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12/15/2022
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation
Recent image degradation estimation methods have enabled single-image su...
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10/19/2022
Rethinking Sharpness-Aware Minimization as Variational Inference
Sharpness-aware minimization (SAM) aims to improve the generalisation of...
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03/29/2022
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data
Learning invariant causal structure often relies on conditional independ...
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02/03/2022
Measuring Disparate Outcomes of Content Recommendation Algorithms with Distributional Inequality Metrics
The harmful impacts of algorithmic decision systems have recently come i...
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11/22/2021
Depth Without the Magic: Inductive Bias of Natural Gradient Descent
In gradient descent, changing how we parametrize the model can lead to d...
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10/21/2021
Algorithmic Amplification of Politics on Twitter
Content on Twitter's home timeline is selected and ordered by personaliz...
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10/12/2020
Efficient Wasserstein Natural Gradients for Reinforcement Learning
A novel optimization approach is proposed for application to policy grad...
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08/03/2020
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations
Recommender systems trained in a continuous learning fashion are plagued...
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07/28/2020
Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems
Deep Neural Networks (DNNs) with sparse input features have been widely ...
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07/15/2019
Addressing Delayed Feedback for Continuous Training with Neural Networks in CTR prediction
One of the challenges in display advertising is that the distribution of...
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07/05/2018
Adaptive Paired-Comparison Method for Subjective Video Quality Assessment on Mobile Devices
To effectively evaluate subjective visual quality in weakly-controlled e...
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02/21/2018
A Generative Deep Recurrent Model for Exchangeable Data
We present a novel model architecture which leverages deep learning tool...
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01/17/2018
Faster gaze prediction with dense networks and Fisher pruning
Predicting human fixations from images has recently seen large improveme...
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12/11/2017
On Quadratic Penalties in Elastic Weight Consolidation
Elastic weight consolidation (EWC, Kirkpatrick et al, 2017) is a novel a...
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03/01/2017
Lossy Image Compression with Compressive Autoencoders
We propose a new approach to the problem of optimizing autoencoders for ...
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02/27/2017
Variational Inference using Implicit Distributions
Generative adversarial networks (GANs) have given us a great tool to fit...
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10/14/2016
Amortised MAP Inference for Image Super-resolution
Image super-resolution (SR) is an underdetermined inverse problem, where...
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09/22/2016
Is the deconvolution layer the same as a convolutional layer?
In this note, we want to focus on aspects related to two questions most ...
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09/16/2016
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Recently, several models based on deep neural networks have achieved gre...
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09/15/2016
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Despite the breakthroughs in accuracy and speed of single image super-re...
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11/16/2015
How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary?
Modern applications and progress in deep learning research have created ...
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08/09/2014
Optimally-Weighted Herding is Bayesian Quadrature
Herding and kernel herding are deterministic methods of choosing samples...
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12/24/2011
Bayesian Active Learning for Classification and Preference Learning
Information theoretic active learning has been widely studied for probab...
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03/09/2011