We propose a self-supervised learning method for long text documents bas...
The recent advances in representation learning inspire us to take on the...
Neural approaches for combinatorial optimization (CO) equip a learning
m...
Denoising diffusion probabilistic models (DDPM) have shown remarkable
pe...
Machine Learning (ML) can help solve combinatorial optimization (CO) pro...
A Lite BERT (ALBERT) has been introduced to scale up deep bidirectional
...
In zero-shot cross-lingual transfer, a supervised NLP task trained on a
...
Contextualized representations from a pre-trained language model are cen...
This paper introduces SelfMatch, a semi-supervised learning method that
...
In neural combinatorial optimization (CO), reinforcement learning (RL) c...
Active Learning for discriminative models has largely been studied with ...
We propose DefogGAN, a generative approach to the problem of inferring s...
We introduce fast millimeter-wave base station (BS) and its antenna sect...
We present a clustering-based language model using word embeddings for t...
Unsupervised methods have proven effective for discriminative tasks in a...