure Access to Sensitive Applications from Untrusted Systems. USENIX ATC 2012: 165-182 - [i4]Reynold Xin, Josh Rosen, Matei Zaharia, Michael J. Franklin, Scott Shenker, Ion Stoica:
Shark: SQL and Rich Analytics at Scale. CoRR abs/1211.6176 (2012) - [i3]Timothy Hunter, Tathagata Das, Matei Zaharia, Pieter Abbeel, Alexandre M. Bayen:
Large Scale Estimation in Cyberphysical Systems using Streaming Data: a Case Study with Smartphone Traces. CoRR abs/1212.3393 (2012) - 2011
- [j5]Shimin Guo, Mohammad Derakhshani, Mohammad Hossein Falaki, Usman Ismail, Rowena Luk, Earl A. Oliver, Sumair Ur Rahman, Aaditeshwar Seth, Matei A. Zaharia, Srinivasan Keshav:
Design and implementation of the KioskNet system. Comput. Networks 55(1): 264-281 (2011) - [j4]Benjamin Hindman, Andy Konwinski, Matei Zaharia, Ali Ghodsi, Anthony D. Joseph, Randy H. Katz, Scott Shenker, Ion Stoica:
Mesos: Flexible Resource Sharing for the Cloud. login Usenix Mag. 36(4) (2011) - [c14]Timothy Hunter, Teodor Mihai Moldovan, Matei Zaharia, Samy Merzgui, Justin Ma, Michael J. Franklin, Pieter Abbeel, Alexandre M. Bayen:
Scaling the mobile millennium system in the cloud. SoCC 2011: 28 - [c13]Matei Zaharia, Benjamin Hindman, Andy Konwinski, Ali Ghodsi, Anthony D. Joseph, Randy H. Katz, Scott Shenker, Ion Stoica:
The Datacenter Needs an Operating System. HotCloud 2011 - [c12]Ali Ghodsi, Matei Zaharia, Benjamin Hindman, Andy Konwinski, Scott Shenker, Ion Stoica:
Dominant Resource Fairness: Fair Allocation of Multiple Resource Types. NSDI 2011 - [c11]Benjamin Hindman, Andy Konwinski, Matei Zaharia, Ali Ghodsi, Anthony D. Joseph, Randy H. Katz, Scott Shenker, Ion Stoica:
Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center. NSDI 2011 - [c10]Mosharaf Chowdhury, Matei Zaharia, Justin Ma, Michael I. Jordan, Ion Stoica:
Managing data transfers in computer clusters with orchestra. SIGCOMM 2011: 98-109 - [i2]Matei Zaharia, William J. Bolosky, Kristal Curtis, Armando Fox, David A. Patterson, Scott Shenker, Ion Stoica, Richard M. Karp, Taylor Sittler:
Faster and More Accurate Sequence Alignment with SNAP. CoRR abs/1111.5572 (2011) - 2010
- [j3]Michael Armbrust, Armando Fox, Rean Griffith, Anthony D. Joseph, Randy H. Katz, Andy Konwinski, Gunho Lee, David A. Patterson, Ariel Rabkin, Ion Stoica, Matei Zaharia:
A view of cloud computing. Commun. ACM 53(4): 50-58 (2010) - [c9]Matei Zaharia, Dhruba Borthakur, Joydeep Sen Sarma, Khaled Elmeleegy, Scott Shenker, Ion Stoica:
Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling. EuroSys 2010: 265-278 - [c8]Matei Zaharia, Mosharaf Chowdhury, Michael J. Franklin, Scott Shenker, Ion Stoica:
Spark: Cluster Computing with Working Sets. HotCloud 2010
2000 – 2009
- 2009
- [c7]Benjamin Hindman, Andy Konwinski, Matei Zaharia, Ion Stoica:
A Common Substrate for Cluster Computing. HotCloud 2009 - [c6]Rowena Luk, Matei Zaharia, Melissa R. Ho, Brian Levine, Paul M. Aoki:
ICTD for healthcare in Ghana: Two parallel case studies. ICTD 2009: 118-128 - [i1]Rowena Luk, Matei Zaharia, Melissa R. Ho, Brian Levine, Paul M. Aoki:
ICTD for Healthcare in Ghana: Two Parallel Case Studies. CoRR abs/0905.0203 (2009) - 2008
- [j2]Matei A. Zaharia, Srinivasan Keshav:
Gossip-based search selection in hybrid peer-to-peer networks. Concurr. Comput. Pract. Exp. 20(2): 139-153 (2008) - [c5]Matei Zaharia, Andy Konwinski, Anthony D. Joseph, Randy H. Katz, Ion Stoica:
Improving MapReduce Performance in Heterogeneous Environments. OSDI 2008: 29-42 - 2007
- [j1]Shimin Guo, Mohammad Hossein Falaki, Earl A. Oliver, Sumair Ur Rahman, Aaditeshwar Seth, Matei A. Zaharia, Srinivasan Keshav:
Very low-cost internet access using KioskNet. Comput. Commun. Rev. 37(5): 95-100 (2007) - [c4]Shimin Guo, Mohammad Hossein Falaki, Earl A. Oliver, Sumair Ur Rahman, Aaditeshwar Seth, Matei A. Zaharia, Usman Ismail, Srinivasan Keshav:
Design and implementation of the KioskNet system. ICTD 2007: 1-10 - [c3]Matei A. Zaharia, Amit Chandel, Stefan Saroiu, Srinivasan Keshav:
Finding Content in File-Sharing Networks When You Can't Even Spell. IPTPS 2007 - 2006
- [c2]Matei A. Zaharia, Srinivasan Keshav:
Gossip-based Search Selection in Hybrid Peer-to-Peer Networks. IPTPS 2006 - [c1]Aaditeshwar Seth, D. Kroeker, Matei A. Zaharia, Shimin Guo, Srinivasan Keshav:
Low-cost communication for rural internet kiosks using mechanical backhaul. MobiCom 2006: 334-345
Coauthor Index
Peter Bailis
aka: Peter D. Bailis
aka: Peter D. Bailis
Tatsunori B. Hashimoto
aka: Tatsunori Hashimoto
aka: Tatsunori Hashimoto
Christoforos E. Kozyrakis
aka: Christos Kozyrakis
aka: Christos Kozyrakis
Reynold Xin
aka: Reynold S. Xin
aka: Reynold S. Xin
James Zou 0001
aka: James Y. Zou
aka: James Y. Zou
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