In this work, we adapt a training approach inspired by the original Alph...
In this paper, we study learning in probabilistic domains where the lear...
Scaling up the size and training of autoregressive language models has
e...
Abnormal states in deep reinforcement learning (RL) are states that are
...
Materials' microstructures are signatures of their alloying composition ...
In this paper, we study the problem of evaluating the addition of elemen...
Drafting, i.e., the selection of a subset of items from a larger candida...
Boolean Satisfiability (SAT) is a well-known NP-complete problem. Despit...
Social media analysis has become a common approach to assess public opin...
In this work, we release COVID-Twitter-BERT (CT-BERT), a transformer-bas...
Despite its potential to improve sample complexity versus model-free
app...
A state-of-the-art criterion to evaluate the importance of a given learn...
We study the problem of identifying the best action among a set of possi...