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01/18/2023
A variational autoencoder-based nonnegative matrix factorisation model for deep dictionary learning
Construction of dictionaries using nonnegative matrix factorisation (NMF...
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01/17/2023
Free Lunch for Generating Effective Outlier Supervision
When deployed in practical applications, computer vision systems will en...
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02/04/2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning
PAC-Bayesian is an analysis framework where the training error can be ex...
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09/19/2021
Regularize! Don't Mix: Multi-Agent Reinforcement Learning without Explicit Centralized Structures
We propose using regularization for Multi-Agent Reinforcement Learning r...
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09/19/2021
Dual Behavior Regularized Reinforcement Learning
Reinforcement learning has been shown to perform a range of complex task...
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09/19/2021
Greedy UnMixing for Q-Learning in Multi-Agent Reinforcement Learning
This paper introduces Greedy UnMix (GUM) for cooperative multi-agent rei...
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08/05/2021
dp-GAN : Alleviating Mode Collapse in GAN via Diversity Penalty Module
The vanilla GAN [5] suffers from mode collapse deeply, which usually man...
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03/03/2021
Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss
Graph convolutional networks (GCNs) and their variants have achieved gre...
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01/12/2021
Resolution-invariant Person ReID Based on Feature Transformation and Self-weighted Attention
Person Re-identification (ReID) is a critical computer vision task which...
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12/22/2020
Revealing the Transmission Dynamics of COVID-19: A Bayesian Framework for R_t Estimation
In epidemiological modelling, the instantaneous reproduction number, R_t...
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11/25/2020
Implicit bias of deep linear networks in the large learning rate phase
Correctly choosing a learning rate (scheme) for gradient-based optimizat...
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04/13/2020
On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization
In recent years, a critical initialization scheme with orthogonal initia...
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12/19/2019
Gaussian Process Latent Variable Model Factorization for Context-aware Recommender Systems
Context-aware recommender systems (CARS) have gained increasing attentio...
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12/19/2019
Mean field theory for deep dropout networks: digging up gradient backpropagation deeply
In recent years, the mean field theory has been applied to the study of ...
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07/15/2018
Magnitude Bounded Matrix Factorisation for Recommender Systems
Low rank matrix factorisation is often used in recommender systems as a ...
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06/12/2018
Diverse Online Feature Selection
Online feature selection has been an active research area in recent year...
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07/18/2017
Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization
The cooperative hierarchical structure is a common and significant data ...
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06/27/2016
The Dependent Random Measures with Independent Increments in Mixture Models
When observations are organized into groups where commonalties exist amo...
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04/16/2016
Smoothed Hierarchical Dirichlet Process: A Non-Parametric Approach to Constraint Measures
Time-varying mixture densities occur in many scenarios, for example, the...
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02/09/2016
Bayesian nonparametric image segmentation using a generalized Swendsen-Wang algorithm
Unsupervised image segmentation aims at clustering the set of pixels of ...
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03/30/2015
Nonparametric Relational Topic Models through Dependent Gamma Processes
Traditional Relational Topic Models provide a way to discover the hidden...
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03/30/2015
Infinite Author Topic Model based on Mixed Gamma-Negative Binomial Process
Incorporating the side information of text corpus, i.e., authors, time s...
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03/10/2015
An Adaptive Online HDP-HMM for Segmentation and Classification of Sequential Data
In the recent years, the desire and need to understand sequential data h...
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10/06/2013
Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network
Effectively modelling hidden structures in a network is very practical b...
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07/02/2013
A non-parametric conditional factor regression model for high-dimensional input and response
In this paper, we propose a non-parametric conditional factor regression...
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06/13/2013
Dynamic Infinite Mixed-Membership Stochastic Blockmodel
Directional and pairwise measurements are often used to model inter-rela...
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06/12/2013
