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Found 7 papers, 2 papers with code
Offline Evaluation of Reward-Optimizing Recommender Systems: The Case of Simulation
Naturally, the reason for this is that we can directly measure utility metrics that rely on interventions, being the recommendations that are being shown to users.
Fixed point label attribution for real-time bidding
We dub our approach the Fixed Point Label Attribution (FiPLA) Algorithm.
Computer Science and Game Theory 91B26, 68Q32 I.2.6
Learning from Bandit Feedback: An Overview of the State-of-the-art
In order to handle this "bandit-feedback" setting, several Counterfactual Risk Minimisation (CRM) methods have been proposed in recent years, that attempt to estimate the performance of different policies on historical data.
Three Methods for Training on Bandit Feedback
There are three quite distinct ways to train a machine learning model on recommender system logs.
Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption
The minimization of convex objectives coming from linear supervised learning problems, such as penalized generalized linear models, can be formulated as finite sums of convex functions.
Tick: a Python library for statistical learning, with a particular emphasis on time-dependent modelling
Tick is a statistical learning library for Python~3, with a particular emphasis on time-dependent models, such as point processes, and tools for generalized linear models and survival analysis.
Sparse and low-rank multivariate Hawkes processes
We consider the problem of unveiling the implicit network structure of node interactions (such as user interactions in a social network), based only on high-frequency timestamps.
