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09/07/2023
On the dynamics of multi agent nonlinear filtering and learning
Multiagent systems aim to accomplish highly complex learning tasks throu...
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05/30/2023
Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting
Existing relationships among time series can be exploited as inductive b...
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01/12/2023
Fair and skill-diverse student group formation via constrained k-way graph partitioning
Forming the right combination of students in a group promises to enable ...
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11/09/2022
Hyper-GST: Predict Metro Passenger Flow Incorporating GraphSAGE, Hypergraph, Social-meaningful Edge Weights and Temporal Exploitation
Predicting metro passenger flow precisely is of great importance for dyn...
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10/16/2022
Demystifying CNNs for Images by Matched Filters
The success of convolution neural networks (CNN) has been revolutionisin...
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07/18/2022
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks
Graph Neural Networks (GNNs) tend to suffer from high computation costs ...
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05/30/2022
Last-iterate convergence analysis of stochastic momentum methods for neural networks
The stochastic momentum method is a commonly used acceleration technique...
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05/30/2022
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis
Binaural audio plays a significant role in constructing immersive augmen...
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02/08/2022
InferGrad: Improving Diffusion Models for Vocoder by Considering Inference in Training
Denoising diffusion probabilistic models (diffusion models for short) re...
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08/26/2021
Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial
Deep Neural Networks (DNN) and especially Convolutional Neural Networks ...
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08/23/2021
Understanding the Basis of Graph Convolutional Neural Networks via an Intuitive Matched Filtering Approach
Graph Convolutional Neural Networks (GCNN) are becoming a preferred mode...
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03/14/2021
Von Mises-Fisher Elliptical Distribution
A large class of modern probabilistic learning systems assumes symmetric...
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03/11/2021
Improved Coherence Index-Based Bound in Compressive Sensing
Within the Compressive Sensing (CS) paradigm, sparse signals can be reco...
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12/11/2020
A Review of Hidden Markov Models and Recurrent Neural Networks for Event Detection and Localization in Biomedical Signals
Biomedical signals carry signature rhythms of complex physiological proc...
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06/15/2020
Reciprocal Adversarial Learning via Characteristic Functions
Generative adversarial nets (GANs) have become a preferred tool for acco...
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03/10/2020
Methods of Adaptive Signal Processing on Graphs Using Vertex-Time Autoregressive Models
The concept of a random process has been recently extended to graph sign...
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01/02/2020
Graph Signal Processing – Part III: Machine Learning on Graphs, from Graph Topology to Applications
Many modern data analytics applications on graphs operate on domains whe...
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09/23/2019
Graph Signal Processing – Part II: Processing and Analyzing Signals on Graphs
The focus of Part I of this monograph has been on both the fundamental p...
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07/08/2019
Graph Signal Processing -- Part I: Graphs, Graph Spectra, and Spectral Clustering
The area of Data Analytics on graphs promises a paradigm shift as we app...
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06/09/2019
A general solver to the elliptical mixture model through an approximate Wasserstein manifold
This paper studies the problem of estimation for general finite mixture ...
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03/31/2019
On the Decomposition of Multivariate Nonstationary Multicomponent Signals
With their ability to handle an increased amount of information, multiva...
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03/26/2019
An Intuitive Derivation of the Coherence Index Relation in Compressive Sensing
The existence and uniqueness conditions are a prerequisite for reliable ...
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03/05/2019
Widely Linear Complex-valued Autoencoder: Dealing with Noncircularity in Generative-Discriminative Models
We propose a new structure for the complex-valued autoencoder by introdu...
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09/07/2018
Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion
In tensor completion tasks, the traditional low-rank tensor decompositio...
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09/03/2018
Tensor Networks for Latent Variable Analysis: Higher Order Canonical Polyadic Decomposition
The Canonical Polyadic decomposition (CPD) is a convenient and intuitive...
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05/22/2018
Rank Minimization on Tensor Ring: A New Paradigm in Scalable Tensor Decomposition and Completion
In low-rank tensor completion tasks, due to the underlying multiple larg...
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03/07/2017
Online Multilinear Dictionary Learning for Sequential Compressive Sensing
A method for online tensor dictionary learning is proposed. With the ass...
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12/17/2012