Training a deep learning model to classify histopathological images is
c...
The generative modeling landscape has experienced tremendous growth in r...
Text-based game environments are challenging because agents must deal wi...
Synthetic image generation has recently experienced significant improvem...
A well-known failure mode of neural networks corresponds to high confide...
Text-based dialogues are now widely used to solve real-world problems. I...
In this paper, we explore the use of GAN-based few-shot data augmentatio...
We introduce Neural Point Light Fields that represent scenes implicitly ...
We investigate the convergence of stochastic mirror descent (SMD) in
rel...
Labeling data is often expensive and time-consuming, especially for task...
Recent work has made significant progress in learning object meshes with...
Explainability for machine learning models has gained considerable atten...
Cattle farming is responsible for 8.8% of greenhouse gas emissions
world...
Aquaculture industries rely on the availability of accurate fish body
me...
Progress in the field of machine learning has been fueled by the introdu...
In the last few years, we have witnessed a renewed and fast-growing inte...
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has rap...
Acquiring count annotations generally requires less human effort than
po...
Data augmentation is a key practice in machine learning for improving
ge...
As adaptive gradient methods are typically used for training
over-parame...
Learning from non-stationary data remains a great challenge for machine
...
Few-shot classification is challenging because the data distribution of ...
We propose a stochastic variant of the classical Polyak step-size (Polya...
We consider stochastic second order methods for minimizing strongly-conv...
We propose a Class-Based Styling method (CBS) that can map different sty...
Recent works have shown that stochastic gradient descent (SGD) achieves ...
Unsupervised domain adaptation techniques have been successful for a wid...