3 papers
cs.IR2024
Evaluating Performance and Bias of Negative Sampling in Large-Scale Sequential Recommendation Models
Arushi Prakash, Dimitrios Bermperidis, Srivas Chennu
Large-scale industrial recommendation models predict the most relevant items from catalogs containing millions or billions of options. To train these models efficiently, a small se…
cs.LG2023
Rapid and Scalable Bayesian AB Testing
Srivas Chennu, Andrew Maher, Christian Pangerl +4
AB testing aids business operators with their decision making, and is considered the gold standard method for learning from data to improve digital user experiences. However, there…
cs.LG2022
Dynamic Memory for Interpretable Sequential Optimisation
Srivas Chennu, Andrew Maher, Jamie Martin +1
Real-world applications of reinforcement learning for recommendation and experimentation faces a practical challenge: the relative reward of different bandit arms can evolve over t…