Toward automatically labeling situations in soccer
D Fassmeyer, G Anzer, P Bauer… - Frontiers in Sports and …, 2021 - frontiersin.org
We study the automatic annotation of situations in soccer games. At first sight, this translates
nicely into a standard supervised learning problem. However, in a fully supervised setting …
nicely into a standard supervised learning problem. However, in a fully supervised setting …
Event representation with sequential, semi-supervised discrete variables
Within the context of event modeling and understanding, we propose a new method for
neural sequence modeling that takes partially-observed sequences of discrete, external …
neural sequence modeling that takes partially-observed sequences of discrete, external …
Near-optimal glimpse sequences for improved hard attention neural network training
Hard visual attention is a promising approach to reduce the computational burden of modern
computer vision methodologies. However, hard attention mechanisms can be difficult and …
computer vision methodologies. However, hard attention mechanisms can be difficult and …
From Latent Knowledge Gathering to Side Information Injection in Discrete Sequential Models
MMR Taghiabadi - 2024 - search.proquest.com
Abstract Representation learning is crucial for processing sequential and discrete data, such
as text in natural language processing (NLP). From classical methods like topic modeling to …
as text in natural language processing (NLP). From classical methods like topic modeling to …
Near-Optimal Glimpse Sequences for Training Hard Attention Neural Networks
Hard visual attention is a promising approach to reduce the computational burden of modern
computer vision methodologies. Hard attention mechanisms are typically non-differentiable …
computer vision methodologies. Hard attention mechanisms are typically non-differentiable …