Displaying present location in the site.
Causal discovery and inference are important research fields leading to higher levels of artificial intelligence. Our Data Analysis Team took the lead in the industry to carry out technical research on discovering causality from data and conducting causal inference, and has achieved a number of industry-leading technical results. This technology has successfully completed application verification in a number of business scenarios in the marketing field. It brings significant value enhancement to the customer's business by achieving rapid and accurate insights into business processes, locating key reasons that affect the realization of business goals, and visualizing business processes, etc..
In October 2020, based on this technological achievement, NEC launched a service business to explore and analyze causality. This technology was also selected as a member of NEC's advanced AI technology group "NEC the WISE" (※). New technologies such as precise insights and intervention strategy planning based on NEC's causal analysis technology are also being developed, which are expected to create greater value for customers in various fields such as marketing scenarios, health care, finance etc..
- 【AAAI 2024】ACAMDA: Improving Data Efficiency in Reinforcement Learning Through Guided Counterfactual Data Augmentation
- 【ICDM 2021】Nonlinear Causal Structure Learning for Mixed Data
- 【ACM 2019】Local learning approaches for finding effects of a specified cause and their causal paths
- 【AAAI Fall symposium 2019】Causal Mediation Analysis with Multiple Treatments and Latent Confounders
- 【IJCAI 2018】Mixed causal structure discovery with application to prescriptive pricing
- 【SCIENTIA SINICA Mathematica 2018】Statistical Approaches for Causal Inference