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11/30/2022
Continual Learning with Optimal Transport based Mixture Model
Online Class Incremental learning (CIL) is a challenging setting in Cont...
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11/19/2022
Face Swapping as A Simple Arithmetic Operation
We propose a novel high-fidelity face swapping method called "Arithmetic...
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07/26/2021
From Implicit to Explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online users
In this work, we examine the advantages of using multiple types of behav...
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04/06/2021
Generalization of GANs under Lipschitz continuity and data augmentation
Generative adversarial networks (GANs) have been being widely used in va...
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02/16/2021
Improving Bayesian Inference in Deep Neural Networks with Variational Structured Dropout
Approximate inference in deep Bayesian networks exhibits a dilemma of ho...
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03/26/2020
Bag of biterms modeling for short texts
Analyzing texts from social media encounters many challenges due to thei...
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03/13/2020
Dynamic transformation of prior knowledge intoBayesian models for data streams
We consider how to effectively use prior knowledge when learning a Bayes...
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03/13/2020
Dynamic transformation of prior knowledge into Bayesian models for data streams
We consider how to effectively use prior knowledge when learning a Bayes...
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03/13/2020
Graph Convolutional Topic Model for Data Streams
Learning hidden topics in data streams has been paid a great deal of att...
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03/02/2020
Predictive Coding for Locally-Linear Control
High-dimensional observations and unknown dynamics are major challenges ...
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12/10/2015
Guaranteed inference in topic models
One of the core problems in statistical models is the estimation of a po...
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12/10/2015
Inference in topic models: sparsity and trade-off
Topic models are popular for modeling discrete data (e.g., texts, images...
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12/16/2013
Probable convexity and its application to Correlated Topic Models
Non-convex optimization problems often arise from probabilistic modeling...
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10/26/2012