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Found 13 papers, 4 papers with code
Exploiting Multiple Abstractions in Episodic RL via Reward Shaping
One major limitation to the applicability of Reinforcement Learning (RL) to many practical domains is the large number of samples required to learn an optimal policy.
A Hierarchical Framework for Collaborative Artificial Intelligence
We propose a hierarchical framework for collaborative intelligent systems.
Image Classification With Small Datasets: Overview and Benchmark
However, as research in this scope is still in its infancy, two key ingredients are missing for ensuring reliable and truthful progress: a systematic and extensive overview of the state of the art, and a common benchmark to allow for objective comparisons between published methods.
On some Foundational Aspects of Human-Centered Artificial Intelligence
The burgeoning of AI has prompted recommendations that AI techniques should be "human-centered".
On the Effectiveness of Neural Ensembles for Image Classification with Small Datasets
For the first time, our work broadly studies the existing concept of neural ensembling in domains with small data, through extensive validation using popular datasets and architectures.
A Strong Baseline for the VIPriors Data-Efficient Image Classification Challenge
Learning from limited amounts of data is the hallmark of intelligence, requiring strong generalization and abstraction skills.
Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification
Data-efficient image classification using deep neural networks in settings, where only small amounts of labeled data are available, has been an active research area in the recent past.
Ranked #1 on
Small Data Image Classification
on DEIC Benchmark
A Reinforcement Learning Environment for Multi-Service UAV-enabled Wireless Systems
We design a multi-purpose environment for autonomous UAVs offering different communication services in a variety of application contexts (e. g., wireless mobile connectivity services, edge computing, data gathering).
On the Effectiveness of Deep Ensembles for Small Data Tasks
Deep neural networks represent the gold standard for image classification and many other tasks.
Proceedings of the AI-HRI Symposium at AAAI-FSS 2019
The past few years have seen rapid progress in the development of service robots.
Robotics
Foundations for Restraining Bolts: Reinforcement Learning with LTLf/LDLf restraining specifications
In this work we investigate on the concept of "restraining bolt", envisioned in Science Fiction.
HuRIC: a Human Robot Interaction Corpus
Recent years show the development of large scale resources (e. g. FrameNet for the Frame Semantics) that supported the definition of several state-of-the-art approaches in Natural Language Processing.
Knowledge Representation for Robots through Human-Robot Interaction
The representation of the knowledge needed by a robot to perform complex tasks is restricted by the limitations of perception.
