Search Results for author:
Found 6 papers, 0 papers with code
Large Scale Generative Multimodal Attribute Extraction for E-commerce Attributes
In a popular e-commerce store, we have deployed our models for 1000s of (product-type, attribute) pairs.
Distantly Supervised Transformers For E-Commerce Product QA
Training with CQA pairs helps our model learning semantic QA relevance and distant supervision enables learning of syntactic features as well as the nuances of user querying language.
Domain Aware Markov Logic Networks
Experiments on the benchmark Friends & Smokers domain show that our ap- proach results in significantly higher accuracies compared to existing methods when testing on domains whose sizes different from those seen during training.
Lifted Marginal MAP Inference
Lifted inference reduces the complexity of inference in relational probabilistic models by identifying groups of constants (or atoms) which behave symmetric to each other.
Lifted Inference Rules With Constraints
Lifted inference rules exploit symmetries for fast reasoning in statistical rela-tional models.
New Rules for Domain Independent Lifted MAP Inference
In this paper, we present two new lifting rules, which enable fast MAP inference in a large class of MLNs.
