Visualisation of Anomaly Using Mixture Model. - Tomoharu Iwata; Kazumi Saito (KES, 2004)

Visualization of Anomalies Using Mixture Models. - Tomoharu Iwata; Kazumi Saito (J. Intell. Manuf., 2005)

Visual nonlinear discriminant analysis for classifier design. - Tomoharu Iwata; Kazumi Saito; Naonori Ueda (ESANN, 2006)

Recommendation method for extending subscription periods. - Tomoharu Iwata; Kazumi Saito; Takeshi Yamada (KDD, 2006)

Organization of Discussion Knowledge Graph from Collaborative Learning Record. - Masahide Kakehi; Tomoko Kojiri; Toyohide Watanabe; Takeshi Yamada; Tomoharu Iwata (KES (3), 2007)

Modeling user behavior in recommender systems based on maximum entropy. - Tomoharu Iwata; Kazumi Saito; Takeshi Yamada (WWW, 2007)

Parametric Embedding for Class Visualization. - Tomoharu Iwata; Kazumi Saito; Naonori Ueda; Sean Stromsten; Thomas L. Griffiths 001; Joshua B. Tenenbaum (Neural Comput., 2007)

Probabilistic latent semantic visualization: topic model for visualizing documents. - Tomoharu Iwata; Takeshi Yamada; Naonori Ueda (KDD, 2008)

English Grammar Learning System Based on Knowledge Network of Fill-in-the-Blank Exercises. - Takuya Goto; Tomoko Kojiri; Toyohide Watanabe; Takeshi Yamada; Tomoharu Iwata (KES (3), 2008)

Recommendation Algorithm for Learning Materials That Maximizes Expected Test Scores. - Tomoharu Iwata; Tomoko Kojiri; Takeshi Yamada; Toyohide Watanabe (PRICAI, 2008)

Recommendation Method for Improving Customer Lifetime Value. - Tomoharu Iwata; Kazumi Saito; Takeshi Yamada (IEEE Trans. Knowl. Data Eng., 2008)

Topic Tracking Model for Analyzing Consumer Purchase Behavior. - Tomoharu Iwata; Shinji Watanabe 001; Takeshi Yamada; Naonori Ueda (IJCAI, 2009)

Modeling Social Annotation Data with Content Relevance using a Topic Model. - Tomoharu Iwata; Takeshi Yamada; Naonori Ueda (NIPS, 2009)

Learning Common Grammar from Multilingual Corpus. - Tomoharu Iwata; Daichi Mochihashi; Hiroshi Sawada (ACL (2), 2010)

Travel route recommendation using geotags in photo sharing sites. - Takeshi Kurashima; Tomoharu Iwata; Go Irie; Ko Fujimura (CIKM, 2010)

Capturing implicit user influence in online social sharing. - Ching-man Au Yeung; Tomoharu Iwata (HT, 2010)

Statistical Learning-based Approach for Automatic Generation System of Multiple-choice Cloze Questions. - Tomoko Kojiri; Takuya Goto; Toyohide Watanabe; Tomoharu Iwata; Takeshi Yamada (ICCE, 2010)

Effective Question Recommendation Based on Multiple Features for Question Answering Communities. - Yutaka Kabutoya; Tomoharu Iwata; Hisako Shiohara; Ko Fujimura (ICWSM, 2010)

Online multiscale dynamic topic models. - Tomoharu Iwata; Takeshi Yamada; Yasushi Sakurai; Naonori Ueda (KDD, 2010)

Dynamic Infinite Relational Model for Time-varying Relational Data Analysis. - Katsuhiko Ishiguro; Tomoharu Iwata; Naonori Ueda; Joshua B. Tenenbaum (NIPS, 2010)

Application of topic tracking model to language model adaptation and meeting analysis. - Shinji Watanabe 001; Tomoharu Iwata; Takaaki Hori; Atsushi Sako; Yasuo Ariki (SLT, 2010)

Modeling Multiple Users' Purchase over a Single Account for Collaborative Filtering. - Yutaka Kabutoya; Tomoharu Iwata; Ko Fujimura (WISE, 2010)

Knowledge network for English grammar learning support system. - Takuya Goto; Tomoko Kojiri; Toyohide Watanabe; Tomoharu Iwata; Takeshi Yamada (Int. J. Adv. Intell. Paradigms, 2010)

Transfer Learning for Multiple-Domain Sentiment Analysis - Identifying Domain Dependent/Independent Word Polarity. - Yasuhisa Yoshida; Tsutomu Hirao; Tomoharu Iwata; Masaaki Nagata; Yuji Matsumoto 001 (AAAI, 2011)

Extracting multi-dimensional relations: a generative model of groups of entities in a corpus. - Ching-man Au Yeung; Tomoharu Iwata (CIKM, 2011)

Modelling User Behaviour and Interactions: Augmented Cognition on the Social Web. - Ching-man Au Yeung; Tomoharu Iwata (HCI (20), 2011)

