Deep learning for pedestrians: backpropagation in CNNs. - Laurent Boué (CoRR, 2018)

Real numbers, data science and chaos: How to fit any dataset with a single parameter. - Laurent Boué (CoRR, 2019)

A Data Source Dependency Analysis Framework for Large Scale Data Science Projects. - Laurent Boué; Pratap Kunireddy; Pavle Subotic (CoRR, 2022)

Automatically Resolving Data Source Dependency Hell in Large Scale Data Science Projects. - Laurent Boué; Pratap Kunireddy; Pavle Subotic (CAIN, 2023)

Domain specificity and data efficiency in typo tolerant spell checkers: the case of search in online marketplaces. - Dayananda Ubrangala; Juhi Sharma; Ravi Prasad Kondapalli; Kiran Rama; Amit Agarwala; Laurent Boué (CoRR, 2023)

Improving search relevance of Azure Cognitive Search by Bayesian optimization. - Nitin Agarwal; Ashish Kumar; Kiran Rama; Manish Gupta; Laurent Boué (CoRR, 2023)

High Significant Fault Detection in Azure Core Workload Insights. - Pranay Lohia; Laurent Boué; Sharath Ranganath; Vijay Agneeswaran 001 (AAAI, 2024)

Searching, fast and slow, through product catalogs. - Dayananda Ubrangala; Juhi Sharma; Sharath Kumar Rangappa; Kiran Rama; Ravi Prasad Kondapalli; Laurent Boué (CoRR, 2024)

A case study of Generative AI in MSX Sales Copilot: Improving seller productivity with a real-time question-answering system for content recommendation. - Manpreet Singh; Ravdeep Pasricha; Nitish Singh; Ravi Prasad Kondapalli; Manoj R; Kiran Rama; Laurent Boué (CoRR, 2024)

High Significant Fault Detection in Azure Core Workload Insights. - Pranay Lohia; Laurent Boué; Sharath Kumar Rangappa; Vijay Agneeswaran 001 (CoRR, 2024)

Fine-grained large-scale content recommendations for MSX sellers. - Manpreet Singh; Ravdeep Pasricha; Ravi Prasad Kondapalli; Kiran Rama; Nitish Singh; Akshita Agarwalla; Manoj R; Manish Prabhakar; Laurent Boué (CoRR, 2024)