1 citations · 1 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
Smooth Sequential Optimisation with Delayed Feedback
Srivas Chennu, Jamie Martin, Puli Liyanagama +1
Stochastic delays in feedback lead to unstable sequential learning using multi-armed bandits. Recently, empirical Bayesian shrinkage has been shown to improve reward estimation in…
A mean field approach to model levels of consciousness from EEG recordings
Marco Alberto Javarone, Olivia Gosseries, Daniele Marinazzo +4
We introduce a mean-field model for analysing the dynamics of human consciousness. In particular, inspired by the Giulio Tononi's Integrated Information Theory and by the Max Tegma…