概要 †

Statistical Relational Learning (SRL) の代表的な枠組みのひとつである Markov Logic Networks [Richardson & Domingos 2006] とその周辺技術を理解し、SRL に関する研究動向を把握する。

記 †

日時

毎週水曜日 17:00-（ご飯を食べながら）

参加者

乾，渡邉，水野，井之上，山本，岡崎

方法 †

• Pedro Domingos 氏の講義資料（http://homes.cs.washington.edu/~pedrod/803/）を参考に進める
• 各回の説明担当者を決めておき、講義資料またはオリジナルの説明資料を用いて発表してもらう
  • 担当者は事前に参考文献を読み、ひととおり説明できるようにしておく
• ご飯（ピザ、カレーほか）を食べながら勉強する

参考文献 †

Pedro Domingos and Daniel Lowd,
Markov Logic: An Interface Layer for AI, Morgan & Claypool, 2008.

• Video Lectures
  • Combining Logic and Probability: Languages, Algorithms and Applications@UAI2011
  • Markov Logic: A Unifying Language for Information and Knowledge Management@CIKM2008
  • Incorporating Prior Knowledge into NLP with Markov Logic@ICML

担当 †

参考リンク（ソフトウェア） †

• Alchemy (http://alchemy.cs.washington.edu/)
• Alchemy 2.0 (https://code.google.com/p/alchemy-2/)
• Tuffy (http://hazy.cs.wisc.edu/hazy/tuffy/)
• markov thebeast (https://code.google.com/p/thebeast/)
• rockit (https://code.google.com/p/rockit/)
• Walksat (http://www.cs.rochester.edu/u/kautz/walksat/)

参考リンク（論文） †

• Application to discourse processing
  • Yufang Hou and Katja Markert and Michael Strube. Global Inference for Bridging Anaphora Resolution. NAACL-HLT2013. pdf
  • Islam Beltagy and Cuong Chau and Gemma Boleda and Dan Garrette and Katrin Erk and Raymond Mooney. Montague Meets Markov: Deep Semantics with Probabilistic Logical Form. *SEM2013. pdf
  • Katsumasa Yoshikawa, Masayuki Asahara, Yuji Matsumoto. Jointly Extracting Japanese Predicate-Argument Relation with Markov Logic. IJCNLP2011. pdf
  • James Blythe, Jerry R. Hobbs, Pedro Domingos, Rohit J. Kate and Raymond J. Mooney. Implementing Weighted Abduction in Markov Logic. IWCS2011. pdf
  • Dan Garrette, Katrin Erk, Raymond Mooney. Integrating Logical Representations with Probabilistic Information using Markov Logic. IWCS2011. pdf
  • Stefan Schoenmackers, Jesse Davis, Oren Etzioni and Daniel Weld. Learning First-Order Horn Clauses from Web Text. EMNLP2010. pdf
  • RohitJ. Kate RaymondJ. Mooney. Probabilistic Abduction using Markov Logic Networks. IJCAI 2009 on PAIR 2009. pdf
  • Stefan Schoenmackers, Oren Etzioni and Daniel Weld. Scaling Textual Inference to the Web. EMNLP2010. pdf
  • Hoifung Poon, Pedro Domingos. Joint Unsupervised Coreference Resolution with Markov Logic. EMNLP2008. pdf

• Inference
  • Cutting Plane Aggregation: Jan Noessner, Mathias Niepert, Heiner Stuckenschmidt. RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models. AAAI2013. pdf
  • Lifted inference: Vibhav Gogate and Pedro Domingos. Probabilistic Theorem Proving. UAI2011. pdf
  • Cutting Plane Inference: Sebastian Riedel, Cutting Plane MAP Inference for Markov Logic. SRL 2009. pdf
  • MC-SAT: Hoifung Poon, Pedro Domingos. Sound and Efficient Inference with Probabilistic and Deterministic Dependencies. AAAI 2006. pdf
  • LazySAT: Parag Singla, Pedro Domingos. Memory-Efficient Inference in Relational Domains. AAAI 2006. pdf
  • SampleSAT: Wei Wei, Jordan Erenrich, and Bart Selman. Towards Efficient Sampling: Exploiting Random Walk Strategies. AAAI 2004. pdf
  • WalkSAT: Bart Selman, Henry Kautz, and Bram Cohen. Local Search Strategies for Satisfiability Testing. 1996. pdf

• Structure/Weight Learning
  • Tuyen N. Huynh and Raymond J. Mooney. Max-Margin Weight Learning for Markov Logic Networks. SRL2009. pdf