47 citations · 51 across the 4 of their papers we have counts for
5 papers
Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions
James McInerney, Brian Brost, Praveen Chandar +2
Users of music streaming, video streaming, news recommendation, and e-commerce services often engage with content in a sequential manner. Providing and evaluating good sequences of…
Data Cleansing with Contrastive Learning for Vocal Note Event Annotations
Gabriel Meseguer-Brocal, Rachel Bittner, Simon Durand +1
Data cleansing is a well studied strategy for cleaning erroneous labels in datasets, which has not yet been widely adopted in Music Information Retrieval. Previously proposed data…
The Music Streaming Sessions Dataset
Brian Brost, Rishabh Mehrotra, Tristan Jehan
At the core of many important machine learning problems faced by online streaming services is a need to model how users interact with the content they are served. Unfortunately, th…
Multi-Dueling Bandits and Their Application to Online Ranker Evaluation
Brian Brost, Yevgeny Seldin, Ingemar J. Cox +1
New ranking algorithms are continually being developed and refined, necessitating the development of efficient methods for evaluating these rankers. Online ranker evaluation focuse…
An Improved Multileaving Algorithm for Online Ranker Evaluation
Brian Brost, Ingemar J. Cox, Yevgeny Seldin +1
Online ranker evaluation is a key challenge in information retrieval. An important task in the online evaluation of rankers is using implicit user feedback for inferring preference…