research
∙
08/03/2023
Fast Slate Policy Optimization: Going Beyond Plackett-Luce
An increasingly important building block of large scale machine learning...
share
research
∙
05/25/2023
Exponential Smoothing for Off-Policy Learning
Off-policy learning (OPL) aims at finding improved policies from logged ...
research
∙
10/05/2022
Learning from aggregated data with a maximum entropy model
Aggregating a dataset, then injecting some noise, is a simple and common...
research
∙
09/18/2022
Offline Evaluation of Reward-Optimizing Recommender Systems: The Case of Simulation
Both in academic and industry-based research, online evaluation methods ...
research
∙
08/10/2022
A Scalable Probabilistic Model for Reward Optimizing Slate Recommendation
We introduce Probabilistic Rank and Reward model (PRR), a scalable proba...
research
∙
08/08/2022
Fast Offline Policy Optimization for Large Scale Recommendation
Personalised interactive systems such as recommender systems require sel...
research
∙
06/28/2022
Welfare-Optimized Recommender Systems
We present a recommender system based on the Random Utility Model. Onlin...
research
∙
07/26/2021
Combining Reward and Rank Signals for Slate Recommendation
We consider the problem of slate recommendation, where the recommender s...
research
∙
09/01/2020
From Clicks to Conversions: Recommendation for long-term reward
Recommender systems are often optimised for short-term reward: a recomme...
research
∙
08/28/2020
BLOB : A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals
A common task for recommender systems is to build a pro le of the intere...
research
∙
10/02/2019
Causal inference with Bayes rule
The concept of causality has a controversial history. The question of wh...
research
∙
10/02/2019
Reconsidering Analytical Variational Bounds for Output Layers of Deep Networks
The combination of the re-parameterization trick with the use of variati...
research
∙
09/18/2019
Learning from Bandit Feedback: An Overview of the State-of-the-art
In machine learning we often try to optimise a decision rule that would ...
research
∙
09/09/2019
Recommendation System-based Upper Confidence Bound for Online Advertising
In this paper, the method UCB-RS, which resorts to recommendation system...
research
∙
07/26/2019
On the Value of Bandit Feedback for Offline Recommender System Evaluation
In academic literature, recommender systems are often evaluated on the t...
research
∙
06/17/2019
A Bayesian Solution to the M-Bias Problem
It is common practice in using regression type models for inferring caus...
research
∙
06/17/2019
Replacing the do-calculus with Bayes rule
The concept of causality has a controversial history. The question of wh...
research
∙
04/24/2019
Three Methods for Training on Bandit Feedback
There are three quite distinct ways to train a machine learning model on...
research
∙
04/24/2019
Latent Variable Session-Based Recommendation
Session based recommendation provides an attractive alternative to the t...
research
∙
08/02/2018
