django rest framework test

Classical Probabilistic Models and Conditional Random Fields

Feature Construction for Reinforcement Learning in Hearts

Temporal difference (TD) learning has been used to learn strong evaluation functions in a variety of two-player games. TD-gammon illustrated how the combination of game tree search and learning methods can achieve grand-master level play in backgammon. In this work, we develop a player for the game of hearts, a 4-player game, based on stochastic linear regression and TD learning. Using a small set of basic game features we exhaustively combined features into a more expressive representation of the game state. We report initial results on learning with various combinations of features and training under self-play and against search-based players. Our simple learner was able to beat one of the best search-based hearts programs.

Neural Machine Translation of Rare Words with Subword Units

BLEU: a Method for Automatic Evaluation of Machine Translation

Effective Approaches to Attention-based Neural Machine Translation

Neural_Machine_Translation_by_Jointly_Learning_to_Align_and_Translate

Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance.

Attention Is All You Need 中文翻译