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09/13/2023
Open-vocabulary Keyword-spotting with Adaptive Instance Normalization
Open vocabulary keyword spotting is a crucial and challenging task in au...
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07/04/2023
Learning Discrete Weights and Activations Using the Local Reparameterization Trick
In computer vision and machine learning, a crucial challenge is to lower...
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01/31/2023
Auxiliary Learning as an Asymmetric Bargaining Game
Auxiliary learning is an effective method for enhancing the generalizati...
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01/30/2023
Equivariant Architectures for Learning in Deep Weight Spaces
Designing machine learning architectures for processing neural networks ...
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06/22/2022
A Study on the Evaluation of Generative Models
Implicit generative models, which do not return likelihood values, such ...
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02/02/2022
Multi-Task Learning as a Bargaining Game
In Multi-task learning (MTL), a joint model is trained to simultaneously...
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06/29/2021
Personalized Federated Learning with Gaussian Processes
Federated learning aims to learn a global model that performs well on cl...
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03/08/2021
Personalized Federated Learning using Hypernetworks
Personalized federated learning is tasked with training machine learning...
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02/15/2021
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
Gaussian processes (GPs) are non-parametric, flexible, models that work ...
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10/08/2020
Learning the Pareto Front with Hypernetworks
Multi-objective optimization problems are prevalent in machine learning....
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12/10/2018
