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12/10/2020
GNN-XML: Graph Neural Networks for Extreme Multi-label Text Classification
Extreme multi-label text classification (XMTC) aims to tag a text instan...
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11/23/2020
Manifold Partition Discriminant Analysis
We propose a novel algorithm for supervised dimensionality reduction nam...
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06/19/2020
Adversarial Attacks for Multi-view Deep Models
Recent work has highlighted the vulnerability of many deep machine learn...
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11/25/2019
Adversarial Attack with Pattern Replacement
We propose a generative model for adversarial attack. The model generate...
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06/17/2019
A Survey of Optimization Methods from a Machine Learning Perspective
Machine learning develops rapidly, which has made many theoretical break...
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06/09/2019
A Variant of Gaussian Process Dynamical Systems
In order to better model high-dimensional sequential data, we propose a ...
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06/01/2019
Variational Langevin Hamiltonian Monte Carlo for Distant Multi-modal Sampling
The Hamiltonian Monte Carlo (HMC) sampling algorithm exploits Hamiltonia...
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05/14/2019
Online Anomaly Detection with Sparse Gaussian Processes
Online anomaly detection of time-series data is an important and challen...
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06/18/2018
PAC-Bayes bounds for stable algorithms with instance-dependent priors
PAC-Bayes bounds have been proposed to get risk estimates based on a tra...
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12/25/2017
Kernel Regression with Sparse Metric Learning
Kernel regression is a popular non-parametric fitting technique. It aims...
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12/25/2017
Network-Scale Traffic Modeling and Forecasting with Graphical Lasso and Neural Networks
Traffic flow forecasting, especially the short-term case, is an importan...
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12/24/2017
Weighted Data Normalization Based on Eigenvalues for Artificial Neural Network Classification
Artificial neural network (ANN) is a very useful tool in solving learnin...
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12/24/2017
Traffic Flow Forecasting Using a Spatio-Temporal Bayesian Network Predictor
A novel predictor for traffic flow forecasting, namely spatio-temporal B...
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12/24/2017
Neural Network Multitask Learning for Traffic Flow Forecasting
Traditional neural network approaches for traffic flow forecasting are u...
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12/18/2017
A Survey on Multi-View Clustering
With the fast development of information technology, especially the popu...
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07/02/2017
Location Dependent Dirichlet Processes
Dirichlet processes (DP) are widely applied in Bayesian nonparametric mo...
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01/17/2017
Multi-view Regularized Gaussian Processes
Gaussian processes (GPs) have been proven to be powerful tools in variou...
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06/21/2014
PAC-Bayes Analysis of Multi-view Learning
This paper presents eight PAC-Bayes bounds to analyze the generalization...
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07/26/2013
Infinite Mixtures of Multivariate Gaussian Processes
This paper presents a new model called infinite mixtures of multivariate...
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07/26/2013