Deep artificial neural networks achieve surprising generalization abilit...
Randomized smoothing is a technique for providing provable robustness
gu...
Score-based generative modeling, informally referred to as diffusion mod...
Modern machine learning pipelines, in particular those based on deep lea...
Susceptibility tensor imaging (STI) is an emerging magnetic resonance im...
Although machine learning classifiers have been increasingly used in
hig...
Machine learning models, in particular artificial neural networks, are
i...
This work studies the adversarial robustness of parametric functions com...
Sparse Principal Component Analysis (PCA) is a prevalent tool across a
p...
Research on both natural intelligence (NI) and artificial intelligence (...
In response to pathogens, the adaptive immune system generates specific
...
Annotating cancerous regions in whole-slide images (WSIs) of pathology
s...
We provide the first global optimization landscape analysis of
Neural Co...
As modern complex neural networks keep breaking records and solving hard...
Several recent results provide theoretical insights into the phenomena o...
Total Variation (TV) is a popular regularization strategy that promotes
...
Quantitative Susceptibility Mapping (QSM) estimates tissue magnetic
susc...
Deep learning is catalyzing a scientific revolution fueled by big data,
...
In over two decades of research, the field of dictionary learning has
ga...
Although momentum-based optimization methods have had a remarkable impac...
The Convolutional Sparse Coding (CSC) model has recently gained consider...
Sparse Representation Theory is a sub-field of signal processing that ha...
Parsimonious representations in data modeling are ubiquitous and central...
The recently proposed multi-layer sparse model has raised insightful
con...
The recently proposed Multi-Layer Convolutional Sparse Coding (ML-CSC) m...
Convolutional Sparse Coding (CSC) is an increasingly popular model in th...
Sparse representations has shown to be a very powerful model for real wo...