Rohit Singh
Research Papers
Pyro: Deep Universal Probabilistic Programming
E. Bingham, J. Chen, M. Jankowiak, F. Obermeyer, N. Pradhan, T. Karaletsos, R. Singh, P. Szerlip, P. Horsfall, N. Goodman
Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research. [...] [PDF]
Journal of Machine Learning Research (JMLR), 2018
Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research. [...] [PDF]
Journal of Machine Learning Research (JMLR), 2018
Synthesizing Entity Matching Rules by Examples
R. Singh, V. Vamsikrishna Meduri, A. Elmagarmid, S. Madden, P. Papotti, Jo. Quiané-Ruiz, A. Solar-Lezama, N. Tang
Entity matching (EM) is a critical part of data integration. We study how to synthesize entity matching rules from positive-negative matching examples. The core of our solution is program synthesis, a powerful tool to automatically generate rules (or programs) that satisfy a given highlevel specification, via a predefined grammar. [...] [PDF]
Proceedings of the VLDB Endowment (PVLDB) 11(2): 189-202, 2017
Entity matching (EM) is a critical part of data integration. We study how to synthesize entity matching rules from positive-negative matching examples. The core of our solution is program synthesis, a powerful tool to automatically generate rules (or programs) that satisfy a given highlevel specification, via a predefined grammar. [...] [PDF]
Proceedings of the VLDB Endowment (PVLDB) 11(2): 189-202, 2017