Humans are able to recognize structured relations in observation, allowing us to decompose
complex scenes into simpler parts and abstract the visual world in multiple levels. However …

Neural networks (NNs) and decision trees (DTs) are both popular models of machine
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

Two things seem to be indisputable in the contemporary deep learning discourse: 1. The
categorical cross-entropy loss after softmax activation is the method of choice for …

Deep neural networks have improved image classification dramatically over the past
decade, but have done so by focusing on performance measures that treat all classes other …

Humans are able to recognize structured relations in observation, allowing us to decompose
complex scenes into simpler parts and abstract the visual world at multiple levels. However …

Open-vocabulary object detection (OvOD) has transformed detection into a language-
guided task empowering users to freely define their class vocabularies of interest during …

Current video retrieval efforts all found their evaluation on an instance-based assumption,
that only a single caption is relevant to a query video and vice versa. We demonstrate that …

Neural networks (NNs) and decision trees (DTs) are both popular models of machine
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …

Embedding representations power machine intelligence in many applications, including
recommendation systems, but they are space intensive-potentially occupying hundreds of …