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06/01/2023
Masked Autoencoders with Multi-Window Attention Are Better Audio Learners
Several recent works have adapted Masked Autoencoders (MAEs) for learnin...
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05/28/2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling
Sparse modeling for signal processing and machine learning has been at t...
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12/05/2021
Stochastic Local Winner-Takes-All Networks Enable Profound Adversarial Robustness
This work explores the potency of stochastic competition-based activatio...
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09/15/2021
Dialog speech sentiment classification for imbalanced datasets
Speech is the most common way humans express their feelings, and sentime...
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01/04/2021
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning
This work addresses adversarial robustness in deep learning by consideri...
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09/05/2020
Towards Probabilistic Tensor Canonical Polyadic Decomposition 2.0: Automatic Tensor Rank Learning Using Generalized Hyperbolic Prior
Tensor rank learning for canonical polyadic decomposition (CPD) has long...
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05/12/2020
Early soft and flexible fusion of EEG and fMRI via tensor decompositions
Data fusion refers to the joint analysis of multiple datasets which prov...
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03/08/2020
FedLoc: Federated Learning Framework for Cooperative Localization and Location Data Processing
In this paper, we propose a new localization framework in which mobile u...
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02/13/2020
Variational Conditional-Dependence Hidden Markov Models for Human Action Recognition
Hidden Markov Models (HMMs) are a powerful generative approach for model...
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04/21/2019
Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series
Gaussian processes (GP) for machine learning have been studied systemati...
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05/19/2018
Nonparametric Bayesian Deep Networks with Local Competition
Local competition among neighboring neurons is a common procedure taking...
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04/20/2018
Unsupervised learning of the brain connectivity dynamic using residual D-net
In this paper, we propose a novel unsupervised learning method to learn ...
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02/05/2018
Information Assisted Dictionary Learning for fMRI data analysis
Extracting information from functional magnetic resonance images (fMRI) ...
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10/11/2016
Assisted Dictionary Learning for fMRI Data Analysis
Extracting information from functional magnetic resonance (fMRI) images ...
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07/15/2016
Higher-Order Block Term Decomposition for Spatially Folded fMRI Data
The growing use of neuroimaging technologies generates a massive amount ...
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06/12/2016
Efficient KLMS and KRLS Algorithms: A Random Fourier Feature Perspective
We present a new framework for online Least Squares algorithms for nonli...
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01/04/2016
Robust Non-linear Regression: A Greedy Approach Employing Kernels with Application to Image Denoising
We consider the task of robust non-linear regression in the presence of ...
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03/09/2013
Complex Support Vector Machines for Regression and Quaternary Classification
The paper presents a new framework for complex Support Vector Regression...
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11/27/2010
