Offline reinforcement learning (RL) is a promising direction that allows...
Road traffic scene reconstruction from videos has been desirable by road...
The replicability crisis in the social, behavioral, and data sciences ha...
Like generic multi-task learning, continual learning has the nature of
m...
Despite the advancement of machine learning techniques in recent years,
...
Satellite image analysis has important implications for land use,
urbani...
A major goal of artificial intelligence (AI) is to create an agent capab...
We present CompoSuite, an open-source simulated robotic manipulation
ben...
Methods for learning from demonstration (LfD) have shown success in acqu...
Humans commonly solve complex problems by decomposing them into easier
s...
While deep neural networks (DNNs) have achieved impressive classificatio...
Research on both natural intelligence (NI) and artificial intelligence (...
What is learning? 20^st century formalizations of learning theory –
whic...
Bird's Eye View (BEV) is a popular representation for processing 3D poin...
A hallmark of human intelligence is the ability to construct self-contai...
Policy gradient methods have shown success in learning control policies ...
Additive models, such as produced by gradient boosting, and full interac...
Knowledge transfer between tasks can improve the performance of learned
...
The 7th Symposium on Educational Advances in Artificial Intelligence
(EA...
Conceived in the early 1990s, Experience Replay (ER) has been shown to b...
Estimation, recognition, and near-future prediction of 3D trajectories b...
Multi-view learning algorithms typically assume a complete bipartite map...