30 citations · 190 across the 36 of their papers we have counts for
5 papers · 1 filter
Are Quantum Computers Practical Yet? A Case for Feature Selection in Recommender Systems using Tensor Networks
Artyom Nikitin, Andrei Chertkov, Rafael Ballester-Ripoll +2
Collaborative filtering models generally perform better than content-based filtering models and do not require careful feature engineering. However, in the cold-start scenario coll…
Tensor-based Collaborative Filtering With Smooth Ratings Scale
Nikita Marin, Elizaveta Makhneva, Maria Lysyuk +3
Conventional collaborative filtering techniques don't take into consideration the effect of discrepancy in users' rating perception. Some users may rarely give 5 stars to items whi…
Dynamic Modeling of User Preferences for Stable Recommendations
Oluwafemi Olaleke, Ivan Oseledets, Evgeny Frolov
In domains where users tend to develop long-term preferences that do not change too frequently, the stability of recommendations is an important factor of the perceived quality of…
Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks
Leyla Mirvakhabova, Evgeny Frolov, Valentin Khrulkov +2
We introduce a simple autoencoder based on hyperbolic geometry for solving standard collaborative filtering problem. In contrast to many modern deep learning techniques, we build o…
Revealing the Unobserved by Linking Collaborative Behavior and Side Knowledge
Evgeny Frolov, Ivan Oseledets
We propose a tensor-based model that fuses a more granular representation of user preferences with the ability to take additional side information into account. The model relies on…