Fashion Coordinates Recommender System Using Photographs from Fashion Magazines. - Tomoharu Iwata; Shinji Watanabe 001; Hiroshi Sawada (IJCAI, 2011)

Learning Influences from Word Use in Polylogue. - Tomoharu Iwata; Shinji Watanabe 001 (INTERSPEECH, 2011)

Alignment Inference and Bayesian Adaptation for Machine Translation. - Kevin Duh; Katsuhito Sudoh; Tomoharu Iwata; Hajime Tsukada (MTSummit, 2011)

Strength of social influence in trust networks in product review sites. - Ching-man Au Yeung; Tomoharu Iwata (WSDM, 2011)

Topic tracking language model for speech recognition. - Shinji Watanabe 001; Tomoharu Iwata; Takaaki Hori; Atsushi Sako; Yasuo Ariki (Comput. Speech Lang., 2011)

Recommendation for English multiple-choice cloze questions based on expected test scores. - Tomoharu Iwata; Tomoko Kojiri; Takeshi Yamada; Toyohide Watanabe (Int. J. Knowl. Based Intell. Eng. Syst., 2011)

Improving Classifier Performance Using Data with Different Taxonomies. - Tomoharu Iwata; Toshiyuki Tanaka; Takeshi Yamada; Naonori Ueda (IEEE Trans. Knowl. Data Eng., 2011)

Handling uncertain observations in unsupervised topic-mixture language model adaptation. - Ekapol Chuangsuwanich; Shinji Watanabe 001; Takaaki Hori; Tomoharu Iwata; James R. Glass (ICASSP, 2012)

Effect of dialog acts on word use in polylogue. - Roland Roller; Shinji Watanabe 001; Tomoharu Iwata (ICASSP, 2012)

Creating Stories: Social Curation of Twitter Messages. - Kevin Duh; Tsutomu Hirao; Akisato Kimura; Katsuhiko Ishiguro; Tomoharu Iwata; Ching-man Au Yeung (ICWSM, 2012)

Fast mining and forecasting of complex time-stamped events. - Yasuko Matsubara; Yasushi Sakurai; Christos Faloutsos; Tomoharu Iwata; Masatoshi Yoshikawa (KDD, 2012)

Bidirectional Semi-supervised Learning with Graphs. - Tomoharu Iwata; Kevin Duh (ECML/PKDD (2), 2012)

A Topic Model for Recommending Movies via Linked Open Data. - Yutaka Kabutoya; Róbert Sumi; Tomoharu Iwata; Toshio Uchiyama; Tadasu Uchiyama (Web Intelligence, 2012)

Sequential Modeling of Topic Dynamics with Multiple Timescales. - Tomoharu Iwata; Takeshi Yamada; Yasushi Sakurai; Naonori Ueda (ACM Trans. Knowl. Discov. Data, 2012)

Unsupervised Cluster Matching via Probabilistic Latent Variable Models. - Tomoharu Iwata; Tsutomu Hirao; Naonori Ueda (AAAI, 2013)

Latent Semantic Matching: Application to Cross-language Text Categorization without Alignment Information. - Tsutomu Hirao; Tomoharu Iwata; Masaaki Nagata (ACL (2), 2013)

Active Learning for Interactive Visualization. - Tomoharu Iwata; Neil Houlsby; Zoubin Ghahramani (AISTATS, 2013)

A Probabilistic Model for Diversifying Recommendation Lists. - Yutaka Kabutoya; Tomoharu Iwata; Hiroyuki Toda; Hiroyuki Kitagawa (APWeb, 2013)

Clustering-based anomaly detection in multi-view data. - Alejandro Marcos Alvarez; Makoto Yamada; Akisato Kimura; Tomoharu Iwata (CIKM, 2013)

A Probabilistic Behavior Model for Discovering Unrecognized Knowledge. - Takeshi Kurashima; Tomoharu Iwata; Noriko Takaya; Hiroshi Sawada (ICDM, 2013)

Discovering latent influence in online social activities via shared cascade poisson processes. - Tomoharu Iwata; Amar Shah 001; Zoubin Ghahramani (KDD, 2013)

Warped Mixtures for Nonparametric Cluster Shapes. - Tomoharu Iwata; David Duvenaud; Zoubin Ghahramani (UAI, 2013)

Geo topic model: joint modeling of user's activity area and interests for location recommendation. - Takeshi Kurashima; Tomoharu Iwata; Takahide Hoshide; Noriko Takaya; Ko Fujimura (WSDM, 2013)

Topic model for analyzing purchase data with price information. - Tomoharu Iwata; Hiroshi Sawada (Data Min. Knowl. Discov., 2013)

Travel route recommendation using geotagged photos. - Takeshi Kurashima; Tomoharu Iwata; Go Irie; Ko Fujimura (Knowl. Inf. Syst., 2013)

Influence relation estimation based on lexical entrainment in conversation. - Tomoharu Iwata; Shinji Watanabe 001 (Speech Commun., 2013)

Modeling Noisy Annotated Data with Application to Social Annotation. - Tomoharu Iwata; Takeshi Yamada; Naonori Ueda (IEEE Trans. Knowl. Data Eng., 2013)

