| 2025 | AISTATS | Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference. | Dai Hai Nguyen, Tetsuya Sakurai, Hiroshi Mamitsuka |
| 2025 | UAI | Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization. | Dai Hai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura |
| 2024 | IJCAI | Learning Low-Rank Tensor Cores with Probabilistic ℓ0-Regularized Rank Selection for Model Compression. | Tianxiao Cao, Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka |
| 2023 | ECAI | Multiplicative Sparse Tensor Factorization for Multi-View Multi-Task Learning. | Xinyi Wang, Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka |
| 2020 | AAAI | Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String. | Atsuyoshi Nakamura, Ichigaku Takigawa, Hiroshi Mamitsuka |
| 2020 | AAAI | Scalable Probabilistic Matrix Factorization with Graph-Based Priors. | Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, Samuel Kaski |
| 2019 | IJCAI | Fast and Robust Multi-View Multi-Task Learning via Group Sparsity. | Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka |
| 2019 | IJCAI | Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning. | Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka |
| 2018 | AISTATS | Factor Analysis on a Graph. | Masayuki Karasuyama, Hiroshi Mamitsuka |
| 2017 | KDD | Convex Factorization Machine for Toxicogenomics Prediction. | Makoto Yamada, Wenzhao Lian, Amit Goyal, Jianhui Chen, Kishan Wimalawarne, Suleiman A. Khan, Samuel Kaski, Hiroshi Mamitsuka, Yi Chang |
| 2016 | AISTATS | New Resistance Distances with Global Information on Large Graphs. | Canh Hao Nguyen, Hiroshi Mamitsuka |
| 2016 | IJCAI | A Robust Convex Formulation for Ensemble Clustering. | Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu |
| 2015 | IJCAI | Instance-Wise Weighted Nonnegative Matrix Factorization for Aggregating Partitions with Locally Reliable Clusters. | Xiaodong Zheng, Shanfeng Zhu, Junning Gao, Hiroshi Mamitsuka |
| 2013 | KDD | Collaborative matrix factorization with multiple similarities for predicting drug-target interactions. | Xiaodong Zheng, Hao Ding, Hiroshi Mamitsuka, Shanfeng Zhu |
| 2010 | SPIRE | Algorithms for Finding a Minimum Repetition Representation of a String. | Atsuyoshi Nakamura, Tomoya Saito, Ichigaku Takigawa, Hiroshi Mamitsuka, Mineichi Kudo |
| 2009 | WABI | A Markov Classification Model for Metabolic Pathways. | Timothy Hancock, Hiroshi Mamitsuka |
| 2008 | ECCB | Mining significant tree patterns in carbohydrate sugar chains. | Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka |
| 2007 | ECIR | A Probabilistic Model for Clustering Text Documents with Multiple Fields. | Shanfeng Zhu, Ichigaku Takigawa, Shuqin Zhang, Hiroshi Mamitsuka |
| 2007 | ISMB | Annotating gene function by combining expression data with a modular gene network. | Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka |
| 2007 | KDD | A spectral clustering approach to optimally combining numericalvectors with a modular network. | Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka |
| 2006 | ISMB | ProfilePSTMM: capturing tree-structure motifs in carbohydrate sugar chains. | Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Hiroshi Mamitsuka, Minoru Kanehisa |
| 2006 | KDD | A new efficient probabilistic model for mining labeled ordered trees. | Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka |
| 2005 | ECCB | A probabilistic model for mining implicit 'chemical compound-gene' relations from literature. | Shanfeng Zhu, Yasushi Okuno, Gozoh Tsujimoto, Hiroshi Mamitsuka |
| 2005 | SAC | Cleaning microarray expression data using Markov random fields based on profile similarity. | Raymond Wan, Hiroshi Mamitsuka, Kiyoko F. Aoki |
| 2004 | ISMB | Application of a new probabilistic model for recognizing complex patterns in glycans. | Kiyoko F. Aoki, Nobuhisa Ueda, Atsuko Yamaguchi, Minoru Kanehisa, Tatsuya Akutsu, Hiroshi Mamitsuka |
| 2004 | SDM | A General Probabilistic Framework for Mining Labeled Ordered Trees. | Nobuhisa Ueda, Kiyoko F. Aoki, Hiroshi Mamitsuka |
| 2003 | BIBE | Empirical Evaluation of Ensemble Feature Subset Selection Methods for Learning from a High-Dimensional Database in Drug Desig. | Hiroshi Mamitsuka |
| 2003 | BIBE | Detecting Experimental Noises in Protein-Protein Interactions with Iterative Sampling and Model-Based Clustering. | Hiroshi Mamitsuka |
| 2003 | ICML | Hierarchical Latent Knowledge Analysis for Co-occurrence Data. | Hiroshi Mamitsuka |
| 2003 | ISAAC | Finding the Maximum Common Subgraph of a Partial k-Tree and a Graph with a Polynomially Bounded Number of Spanning Trees. | Atsuko Yamaguchi, Hiroshi Mamitsuka |
| 2003 | IDA | Selective Sampling with a Hierarchical Latent Variable Model. | Hiroshi Mamitsuka |
| 2003 | SDM | Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data. | Hiroshi Mamitsuka |
| 2000 | ICML | Efficient Mining from Large Databases by Query Learning. | Hiroshi Mamitsuka, Naoki Abe |
| 1998 | DIS | Empirical Comparison of Competing Query Learning Methods. | Naoki Abe, Hiroshi Mamitsuka, Atsuyoshi Nakamura |
| 1998 | ICML | Query Learning Strategies Using Boosting and Bagging. | Naoki Abe, Hiroshi Mamitsuka |
| 1997 | RECOMB | Supervised learning of hidden Markov models for sequence discrimination. | Hiroshi Mamitsuka |
| 1994 | ICML | A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars. | Naoki Abe, Hiroshi Mamitsuka |
| 1994 | ISMB | Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars. | Hiroshi Mamitsuka, Naoki Abe |
| 1992 | ALT | Protein Secondary Structure Prediction Based on Stochastic-Rule Learning. | Hiroshi Mamitsuka, Kenji Yamanishi |