5 citations · 11 across the 5 of their papers we have counts for
5 papers
Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning
Raphael Lafargue, Luke Smith, Franck Vermet +4
The predominant method for computing confidence intervals (CI) in few-shot learning (FSL) is based on sampling the tasks with replacement, i.e.\ allowing the same samples to appear…
Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning
Mathias Löwe, Jennifer Villareale, Evan Freed +3
Applying neural network (NN) methods in games can lead to various new and exciting game dynamics not previously possible. However, they also lead to new challenges such as the lack…
Rapid Risk Minimization with Bayesian Models Through Deep Learning Approximation
Mathias Löwe, Per Lunnemann Hansen, Sebastian Risi
We introduce a novel combination of Bayesian Models (BMs) and Neural Networks (NNs) for making predictions with a minimum expected risk. Our approach combines the best of both worl…
Player-AI Interaction: What Neural Network Games Reveal About AI as Play
Jichen Zhu, Jennifer Villareale, Nithesh Javvaji +4
The advent of artificial intelligence (AI) and machine learning (ML) bring human-AI interaction to the forefront of HCI research. This paper argues that games are an ideal domain f…
iNNk: A Multi-Player Game to Deceive a Neural Network
Jennifer Villareale, Ana Acosta-Ruiz, Samuel Arcaro +10
This paper presents iNNK, a multiplayer drawing game where human players team up against an NN. The players need to successfully communicate a secret code word to each other throug…