Iwata, Tomoharu

69 publications

AISTATS 2025 Energy-Consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations Yusuke Tanaka, Takaharu Yaguchi, Tomoharu Iwata, Naonori Ueda
ECML-PKDD 2025 Fast Proximal Gradient Methods with Node Pruning for Tree-Structured Sparse Regularization Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
AISTATS 2025 Importance-Weighted Positive-Unlabeled Learning for Distribution Shift Adaptation Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara
ICML 2025 K$^2$IE: Kernel Method-Based Kernel Intensity Estimators for Inhomogeneous Poisson Processes Hideaki Kim, Tomoharu Iwata, Akinori Fujino
ICML 2025 Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems Tomoharu Iwata, Shinsaku Sakaue
AISTATS 2025 Meta-Learning Task-Specific Regularization Weights for Few-Shot Linear Regression Tomoharu Iwata, Atsutoshi Kumagai, Yasutoshi Ida
TMLR 2025 Meta-Learning for Graphs with Heterogeneous Node Attribute Spaces for Few-Shot Edge Predictions Zhong Chuang, Yusuke Tanaka, Tomoharu Iwata
AISTATS 2025 Meta-Learning from Heterogeneous Tensors for Few-Shot Tensor Completion Tomoharu Iwata, Atsutoshi Kumagai
ICML 2025 Positive-Unlabeled AUC Maximization Under Covariate Shift Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Kazuki Adachi, Yasuhiro Fujiwara
ICLR 2025 Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka, Tomoya Yamashita
NeurIPS 2024 AUC Maximization Under Positive Distribution Shift Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Taishi Nishiyama, Yasuhiro Fujiwara
AISTATS 2024 Explanation-Based Training with Differentiable Insertion/Deletion Metric-Aware Regularizers Yuya Yoshikawa, Tomoharu Iwata
NeurIPS 2024 Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations Yasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
AISTATS 2024 Information-Theoretic Analysis of Bayesian Test Data Sensitivity Futoshi Futami, Tomoharu Iwata
TMLR 2024 Meta-Learning Under Task Shift Lei Sun, Yusuke Tanaka, Tomoharu Iwata
MLJ 2024 Meta-Learning for Heterogeneous Treatment Effect Estimation with Closed-Form Solvers Tomoharu Iwata, Yoichi Chikahara
IJCAI 2024 Symplectic Neural Gaussian Processes for Meta-Learning Hamiltonian Dynamics Tomoharu Iwata, Yusuke Tanaka
AISTATS 2024 Warped Diffusion for Latent Differentiation Inference Masahiro Nakano, Hiroki Sakuma, Ryo Nishikimi, Ryohei Shibue, Takashi Sato, Tomoharu Iwata, Kunio Kashino
AAAI 2024 Zero-Shot Task Adaptation with Relevant Feature Information Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
AISTATS 2023 Meta-Learning for Robust Anomaly Detection Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Yasuhiro Fujiwara
AISTATS 2022 Predictive Variational Bayesian Inference as Risk-Seeking Optimization Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
MLJ 2022 Context-Aware Spatio-Temporal Event Prediction via Convolutional Hawkes Processes Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Takeshi Kurashima, Hiroyuki Toda, Hisashi Kashima
NeurIPS 2022 Few-Shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion Atsutoshi Kumagai, Tomoharu Iwata, Yasutoshi Ida, Yasuhiro Fujiwara
MLJ 2022 Few-Shot Learning for Spatial Regression via Neural Embedding-Based Gaussian Processes Tomoharu Iwata, Yusuke Tanaka
NeurIPS 2022 Sharing Knowledge for Meta-Learning with Feature Descriptions Tomoharu Iwata, Atsutoshi Kumagai
NeurIPS 2022 Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data Yusuke Tanaka, Tomoharu Iwata, Naonori Ueda
NeurIPS 2021 Loss Function Based Second-Order Jensen Inequality and Its Application to Particle Variational Inference Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
NeurIPS 2021 Meta-Learning for Relative Density-Ratio Estimation Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
ACML 2021 Skew-Symmetrically Perturbed Gradient Flow for Convex Optimization Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane
MLJ 2020 Anomaly Detection with Inexact Labels Tomoharu Iwata, Machiko Toyoda, Shotaro Tora, Naonori Ueda
AAAI 2020 Co-Occurrence Estimation from Aggregated Data with Auxiliary Information Tomoharu Iwata, Naoki Marumo
ACML 2020 Disentangled Representations for Sequence Data Using Information Bottleneck Principle Masanori Yamada, Heecheol Kim, Kosuke Miyoshi, Tomoharu Iwata, Hiroshi Yamakawa
ICML 2020 Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima
NeurIPS 2020 Meta-Learning from Tasks with Heterogeneous Attribute Spaces Tomoharu Iwata, Atsutoshi Kumagai
AAAI 2020 Semi-Supervised Learning for Maximizing the Partial AUC Tomoharu Iwata, Akinori Fujino, Naonori Ueda