Managing information disparity in multilingual document collections. - Kevin Duh; Ching-man Au Yeung; Tomoharu Iwata; Masaaki Nagata (ACM Trans. Speech Lang. Process., 2013)

Probabilistic latent network visualization: inferring and embedding diffusion networks. - Takeshi Kurashima; Tomoharu Iwata; Noriko Takaya; Hiroshi Sawada (KDD, 2014)

Latent Support Measure Machines for Bag-of-Words Data Classification. - Yuya Yoshikawa; Tomoharu Iwata; Hiroshi Sawada (NIPS, 2014)

Generating structure of latent variable models for nested data. - Masakazu Ishihata; Tomoharu Iwata (UAI, 2014)

Multi-view Anomaly Detection via Probabilistic Latent Variable Models. - Tomoharu Iwata; Makoto Yamada (CoRR, 2014)

Collaboration on Social Media: Analyzing Successful Projects on Social Coding. - Yuya Yoshikawa; Tomoharu Iwata; Hiroshi Sawada (CoRR, 2014)

Creating Stories from Socially Curated Microblog Messages. - Akisato Kimura; Kevin Duh; Tsutomu Hirao; Katsuhiko Ishiguro; Tomoharu Iwata; Albert Au Yeung (IEICE Trans. Inf. Syst., 2014)

Non-Linear Regression for Bag-of-Words Data via Gaussian Process Latent Variable Set Model. - Yuya Yoshikawa; Tomoharu Iwata; Hiroshi Sawada (AAAI, 2015)

Cross-domain recommendation without shared users or items by sharing latent vector distributions. - Tomoharu Iwata; Koh Takeuchi 001 (AISTATS, 2015)

Real-time and proactive navigation via spatio-temporal prediction. - Naonori Ueda; Futoshi Naya; Hitoshi Shimizu; Tomoharu Iwata; Maya Okawa; Hiroshi Sawada (UbiComp/ISWC Adjunct, 2015)

Multiscale recurrent neural network based language model. - Tsuyoshi Morioka; Tomoharu Iwata; Takaaki Hori; Tetsunori Kobayashi (INTERSPEECH, 2015)

Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions. - Yuya Yoshikawa; Tomoharu Iwata; Hiroshi Sawada; Takeshi Yamada (NIPS, 2015)

Higher Order Fused Regularization for Supervised Learning with Grouped Parameters. - Koh Takeuchi 001; Yoshinobu Kawahara; Tomoharu Iwata (ECML/PKDD (1), 2015)

Learning Future Classifiers without Additional Data. - Atsutoshi Kumagai; Tomoharu Iwata (AAAI, 2016)

Identifying Key Observers to Find Popular Information in Advance. - Takuya Konishi; Tomoharu Iwata; Kohei Hayashi; Ken-ichi Kawarabayashi (IJCAI, 2016)

Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models. - Tomoharu Iwata; Makoto Yamada (NIPS, 2016)

Inferring Latent Triggers of Purchases with Consideration of Social Effects and Media Advertisements. - Yusuke Tanaka 002; Takeshi Kurashima; Yasuhiro Fujiwara; Tomoharu Iwata; Hiroshi Sawada (WSDM, 2016)

Sparse Network Lasso for Local High-dimensional Regression. - Makoto Yamada; Koh Takeuchi 001; Tomoharu Iwata; John Shawe-Taylor; Samuel Kaski (CoRR, 2016)

Probabilistic latent variable models for unsupervised many-to-many object matching. - Tomoharu Iwata; Tsutomu Hirao; Naonori Ueda (Inf. Process. Manag., 2016)

Unsupervised Many-to-Many Object Matching for Relational Data. - Tomoharu Iwata; James Robert Lloyd; Zoubin Ghahramani (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Read the Silence: Well-Timed Recommendation via Admixture Marked Point Processes. - Hideaki Kim; Tomoharu Iwata; Yasuhiro Fujiwara; Naonori Ueda (AAAI, 2017)

Learning Non-Linear Dynamics of Decision Boundaries for Maintaining Classification Performance. - Atsutoshi Kumagai; Tomoharu Iwata (AAAI, 2017)

Localized Lasso for High-Dimensional Regression. - Makoto Yamada; Koh Takeuchi 001; Tomoharu Iwata; John Shawe-Taylor; Samuel Kaski (AISTATS, 2017)

Exploiting end of sentences and speaker alternations in language modeling for multiparty conversations. - Hiroto Ashikawa; Naohiro Tawara; Atsunori Ogawa; Tomoharu Iwata; Tetsunori Kobayashi; Tetsuji Ogawa (APSIPA, 2017)

Latent Dimensionality Estimation for Probabilistic Canonical Correlation Analysis Using Normalized Maximum Likelihood Code-Length. - Tomohiko Nakmaura; Tomoharu Iwata; Kenji Yamanishi (DSAA, 2017)

