Human-in-the-loop machine learning: a state of the art
E Mosqueira-Rey, E Hernández-Pereira… - Artificial Intelligence …, 2023 - Springer
Researchers are defining new types of interactions between humans and machine learning
algorithms generically called human-in-the-loop machine learning. Depending on who is in …
algorithms generically called human-in-the-loop machine learning. Depending on who is in …
Quality control in crowdsourcing: A survey of quality attributes, assessment techniques, and assurance actions
Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large
groups of individuals toward solving problems. Common problems approached with …
groups of individuals toward solving problems. Common problems approached with …
The inaturalist species classification and detection dataset
Existing image classification datasets used in computer vision tend to have a uniform
distribution of images across object categories. In contrast, the natural world is heavily …
distribution of images across object categories. In contrast, the natural world is heavily …
On human predictions with explanations and predictions of machine learning models: A case study on deception detection
Humans are the final decision makers in critical tasks that involve ethical and legal
concerns, ranging from recidivism prediction, to medical diagnosis, to fighting against fake …
concerns, ranging from recidivism prediction, to medical diagnosis, to fighting against fake …
Submodularity in data subset selection and active learning
We study the problem of selecting a subset of big data to train a classifier while incurring
minimal performance loss. We show the connection of submodularity to the data likelihood …
minimal performance loss. We show the connection of submodularity to the data likelihood …
The effectiveness of feature attribution methods and its correlation with automatic evaluation scores
Explaining the decisions of an Artificial Intelligence (AI) model is increasingly critical in many
real-world, high-stake applications. Hundreds of papers have either proposed new feature …
real-world, high-stake applications. Hundreds of papers have either proposed new feature …
An overview of machine teaching
In this paper we try to organize machine teaching as a coherent set of ideas. Each idea is
presented as varying along a dimension. The collection of dimensions then form the …
presented as varying along a dimension. The collection of dimensions then form the …
Visual correspondence-based explanations improve AI robustness and human-AI team accuracy
MR Taesiri, G Nguyen… - Advances in Neural …, 2022 - proceedings.neurips.cc
Explaining artificial intelligence (AI) predictions is increasingly important and even
imperative in many high-stake applications where humans are the ultimate decision-makers …
imperative in many high-stake applications where humans are the ultimate decision-makers …
Enabling robots to communicate their objectives
The overarching goal of this work is to efficiently enable end-users to correctly anticipate a
robot's behavior in novel situations. And since a robot's behavior is often a direct result of its …
robot's behavior in novel situations. And since a robot's behavior is often a direct result of its …
Iterative machine teaching
In this paper, we consider the problem of machine teaching, the inverse problem of machine
learning. Different from traditional machine teaching which views the learners as batch …
learning. Different from traditional machine teaching which views the learners as batch …