AAAI 2019 Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data Tomoharu Iwata, Hitoshi Shimizu
AAAI 2019 Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities Yusuke Tanaka, Tomoharu Iwata, Toshiyuki Tanaka, Takeshi Kurashima, Maya Okawa, Hiroyuki Toda
NeurIPS 2019 Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata, Takeshi Kurashima, Maya Okawa, Yasunori Akagi, Hiroyuki Toda
NeurIPS 2019 Transfer Anomaly Detection by Inferring Latent Domain Representations Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
AAAI 2019 Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations Atsutoshi Kumagai, Tomoharu Iwata
AAAI 2019 Variational Autoencoder with Implicit Optimal Priors Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada, Satoshi Yagi
IJCAI 2018 Estimating Latent People Flow Without Tracking Individuals Yusuke Tanaka, Tomoharu Iwata, Takeshi Kurashima, Hiroyuki Toda, Naonori Ueda
IJCAI 2018 Student-T Variational Autoencoder for Robust Density Estimation Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada, Satoshi Yagi
IJCAI 2017 Learning Latest Classifiers Without Additional Labeled Data Atsutoshi Kumagai, Tomoharu Iwata
AAAI 2017 Learning Non-Linear Dynamics of Decision Boundaries for Maintaining Classification Performance Atsutoshi Kumagai, Tomoharu Iwata
AISTATS 2017 Localized Lasso for High-Dimensional Regression Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski
AAAI 2017 Read the Silence: Well-Timed Recommendation via Admixture Marked Point Processes Hideaki Kim, Tomoharu Iwata, Yasuhiro Fujiwara, Naonori Ueda
ECML-PKDD 2017 Robust Multi-View Topic Modeling by Incorporating Detecting Anomalies Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima
IJCAI 2017 SVD-Based Screening for the Graphical Lasso Yasuhiro Fujiwara, Naoki Marumo, Mathieu Blondel, Koh Takeuchi, Hideaki Kim, Tomoharu Iwata, Naonori Ueda
ECML-PKDD 2017 Structurally Regularized Non-Negative Tensor Factorization for Spatio-Temporal Pattern Discoveries Koh Takeuchi, Yoshinobu Kawahara, Tomoharu Iwata
IJCAI 2016 Identifying Key Observers to Find Popular Information in Advance Takuya Konishi, Tomoharu Iwata, Kohei Hayashi, Ken-ichi Kawarabayashi
AAAI 2016 Learning Future Classifiers Without Additional Data Atsutoshi Kumagai, Tomoharu Iwata
NeurIPS 2016 Multi-View Anomaly Detection via Robust Probabilistic Latent Variable Models Tomoharu Iwata, Makoto Yamada
NeurIPS 2015 Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions Yuya Yoshikawa, Tomoharu Iwata, Hiroshi Sawada, Takeshi Yamada
AISTATS 2015 Cross-Domain Recommendation Without Shared Users or Items by Sharing Latent Vector Distributions Tomoharu Iwata, Koh Takeuchi
ECML-PKDD 2015 Higher Order Fused Regularization for Supervised Learning with Grouped Parameters Koh Takeuchi, Yoshinobu Kawahara, Tomoharu Iwata
AAAI 2015 Non-Linear Regression for Bag-of-Words Data via Gaussian Process Latent Variable Set Model Yuya Yoshikawa, Tomoharu Iwata, Hiroshi Sawada
UAI 2014 Generating Structure of Latent Variable Models for Nested Data Masakazu Ishihata, Tomoharu Iwata
NeurIPS 2014 Latent Support Measure Machines for Bag-of-Words Data Classification Yuya Yoshikawa, Tomoharu Iwata, Hiroshi Sawada
AISTATS 2013 Active Learning for Interactive Visualization Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani
AAAI 2013 Unsupervised Cluster Matching via Probabilistic Latent Variable Models Tomoharu Iwata, Tsutomu Hirao, Naonori Ueda
UAI 2013 Warped Mixtures for Nonparametric Cluster Shapes Tomoharu Iwata, David Duvenaud, Zoubin Ghahramani
ECML-PKDD 2012 Bidirectional Semi-Supervised Learning with Graphs Tomoharu Iwata, Kevin Duh
IJCAI 2011 Fashion Coordinates Recommender System Using Photographs from Fashion Magazines Tomoharu Iwata, Shinji Watanabe, Hiroshi Sawada
AAAI 2011 Transfer Learning for Multiple-Domain Sentiment Analysis - Identifying Domain Dependent/Independent Word Polarity Yasuhisa Yoshida, Tsutomu Hirao, Tomoharu Iwata, Masaaki Nagata, Yuji Matsumoto
NeurIPS 2010 Dynamic Infinite Relational Model for Time-Varying Relational Data Analysis Katsuhiko Ishiguro, Tomoharu Iwata, Naonori Ueda, Joshua B. Tenenbaum
NeurIPS 2009 Modeling Social Annotation Data with Content Relevance Using a Topic Model Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
IJCAI 2009 Topic Tracking Model for Analyzing Consumer Purchase Behavior Tomoharu Iwata, Shinji Watanabe, Takeshi Yamada, Naonori Ueda
NeurIPS 2004 Parametric Embedding for Class Visualization Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean Stromsten, Thomas L. Griffiths, Joshua B. Tenenbaum