P. Baudis

We present a state of the art implementation of the Monte Carlo Tree Search algorithm for the game of Go. Expand

We briefly survey the current state of art in the field of Question Answering and present the YodaQA system, an open source framework for this task and a baseline pipeline with reasonable performance. Expand

Monte-Carlo Tree Search tends to produce unstable and unreasonable results in the game of Go when used in positions with an extreme advantage or disadvantage. Expand

We consider the problem of Recognizing Textual Entailment within an Information Retrieval context, where we must simultaneously determine the relevancy as and degree of entailment for individual pieces of evidence to determine a yes/no answer to a binary natural language question. Expand

This article explores the possibility to choose the dimension for the next step in a more "intelligent way", i.e. to optimize first along dimensions which are believed to bring the highest profit. Expand

We investigate algorithm selection through the Multi-Armed Bandit scenario for continuous black-box optimization. Expand

We process a large corpus of game records of the board game of Go and propose a way of extracting summary information on played moves. Expand

We propose a way of extracting and aggregating per-move evaluations from sets of Go game records. Expand

Table detection and extraction has been studied in the context of documents like reports, where tables are clearly outlined and stand out from the document structure visually. Expand