Mayukh Das
mayukhdas
Senior Research Scientist (L2) @ Microsoft365 Research Interests: AI-Ops, Human-in-the-loop AI, Model Efficiency Optimization
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Approximate satisfiability counting via hypergraphs
Learning Boosted MLN with in-memory Relational Database integration (Malec et al. ILP 2016). This is an extension where wrapper ensures same command line argument structure as MLN-Boost. Most arguments are same as the original MLN-Boost(Khot et al. ICDM 2011) platform. Few that are different have been stated below.
Artifacts of LoadStar framework for VLDB
PDS
Repositories
18Artifacts of LoadStar framework for VLDB
PDS
No description provided.
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Learning Boosted MLN with in-memory Relational Database integration (Malec et al. ILP 2016). This is an extension where wrapper ensures same command line argument structure as MLN-Boost. Most arguments are same as the original MLN-Boost(Khot et al. ICDM 2011) platform. Few that are different have been stated below.
Approximate satisfiability counting via hypergraphs
Learn concepts from 1 example via ILP Onion framework
A Python package and tool for learning statistical relational models via gradient boosting.
StarCraft II Learning Environment
DO NOT USE : Under Development
For Demo in CwC PI meeting
Returns all exact groundings/instances of a Horn Clause
Multi-class Malware Classification using source/assembly level code files
No description provided.
Development repository for the STARLinG Lab's webpage. Built wtih Jekyll, jQuery, and the minimal-mistakes Jekyll theme. https://boost-starai.github.io
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