Alexandre V. Evfimievski

Publication Activity (10 Years)

Years Active: 1998-2023
Publications (10 Years): 13

Top Topics

Subset Selection

Machine Learning

Plan Generation

Top Venues

Proc. VLDB Endow.

Publications

KirshnaTeja Killamsetty, Alexandre V. Evfimievski, Tejaswini Pedapati, Kiran Kate, Lucian Popa, Rishabh K. Iyer
MILO: Model-Agnostic Subset Selection Framework for Efficient Model Training and Tuning. CoRR (2023)
KrishnaTeja Killamsetty, Guttu Sai Abhishek, Aakriti, Alexandre V. Evfimievski, Lucian Popa, Ganesh Ramakrishnan, Rishabh K. Iyer
AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning. CoRR (2022)
KrishnaTeja Killamsetty, Guttu Sai Abhishek, Aakriti, Ganesh Ramakrishnan, Alexandre V. Evfimievski, Lucian Popa, Rishabh K. Iyer
AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning. NeurIPS (2022)
Arunima Chaudhary, Alayt Issak, Kiran Kate, Yannis Katsis, Abel N. Valente, Dakuo Wang, Alexandre V. Evfimievski, Sairam Gurajada, Ban Kawas, A. Cristiano I. Malossi, Lucian Popa, Tejaswini Pedapati, Horst Samulowitz, Martin Wistuba, Yunyao Li
AutoText: An End-to-End AutoAI Framework for Text. AAAI (2021)
Doug Burdick, Marina Danilevsky, Alexandre V. Evfimievski, Yannis Katsis, Nancy Xin Ru Wang
Table Extraction and Understanding for Scientific and Enterprise Applications. Proc. VLDB Endow. 13 (12) (2020)
Johanna Sommer, Matthias Boehm, Alexandre V. Evfimievski, Berthold Reinwald, Peter J. Haas
MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions. SIGMOD Conference (2019)
Matthias Boehm, Alexandre V. Evfimievski, Berthold Reinwald
Efficient Data-Parallel Cumulative Aggregates for Large-Scale Machine Learning. BTW (2019)
Matthias Boehm, Berthold Reinwald, Dylan Hutchison, Alexandre V. Evfimievski, Prithviraj Sen
On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML. CoRR (2018)
Matthias Boehm, Berthold Reinwald, Dylan Hutchison, Prithviraj Sen, Alexandre V. Evfimievski, Niketan Pansare
On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML. Proc. VLDB Endow. 11 (12) (2018)
Tarek Elgamal, Shangyu Luo, Matthias Boehm, Alexandre V. Evfimievski, Shirish Tatikonda, Berthold Reinwald, Prithviraj Sen
SPOOF: Sum-Product Optimization and Operator Fusion for Large-Scale Machine Learning. CIDR (2017)
Xilun Chen, Laura Chiticariu, Marina Danilevsky, Alexandre V. Evfimievski, Prithviraj Sen
A Rectangle Mining Method for Understanding the Semantics of Financial Tables. ICDAR (2017)
Matthias Boehm, Michael Dusenberry, Deron Eriksson, Alexandre V. Evfimievski, Faraz Makari Manshadi, Niketan Pansare, Berthold Reinwald, Frederick Reiss, Prithviraj Sen, Arvind Surve, Shirish Tatikonda
SystemML: Declarative Machine Learning on Spark. Proc. VLDB Endow. 9 (13) (2016)
Matthias Boehm, Alexandre V. Evfimievski, Niketan Pansare, Berthold Reinwald
Declarative Machine Learning - A Classification of Basic Properties and Types. CoRR (2016)
Sebastian Schelter, Juan Soto, Volker Markl, Douglas Burdick, Berthold Reinwald, Alexandre V. Evfimievski
Efficient sample generation for scalable meta learning. ICDE (2015)
Douglas Burdick, Alexandre V. Evfimievski, Rajasekar Krishnamurthy, Neal Lewis, Lucian Popa, Scott Rickards, Peter Williams
Financial Analytics from Public Data. DSMM (2014)
Matthias Böhm, Douglas R. Burdick, Alexandre V. Evfimievski, Berthold Reinwald, Frederick R. Reiss, Prithviraj Sen, Shirish Tatikonda, Yuanyuan Tian
SystemML's Optimizer: Plan Generation for Large-Scale Machine Learning Programs. IEEE Data Eng. Bull. 37 (3) (2014)
Matthias Boehm, Douglas Burdick, Alexandre V. Evfimievski, Berthold Reinwald, Prithviraj Sen, Shirish Tatikonda, Yuanyuan Tian
Compiling machine learning algorithms with SystemML. SoCC (2013)
Joseph P. Bigus, Murray Campbell, Boaz Carmeli, Melissa Cefkin, Henry Chang, Ching-Hua Chen-Ritzo, William F. Cody, Shahram Ebadollahi, Alexandre V. Evfimievski, Ariel Farkash, Susanne Glissmann, David Gotz, Tyrone Grandison, Daniel Gruhl, Peter J. Haas, Mark J. H. Hsiao, Pei-Yun Sabrina Hsueh, Jianying Hu, Joseph M. Jasinski, James H. Kaufman, Cheryl A. Kieliszewski, Martin S. Kohn, Sarah E. Knoop, Paul P. Maglio, Ronald L. Mak, Haim Nelken, Chalapathy Neti, Hani Neuvirth, Yue Pan, Yardena Peres, Sreeram Ramakrishnan, Michal Rosen-Zvi, Sondra R. Renly, Pat Selinger, Amnon Shabo, Robert Sorrentino, Jimeng Sun, Tanveer Fathima Syeda-Mahmood, Wang Chiew Tan, Ying Y. Y. Tao, Reza Yaesoubi, Xinxin Zhu
Information technology for healthcare transformation. IBM J. Res. Dev. 55 (5) (2011)
Alexandre V. Evfimievski, Ronald Fagin, David P. Woodruff
Epistemic privacy. J. ACM 58 (1) (2010)
Alexandre V. Evfimievski, Ronald Fagin, David P. Woodruff
Epistemic privacy. PODS (2008)
Rakesh Agrawal, Alexandre V. Evfimievski, Jerry Kiernan, Raja Velu
Auditing disclosure by relevance ranking. SIGMOD Conference (2007)
Alexandre V. Evfimievski, Ramakrishnan Srikant, Rakesh Agrawal, Johannes Gehrke
Privacy preserving mining of association rules. Inf. Syst. 29 (4) (2004)
Rakesh Agrawal, Alexandre V. Evfimievski, Ramakrishnan Srikant
Information Sharing Across Private Databases. SIGMOD Conference (2003)
Alexandre V. Evfimievski, Johannes Gehrke, Ramakrishnan Srikant
Limiting privacy breaches in privacy preserving data mining. PODS (2003)
Alexandre V. Evfimievski
Randomization in Privacy-Preserving Data Mining. SIGKDD Explor. 4 (2) (2002)
Alexandre V. Evfimievski, Ramakrishnan Srikant, Rakesh Agrawal, Johannes Gehrke
Privacy preserving mining of association rules. KDD (2002)
Alexandre V. Evfimievski
A probabilistic algorithm for updating files over a communication link. Theor. Comput. Sci. 233 (1-2) (2000)
Alexandre V. Evfimievski
A Probabilistic Algorithm for Updating Files over a Communication Link. SODA (1998)