SVD-Based Screening for the Graphical Lasso. - Yasuhiro Fujiwara; Naoki Marumo; Mathieu Blondel; Koh Takeuchi 001; Hideaki Kim; Tomoharu Iwata; Naonori Ueda (IJCAI, 2017)

Learning Latest Classifiers without Additional Labeled Data. - Atsutoshi Kumagai; Tomoharu Iwata (IJCAI, 2017)

Structurally Regularized Non-negative Tensor Factorization for Spatio-Temporal Pattern Discoveries. - Koh Takeuchi 001; Yoshinobu Kawahara; Tomoharu Iwata (ECML/PKDD (1), 2017)

Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies. - Guoxi Zhang; Tomoharu Iwata; Hisashi Kashima (ECML/PKDD (2), 2017)

Scaling Locally Linear Embedding. - Yasuhiro Fujiwara; Naoki Marumo; Mathieu Blondel; Koh Takeuchi 001; Hideaki Kim; Tomoharu Iwata; Naonori Ueda (SIGMOD Conference, 2017)

Robust unsupervised cluster matching for network data. - Tomoharu Iwata; Katsuhiko Ishiguro (Data Min. Knowl. Discov., 2017)

Unsupervised group matching with application to cross-lingual topic matching without alignment information. - Tomoharu Iwata; Motonobu Kanagawa; Tsutomu Hirao; Kenji Fukumizu (Data Min. Knowl. Discov., 2017)

Estimating People Flow from Spatiotemporal Population Data via Collective Graphical Mixture Models. - Tomoharu Iwata; Hitoshi Shimizu; Futoshi Naya; Naonori Ueda (ACM Trans. Spatial Algorithms Syst., 2017)

Factorised Hidden Layer Based Domain Adaptation for Recurrent Neural Network Language Models. - Michael Hentschel; Marc Delcroix; Atsunori Ogawa; Tomoharu Iwata; Tomohiro Nakatani (APSIPA, 2018)

Few-shot learning of neural networks from scratch by pseudo example optimization. - Akisato Kimura; Zoubin Ghahramani; Koh Takeuchi 001; Tomoharu Iwata; Naonori Ueda (BMVC, 2018)

Language Model Domain Adaptation Via Recurrent Neural Networks with Domain-Shared and Domain-Specific Representations. - Tsuyoshi Morioka; Naohiro Tawara; Tetsuji Ogawa; Atsunori Ogawa; Tomoharu Iwata; Tetsunori Kobayashi (ICASSP, 2018)

Student-t Variational Autoencoder for Robust Density Estimation. - Hiroshi Takahashi; Tomoharu Iwata; Yuki Yamanaka; Masanori Yamada; Satoshi Yagi (IJCAI, 2018)

Estimating Latent People Flow without Tracking Individuals. - Yusuke Tanaka 002; Tomoharu Iwata; Takeshi Kurashima; Hiroyuki Toda; Naonori Ueda (IJCAI, 2018)

Semi-Supervised End-to-End Speech Recognition. - Shigeki Karita; Shinji Watanabe 001; Tomoharu Iwata; Atsunori Ogawa; Marc Delcroix (INTERSPEECH, 2018)

Learning Dynamics of Decision Boundaries without Additional Labeled Data. - Atsutoshi Kumagai; Tomoharu Iwata (KDD, 2018)

On Reducing Dimensionality of Labeled Data Efficiently. - Guoxi Zhang; Tomoharu Iwata; Hisashi Kashima (PAKDD (3), 2018)

Improving Route Traffic Estimation by Considering Staying Population. - Hitoshi Shimizu; Tatsushi Matsubayashi; Yusuke Tanaka 002; Tomoharu Iwata; Naonori Ueda; Hiroshi Sawada (PRIMA, 2018)

Imitation networks: Few-shot learning of neural networks from scratch. - Akisato Kimura; Zoubin Ghahramani; Koh Takeuchi 001; Tomoharu Iwata; Naonori Ueda (CoRR, 2018)

Zero-shot Domain Adaptation without Domain Semantic Descriptors. - Atsutoshi Kumagai; Tomoharu Iwata (CoRR, 2018)

Unsupervised Cross-lingual Word Embedding by Multilingual Neural Language Models. - Takashi Wada 001; Tomoharu Iwata (CoRR, 2018)

Unsupervised Object Matching for Relational Data. - Tomoharu Iwata; Naonori Ueda (CoRR, 2018)

Finding Appropriate Traffic Regulations via Graph Convolutional Networks. - Tomoharu Iwata; Takuma Otsuka; Hitoshi Shimizu; Hiroshi Sawada; Futoshi Naya; Naonori Ueda (CoRR, 2018)

Topic Models for Unsupervised Cluster Matching. - Tomoharu Iwata; Tsutomu Hirao; Naonori Ueda (IEEE Trans. Knowl. Data Eng., 2018)

Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities. - Yusuke Tanaka 002; Tomoharu Iwata; Toshiyuki Tanaka; Takeshi Kurashima; Maya Okawa; Hiroyuki Toda (AAAI, 2019)

Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data. - Tomoharu Iwata; Hitoshi Shimizu (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 (AAAI, 2019)

Unsupervised Multilingual Word Embedding with Limited Resources using Neural Language Models. - Takashi Wada 001; Tomoharu Iwata; Yuji Matsumoto 001 (ACL (1), 2019)

A Unified Framework for Feature-based Domain Adaptation of Neural Network Language Models. - Michael Hentschel; Marc Delcroix; Atsunori Ogawa; Tomoharu Iwata; Tomohiro Nakatani (ICASSP, 2019)

Semi-supervised End-to-end Speech Recognition Using Text-to-speech and Autoencoders. - Shigeki Karita; Shinji Watanabe 001; Tomoharu Iwata; Marc Delcroix; Atsunori Ogawa; Tomohiro Nakatani (ICASSP, 2019)

Bayesian Optimization for Crowd Traffic Control Using Multi-Agent Simulation. - Takuma Otsuka; Hitoshi Shimizu; Tomoharu Iwata; Futoshi Naya; Hiroshi Sawada; Naonori Ueda (ITSC, 2019)

Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information. - Maya Okawa; Tomoharu Iwata; Takeshi Kurashima; Yusuke Tanaka 002; Hiroyuki Toda; Naonori Ueda (KDD, 2019)

Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs. - Yusuke Tanaka 002; 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 (NeurIPS, 2019)

Autoencoding Binary Classifiers for Supervised Anomaly Detection. - Yuki Yamanaka; Tomoharu Iwata; Hiroshi Takahashi; Masanori Yamada; Sekitoshi Kanai (PRICAI (2), 2019)

Supervised Anomaly Detection based on Deep Autoregressive Density Estimators. - Tomoharu Iwata; Yuki Yamanaka (CoRR, 2019)

Efficient Transfer Bayesian Optimization with Auxiliary Information. - Tomoharu Iwata; Takuma Otsuka (CoRR, 2019)

Feature Based Domain Adaptation for Neural Network Language Models with Factorised Hidden Layers. - Michael Hentschel; Marc Delcroix; Atsunori Ogawa; Tomoharu Iwata; Tomohiro Nakatani (IEICE Trans. Inf. Syst., 2019)

Semi-Supervised Learning for Maximizing the Partial AUC. - Tomoharu Iwata; Akinori Fujino; Naonori Ueda (AAAI, 2020)

Co-Occurrence Estimation from Aggregated Data with Auxiliary Information. - Tomoharu Iwata; Naoki Marumo (AAAI, 2020)

Disentangled Representations for Sequence Data using Information Bottleneck Principle. - Masanori Yamada; Heecheol Kim 002; Kosuke Miyoshi; Tomoharu Iwata; Hiroshi Yamakawa (ACML, 2020)

Noise-robust Attention Learning for End-to-End Speech Recognition. - Yosuke Higuchi; Naohiro Tawara; Atsunori Ogawa; Tomoharu Iwata; Tetsunori Kobayashi; Tetsuji Ogawa (EUSIPCO, 2020)

Frame-Level Phoneme-Invariant Speaker Embedding for Text-Independent Speaker Recognition on Extremely Short Utterances. - Naohiro Tawara; Atsunori Ogawa; Tomoharu Iwata; Marc Delcroix; Tetsuji Ogawa (ICASSP, 2020)

Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance. - Yasutoshi Ida; Sekitoshi Kanai; Yasuhiro Fujiwara; Tomoharu Iwata; Koh Takeuchi 001; Hisashi Kashima (ICML, 2020)

Reinforcement Learning in Latent Action Sequence Space. - Heecheol Kim 002; Masanori Yamada; Kosuke Miyoshi; Tomoharu Iwata; Hiroshi Yamakawa (IROS, 2020)

Meta-learning from Tasks with Heterogeneous Attribute Spaces. - Tomoharu Iwata; Atsutoshi Kumagai (NeurIPS, 2020)

Deep Reinforcement Learning for Pedestrian Guidance. - Hitoshi Shimizu; Takanori Hara; Tomoharu Iwata (PRIMA, 2020)

Probabilistic Optimal Transport based on Collective Graphical Models. - Yasunori Akagi; Yusuke Tanaka 002; Tomoharu Iwata; Takeshi Kurashima; Hiroyuki Toda (CoRR, 2020)

Gaussian Process Regression with Local Explanation. - Yuya Yoshikawa; Tomoharu Iwata (CoRR, 2020)

Few-shot Learning for Time-series Forecasting. - Tomoharu Iwata; Atsutoshi Kumagai (CoRR, 2020)

Few-shot Learning for Spatial Regression. - Tomoharu Iwata; Yusuke Tanaka 002 (CoRR, 2020)

Meta-Active Learning for Node Response Prediction in Graphs. - Tomoharu Iwata (CoRR, 2020)

Learning Contextualised Cross-lingual Word Embeddings for Extremely Low-Resource Languages Using Parallel Corpora. - Takashi Wada 001; Tomoharu Iwata; Yuji Matsumoto 001; Timothy Baldwin; Jey Han Lau (CoRR, 2020)

