N. Yugami

发表

Effective Decision Support for Product Configuration by Using CBR

S. Okamoto, Hiroya Inakoshi, Yuiko Ohta, 2001 .

Classification of glomerular pathological findings using deep learning and nephrologist-AI collective intelligence approach.

Kanata Suzuki, Y. Tamada, R. Kojima, 2020, International journal of medical informatics.

De ned Constraint Satisfaction Problems with Nearest Neighbour Method

Yuiko Ohta, N. Yugami, 2007 .

Assumption based combinatorial optimization method (abstract)

Nobuhiro Yugami, Hirotaka Hara, Hiroyuki Yoshida, 1992 .

Agent-Based Social Simulation for a Checkout Layout Design of a Specific Supermarket

N. Yugami, Kotaro Ohori, S. Yamane, 2012 .

An assumption-based combinatorial optimization system

H. Yoshida, Nobuhiro Yugami, H. Hara, 1992, Proceedings Eighth Conference on Artificial Intelligence for Applications.

Discovery of M-of-N Concepts for Classification

Nobuhiro Yugami, N. Yugami, 2000, Discovery Science.

Fast Discovery of Interesting Rules

Nobuhiro Yugami, Seishi Okamoto, Yuiko Ohta, 2000, PAKDD.

Classification of glomerular pathological findings using deep learning and nephrologist-AI collective intelligence approach

Kanata Suzuki, Noriaki Sato, Ryosuke Kojima, 2020, medRxiv.

Pyramid stack data stream mining for handling concept-drifting

Jun Sun, Zhuoran Xu, Yingju Xia, 2016, 2016 IEEE Region 10 Conference (TENCON).

Improving Repair-Based Constraint Satisfaction Methods by Value Propagation

Nobuhiro Yugami, Hirotaka Hara, Yuiko Ohta, 1994, AAAI.

Bosonic Constructions of W3 Algebra

N. Yugami, N. Sakai, Yoshihiro Saitoh, 1990 .

Mining Interesting Patterns Using Estimated Frequencies from Subpatterns and Superpatterns

Kenichi Kobayashi, Nobuhiro Yugami, Yukiko Yoshida, 2003, Discovery Science.

Evaluation of an interestingness measure of patterns based on frequencies estimated from their subpatterns and superpatterns

Yuiko Ohta, N. Yugami, Yukiko Yoshida, 2004 .

Effects of domain characteristics on instance-based learning algorithms

Nobuhiro Yugami, Seishi Okamoto, S. Okamoto, 2003, Theor. Comput. Sci..

An Average-Case Analysis of the k-Nearest Neighbar Classifier for Noisy Domains

Nobuhiro Yugami, Seishi Okamoto, S. Okamoto, 1997, IJCAI.

Theoretical Analysis of Case Retrieval Method Based on Neighborhood of a New Problem

Nobuhiro Yugami, Seishi Okamoto, S. Okamoto, 1997, ICCBR.

MultiAspectSpotting: Spotting Anomalous Behavior within Count Data Using Tensor

Nobuhiro Yugami, Koji Maruhashi, N. Yugami, 2014, PAKDD.