I am an incoming computer science PhD student at University of Colorado, Boulder.
I was previously a search engineer at Amazon Japan and its subsidiary A9.com. My Japanese name is “藤沼祥成”.
My main interest is on Natural Language Processing and Machine Learning. On the method side, I am intersted in unsupervised/semi-supervised/distant-supervised learning, or making use of unlabeled data because it requires less manual labor. On the application side, I am interested in cross-lingual processing on Japanese or other Asian languages. Japanese (or Chinese, Korean, etc.) is an unsegmented language and this fact makes it difficult to tokenize (word segmentation and POS-tagging) when compared to English.
You can find me on LinkedIn, Twitter, and Github.
My CV is here.
- Yoshinari Fujinuma, Alvin Grissom II: “Substring Frequency Features for Segmentation of Japanese Katakana Words with Unlabeled Corpora”, The 8th International Joint Conference on Natural Language Processing, Nov. 2017 (acceptance rate: 31%) pdf poster
- Yoshinari Fujinuma, Hikaru Yokono, Pascual Martinez-Gomez, Akiko Aizawa: “Distant-supervised Language Model for Detecting Emotional Upsurge on Twitter”, The 29th Pacific Asia Conference on Language, Information and Computation, Nov. 2015 pdf
- Yoshinari Fujinuma: “Detecting Japanese-English transliteration pairs from search query and clickthrough logs” Amazon Machine Learning Conference 2015 (Internal)
- Yoshinari Fujinuma, Jordan Boyd-Graber, Michael J. Paul “Diagnosing Language Inconsistency in Cross-Lingual Word Embeddings” 2018 pdf
- Mozhi Zhang, Yoshinari Fujinuma, Jordan L. Boyd-Graber: “Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification” arXiv 2018 pdf
- Kuromoji FST: A finite-state transducer for efficient key-value (text -> integers) lookup.
My Personal Notes
fujinumay at gmail dot com