Neural Dynamic Mode Decomposition for End-to-End Modeling of Nonlinear Dynamics. - Tomoharu Iwata; Yoshinobu Kawahara (CoRR, 2020)

Transfer Metric Learning for Unseen Domains. - Atsutoshi Kumagai; Tomoharu Iwata; Yasuhiro Fujiwara (Data Sci. Eng., 2020)

Anomaly detection with inexact labels. - Tomoharu Iwata; Machiko Toyoda; Shotaro Tora; Naonori Ueda (Mach. Learn., 2020)

Skew-symmetrically perturbed gradient flow for convex optimization. - Futoshi Futami; Tomoharu Iwata; Naonori Ueda; Ikko Yamane (ACML, 2021)

Controlling Nonlinear Dynamical Systems with Linear Quadratic Regulator-based Policy Networks in Koopman space. - Tomoharu Iwata; Yoshinobu Kawahara (CDC, 2021)

Context-aware Neural Machine Translation with Mini-batch Embedding. - Makoto Morishita; Jun Suzuki 001; Tomoharu Iwata; Masaaki Nagata (EACL, 2021)

Unsupervised Heart Sound Decomposition and State Estimation with Generative Oscillation Models. - Ryohei Shibue; Masahiro Nakano; Tomoharu Iwata; Kunio Kashino; Hitonobu Tomoike (EMBC, 2021)

Semi-supervised Anomaly Detection on Attributed Graphs. - Atsutoshi Kumagai; Tomoharu Iwata; Yasuhiro Fujiwara (IJCNN, 2021)

Fault Detection of ICT systems with Deep Learning Model for Missing Data. - Kengo Tajiri; Tomoharu Iwata; Yoichi Matsuo; Keishiro Watanabe (IM, 2021)

Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. - Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 002; Hiroyuki Toda; Takeshi Kurashima; Hisashi Kashima (KDD, 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 (NeurIPS, 2021)

Time-delayed collective flow diffusion models for inferring latent people flow from aggregated data at limited locations. - Yusuke Tanaka 002; Tomoharu Iwata; Takeshi Kurashima; Hiroyuki Toda; Naonori Ueda; Toshiyuki Tanaka (Artif. Intell., 2021)

Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression. - Masanori Yamada; Sekitoshi Kanai; Tomoharu Iwata; Tomokatsu Takahashi; Yuki Yamanaka; Hiroshi Takahashi; Atsutoshi Kumagai (CoRR, 2021)

Meta-Learning for Koopman Spectral Analysis with Short Time-series. - Tomoharu Iwata; Yoshinobu Kawahara (CoRR, 2021)

Meta-learning One-class Classifiers with Eigenvalue Solvers for Supervised Anomaly Detection. - Tomoharu Iwata; Atsutoshi Kumagai (CoRR, 2021)

Few-shot Learning for Topic Modeling. - Tomoharu Iwata (CoRR, 2021)

Meta-learning for Matrix Factorization without Shared Rows or Columns. - Tomoharu Iwata (CoRR, 2021)

Few-shot Learning for Unsupervised Feature Selection. - Atsutoshi Kumagai; Tomoharu Iwata; Yasuhiro Fujiwara (CoRR, 2021)

End-to-End Learning of Deep Kernel Acquisition Functions for Bayesian Optimization. - Tomoharu Iwata (CoRR, 2021)

Training Deep Models to be Explained with Fewer Examples. - Tomoharu Iwata; Yuya Yoshikawa (CoRR, 2021)

Accelerated Diffusion-Based Sampling by the Non-Reversible Dynamics with Skew-Symmetric Matrices. - Futoshi Futami; Tomoharu Iwata; Naonori Ueda; Issei Sato (Entropy, 2021)

Predictive variational Bayesian inference as risk-seeking optimization. - Futoshi Futami; Tomoharu Iwata; Naonori Ueda; Issei Sato; Masashi Sugiyama (AISTATS, 2022)

Evacuation Shelter Scheduling Problem. - Hitoshi Shimizu; Hirohiko Suwa; Tomoharu Iwata; Akinori Fujino; Hiroshi Sawada; Keiichi Yasumoto (HICSS, 2022)

Tight Integration Of Neural- And Clustering-Based Diarization Through Deep Unfolding Of Infinite Gaussian Mixture Model. - Keisuke Kinoshita; Marc Delcroix; Tomoharu Iwata (ICASSP, 2022)

Transfer Anomaly Detection for Maximizing the Partial AUC. - Atsutoshi Kumagai; Tomoharu Iwata; Taishi Nishiyama; Yasuhiro Fujiwara (IJCNN, 2022)

Predicting Opinion Dynamics via Sociologically-Informed Neural Networks. - Maya Okawa; Tomoharu Iwata (KDD, 2022)

Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders. - Hiroshi Takahashi; Tomoharu Iwata; Atsutoshi Kumagai; Sekitoshi Kanai; Masanori Yamada; Yuki Yamanaka; Hisashi Kashima (KDD, 2022)

Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data. - Yusuke Tanaka 002; Tomoharu Iwata; Naonori Ueda (NeurIPS, 2022)

Sharing Knowledge for Meta-learning with Feature Descriptions. - Tomoharu Iwata; Atsutoshi Kumagai (NeurIPS, 2022)

Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion. - Atsutoshi Kumagai; Tomoharu Iwata; Yasutoshi Ida; Yasuhiro Fujiwara (NeurIPS, 2022)

Excess risk analysis for epistemic uncertainty with application to variational inference. - Futoshi Futami; Tomoharu Iwata; Naonori Ueda; Issei Sato; Masashi Sugiyama (CoRR, 2022)

Meta-learning for Out-of-Distribution Detection via Density Estimation in Latent Space. - Tomoharu Iwata; Atsutoshi Kumagai (CoRR, 2022)

Aggregated Multi-output Gaussian Processes with Knowledge Transfer Across Domains. - Yusuke Tanaka 002; Toshiyuki Tanaka; Tomoharu Iwata; Takeshi Kurashima; Maya Okawa; Yasunori Akagi; Hiroyuki Toda (CoRR, 2022)

Data-driven End-to-end Learning of Pole Placement Control for Nonlinear Dynamics via Koopman Invariant Subspaces. - Tomoharu Iwata; Yoshinobu Kawahara (CoRR, 2022)

Active Learning for Regression with Aggregated Outputs. - Tomoharu Iwata (CoRR, 2022)

Linear Embedding-based High-dimensional Batch Bayesian Optimization without Reconstruction Mappings. - Shuhei A. Horiguchi; Tomoharu Iwata; Taku Tsuzuki; Yosuke Ozawa (CoRR, 2022)

Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies. - Tomoharu Iwata; Yoshinobu Kawahara (CoRR, 2022)

Dynamic mode decomposition via convolutional autoencoders for dynamics modeling in videos. - Israr Ul Haq; Tomoharu Iwata; Yoshinobu Kawahara (Comput. Vis. Image Underst., 2022)

Multi-Source Domain Generalization Using Domain Attributes for Recurrent Neural Network Language Models. - Naohiro Tawara; Atsunori Ogawa; Tomoharu Iwata; Hiroto Ashikawa; Tetsunori Kobayashi; Tetsuji Ogawa (IEICE Trans. Inf. Syst., 2022)

Neural generators of sparse local linear models for achieving both accuracy and interpretability. - Yuya Yoshikawa; Tomoharu Iwata (Inf. Fusion, 2022)

Few-shot learning for spatial regression via neural embedding-based Gaussian processes. - Tomoharu Iwata; Yusuke Tanaka 002 (Mach. Learn., 2022)

Context-aware spatio-temporal event prediction via convolutional Hawkes processes. - Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 002; Takeshi Kurashima; Hiroyuki Toda; Hisashi Kashima (Mach. Learn., 2022)

Probabilistic Pedestrian Models for Estimating Unobserved Road Populations. - Tomoharu Iwata; Hitoshi Shimizu; Naoki Marumo (IEEE Trans. Intell. Transp. Syst., 2022)

Meta-learning for Robust Anomaly Detection. - Atsutoshi Kumagai; Tomoharu Iwata; Hiroshi Takahashi; Yasuhiro Fujiwara (AISTATS, 2023)

School Families: A New Formulation of School District Planning Problem. - Hitoshi Shimizu; Hirohiko Suwa; Tomoharu Iwata; Akinori Fujino; Hiroshi Sawada; Keiichi Yasumoto (HICSS, 2023)

Personal History Affects Reference Points: A Case Study of Codeforces. - Takeshi Kurashima; Tomoharu Iwata; Tomu Tominaga; Shuhei Yamamoto; Hiroyuki Toda; Kazuhisa Takemura (ICWSM, 2023)

Information-theoretic Analysis of Test Data Sensitivity in Uncertainty. - Futoshi Futami; Tomoharu Iwata (CoRR, 2023)

Meta-learning of Physics-informed Neural Networks for Efficiently Solving Newly Given PDEs. - Tomoharu Iwata; Yusuke Tanaka 002; Naonori Ueda (CoRR, 2023)

Meta-learning of semi-supervised learning from tasks with heterogeneous attribute spaces. - Tomoharu Iwata; Atsutoshi Kumagai (CoRR, 2023)

Meta-learning representations for clustering with infinite Gaussian mixture models. - Tomoharu Iwata (Neurocomputing, 2023)

Gaussian Process Regression With Interpretable Sample-Wise Feature Weights. - Yuya Yoshikawa; Tomoharu Iwata (IEEE Trans. Neural Networks Learn. Syst., 2023)

Zero-Shot Task Adaptation with Relevant Feature Information. - Atsutoshi Kumagai; Tomoharu Iwata; Yasuhiro Fujiwara (AAAI, 2024)

Information-theoretic Analysis of Bayesian Test Data Sensitivity. - Futoshi Futami; Tomoharu Iwata (AISTATS, 2024)

