AAAI 2019 Highlights: Dialogue, reproducibility, and more
AAAI 2019 Highlights: Dialogue, reproducibility, and more This post discusses highlights of AAAI 2019. It covers dialogue, reproducibility, question answering, the Oxford style debate, invited talks, and a diverse set of research papers. This post discusses highlights of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19). I attended AAAI 2019 in Honolulu, Hawaii last week. Overa
Optimization for Deep Learning Highlights in 2017
Optimization for Deep Learning Highlights in 2017 Different gradient descent optimization algorithms have been proposed in recent years but Adam is still most commonly used. This post discusses the most exciting highlights and most promising recent approaches that may shape the way we will optimize our models in the future. This post discusses the most exciting highlights and most promising direct
Word embeddings in 2017: Trends and future directions
Word embeddings in 2017: Trends and future directions Word embeddings are an integral part of current NLP models, but approaches that supersede the original word2vec have not been proposed. This post focuses on the deficiencies of word embeddings and how recent approaches have tried to resolve them. This post discusses the deficiencies of word embeddings and how recent approaches have tried to res
Deep Learning for NLP Best Practices
Deep Learning for NLP Best Practices Neural networks are widely used in NLP, but many details such as task or domain-specific considerations are left to the practitioner. This post collects best practices that are relevant for most tasks in NLP. This post gives an overview of best practices relevant for most tasks in natural language processing. Update July 26, 2017: For additional context, the Ha
Transfer Learning - Machine Learning's Next Frontier
Transfer Learning - Machine Learning's Next Frontier Deep learning models excel at learning from a large number of labeled examples, but typically do not generalize to conditions not seen during training. This post gives an overview of transfer learning, motivates why it warrants our application, and discusses practical applications and methods. This post gives an overview of transfer learning and
1
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
処理を実行中です
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
