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08/31/2022
One-class Recommendation Systems with the Hinge Pairwise Distance Loss and Orthogonal Representations
In one-class recommendation systems, the goal is to learn a model from a...
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03/14/2022
Simultaneous Learning of the Inputs and Parameters in Neural Collaborative Filtering
Neural network-based collaborative filtering systems focus on designing ...
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12/06/2020
Estimating Vector Fields from Noisy Time Series
While there has been a surge of recent interest in learning differential...
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10/12/2020
Neural Representations in Hybrid Recommender Systems: Prediction versus Regularization
Autoencoder-based hybrid recommender systems have become popular recentl...
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10/16/2018
A Direct Method to Learn States and Parameters of Ordinary Differential Equations
Though ordinary differential equations (ODE) are used extensively in sci...
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02/04/2016
An ensemble diversity approach to supervised binary hashing
Binary hashing is a well-known approach for fast approximate nearest-nei...
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01/21/2015
Optimizing affinity-based binary hashing using auxiliary coordinates
In supervised binary hashing, one wants to learn a function that maps a ...
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01/05/2015
