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05/02/2023
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?
In recent years, neural models have been repeatedly touted to exhibit st...
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11/11/2022
Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates
With information systems becoming larger scale, recommendation systems a...
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11/02/2022
Where Do We Go From Here? Guidelines For Offline Recommender Evaluation
Various studies in recent years have pointed out large issues in the off...
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07/12/2022
EvalRS: a Rounded Evaluation of Recommender Systems
Much of the complexity of Recommender Systems (RSs) comes from the fact ...
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02/04/2022
Lightweight Compositional Embeddings for Incremental Streaming Recommendation
Most work in graph-based recommender systems considers a static setting ...
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11/18/2021
SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization
In the summarization domain, a key requirement for summaries is to be fa...
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07/07/2021
Keep it Simple: Unsupervised Simplification of Multi-Paragraph Text
This work presents Keep it Simple (KiS), a new approach to unsupervised ...
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05/29/2019
Deep Generalized Method of Moments for Instrumental Variable Analysis
Instrumental variable analysis is a powerful tool for estimating causal ...
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02/21/2018
Improving Recommender Systems Beyond the Algorithm
Recommender systems rely heavily on the predictive accuracy of the learn...
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04/02/2016
Online Updating of Word Representations for Part-of-Speech Tagging
We propose online unsupervised domain adaptation (DA), which is performe...
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02/17/2016
Recommendations as Treatments: Debiasing Learning and Evaluation
Most data for evaluating and training recommender systems is subject to ...
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11/06/2015