Warped Diffusion for Latent Differentiation Inference. - Masahiro Nakano; Hiroki Sakuma; Ryo Nishikimi; Ryohei Shibue; Takashi Sato; Tomoharu Iwata; Kunio Kashino (AISTATS, 2024)

Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers. - Yuya Yoshikawa; Tomoharu Iwata (AISTATS, 2024)

Electrocardiographic Classification using Deep Learning with Lead Switching. - Tomoharu Iwata; Ryo Nishikimi; Ryohei Shibue; Masahiro Nakano; Kunio Kashino; Hitonobu Tomoike (EMBC, 2024)

Symplectic Neural Gaussian Processes for Meta-learning Hamiltonian Dynamics. - Tomoharu Iwata; Yusuke Tanaka 002 (IJCAI, 2024)

Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations. - Yasutoshi Ida; Sekitoshi Kanai; Atsutoshi Kumagai; Tomoharu Iwata; Yasuhiro Fujiwara (NeurIPS, 2024)

AUC Maximization under Positive Distribution Shift. - Atsutoshi Kumagai; Tomoharu Iwata; Hiroshi Takahashi; Taishi Nishiyama; Yasuhiro Fujiwara (NeurIPS, 2024)

Meta-Learning for Neural Network-based Temporal Point Processes. - Yoshiaki Takimoto; Yusuke Tanaka 002; Tomoharu Iwata; Maya Okawa; Hideaki Kim; Hiroyuki Toda; Takeshi Kurashima (CoRR, 2024)

Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs. - Yusuke Tanaka 002; Takaharu Yaguchi; Tomoharu Iwata; Naonori Ueda (CoRR, 2024)

Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data. - Hiroshi Takahashi; Tomoharu Iwata; Atsutoshi Kumagai; Yuki Yamanaka (CoRR, 2024)

Meta-learning for Positive-unlabeled Classification. - Atsutoshi Kumagai; Tomoharu Iwata; Yasuhiro Fujiwara (CoRR, 2024)

Deep Koopman-layered Model with Universal Property Based on Toeplitz Matrices. - Yuka Hashimoto; Tomoharu Iwata (CoRR, 2024)

Meta-learning to calibrate Gaussian processes with deep kernels for regression uncertainty estimation. - Tomoharu Iwata; Atsutoshi Kumagai (Neurocomputing, 2024)

Marked point process variational autoencoder with applications to unsorted spiking activities. - Ryohei Shibue; Tomoharu Iwata (PLoS Comput. Biol., 2024)

Meta-Learning under Task Shift. - Lei Sun; Yusuke Tanaka 002; Tomoharu Iwata (Trans. Mach. Learn. Res., 2024)

Meta-learning for heterogeneous treatment effect estimation with closed-form solvers. - Tomoharu Iwata; Yoichi Chikahara (Mach. Learn., 2024)

Meta-learning from Heterogeneous Tensors for Few-shot Tensor Completion. - Tomoharu Iwata; Atsutoshi Kumagai (AISTATS, 2025)

Meta-learning Task-specific Regularization Weights for Few-shot Linear Regression. - Tomoharu Iwata; Atsutoshi Kumagai; Yasutoshi Ida (AISTATS, 2025)

Importance-weighted Positive-unlabeled Learning for Distribution Shift Adaptation. - Atsutoshi Kumagai; Tomoharu Iwata; Hiroshi Takahashi; Taishi Nishiyama; Yasuhiro Fujiwara (AISTATS, 2025)

Energy-consistent Neural Operators for Hamiltonian and Dissipative Partial Differential Equations. - Yusuke Tanaka 002; Takaharu Yaguchi; Tomoharu Iwata; Naonori Ueda (AISTATS, 2025)

Hyperbolic PHATE: Visualizing Continuous Hierarchy of Latent Differentiation Structures. - Masahiro Nakano; Hiroki Sakuma; Ryo Nishikimi; Kenji Komiya; Tomoharu Iwata; Kunio Kashino (ICASSP, 2025)

Positive-Unlabeled Diffusion Models for Preventing Sensitive Data Generation. - Hiroshi Takahashi; Tomoharu Iwata; Atsutoshi Kumagai; Yuuki Yamanaka; Tomoya Yamashita (ICLR, 2025)

Meta-learning of Class Knowledge in Zero-shot Learning. - Yuta Nambu; Masahiro Kohjima; Tomoharu Iwata; Ryuji Yamamoto (SDM, 2025)

Meta-Learning for Graphs with Heterogeneous Node Attribute Spaces for Few-Shot Edge Predictions. - Zhong Chuang; Yusuke Tanaka 002; Tomoharu Iwata (Trans. Mach. Learn. Res., 2025)

K2IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes. - Hideaki Kim; Tomoharu Iwata; Akinori Fujino (CoRR, 2025)

Meta-learning Representations for Learning from Multiple Annotators. - Atsutoshi Kumagai; Tomoharu Iwata; Taishi Nishiyama; Yasutoshi Ida; Yasuhiro Fujiwara (CoRR, 2025)