What is MRR and where is it used?
Machine Learning / AI
What are diffusion audio models (AudioLDM)?
What are the practical disadvantages of Bayesian approaches?
What is BM25 and what are the parameters (k1, b)?
What is hard negative mining in ranking?
What is early stopping in boosting and how to validate it correctly?
What is Megatron-LM and its tensor parallel approach?
What is sequential testing (mSPRT, always valid)?
What are the features of deploying models on edge (memory, latency, batch=1)?
What are the features of Parquet schemas and why is it efficient for ML?
What are the features of label collection (crowdsourcing, active learning)?
What tasks does ML solve in robotics (perception, planning, control)?
What is propensity score and its use (matching, IPW)?
What are potential outcomes (potential outcomes) according to Rubin?
How does NDCG@10 differ from NDCG over the entire list?