Mamitsuka, Hiroshi

26 publications

UAI 2025 Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization Hai Dai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura

AISTATS 2025 Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference Dai Hai Nguyen, Tetsuya Sakurai, Hiroshi Mamitsuka

IJCAI 2024 Learning Low-Rank Tensor Cores with Probabilistic ℓ0-Regularized Rank Selection for Model Compression Tianxiao Cao, Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka

MLJ 2021 Learning Subtree Pattern Importance for Weisfeiler-Lehman Based Graph Kernels Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka

MLJ 2021 Reshaped Tensor Nuclear Norms for Higher Order Tensor Completion Kishan Wimalawarne, Hiroshi Mamitsuka

AAAI 2020 Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String Atsuyoshi Nakamura, Ichigaku Takigawa, Hiroshi Mamitsuka

AAAI 2020 Scalable Probabilistic Matrix Factorization with Graph-Based Priors Jonathan Strahl, Jaakko Peltonen, Hiroshi Mamitsuka, Samuel Kaski

NeurIPS 2019 AttentionXML: Label Tree-Based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification Ronghui You, Zihan Zhang, Ziye Wang, Suyang Dai, Hiroshi Mamitsuka, Shanfeng Zhu

IJCAI 2019 Fast and Robust Multi-View Multi-Task Learning via Group Sparsity Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka

IJCAI 2019 Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka

NeurIPS 2018 Efficient Convex Completion of Coupled Tensors Using Coupled Nuclear Norms Kishan Wimalawarne, Hiroshi Mamitsuka

AISTATS 2018 Factor Analysis on a Graph Masayuki Karasuyama, Hiroshi Mamitsuka

MLJ 2017 Adaptive Edge Weighting for Graph-Based Learning Algorithms Masayuki Karasuyama, Hiroshi Mamitsuka

IJCAI 2016 A Robust Convex Formulation for Ensemble Clustering Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu

AISTATS 2016 New Resistance Distances with Global Information on Large Graphs Canh Hao Nguyen, Hiroshi Mamitsuka

IJCAI 2015 Instance-Wise Weighted Nonnegative Matrix Factorization for Aggregating Partitions with Locally Reliable Clusters Xiaodong Zheng, Shanfeng Zhu, Junning Gao, Hiroshi Mamitsuka

NeurIPS 2013 Manifold-Based Similarity Adaptation for Label Propagation Masayuki Karasuyama, Hiroshi Mamitsuka

MLJ 2011 Efficiently Mining Δ-Tolerance Closed Frequent Subgraphs Ichigaku Takigawa, Hiroshi Mamitsuka

ECML-PKDD 2011 Kernels for Link Prediction with Latent Feature Models Canh Hao Nguyen, Hiroshi Mamitsuka

AISTATS 2010 Boosted Optimization for Network Classification Timothy Hancock, Hiroshi Mamitsuka

ICML 2003 Hierarchical Latent Knowledge Analysis for Co-Occurrence Data Hiroshi Mamitsuka

ICML 2000 Efficient Mining from Large Databases by Query Learning Hiroshi Mamitsuka, Naoki Abe

ICML 1998 Query Learning Strategies Using Boosting and Bagging Naoki Abe, Hiroshi Mamitsuka

MLJ 1997 Predicting Protein Secondary Structure Using Stochastic Tree Grammars Naoki Abe, Hiroshi Mamitsuka

ICML 1994 A New Method for Predicting Protein Secondary Structures Based on Stochastic Tree Grammars Naoki Abe, Hiroshi Mamitsuka

ALT 1992 Protein Secondary Structure Prediction Based on Stochastic-Rule Learning Hiroshi Mamitsuka, Kenji Yamanishi