Riku Togashi

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 41

Top Topics

Density Estimation

Recommender Systems

Matrix Factorization

Top Venues

Publications

Mayu Otani, Naoto Inoue, Kotaro Kikuchi, Riku Togashi
LTSim: Layout Transportation-based Similarity Measure for Evaluating Layout Generation. CoRR (2024)
Riku Togashi, Kenshi Abe, Yuta Saito
Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems. CoRR (2024)
Riku Togashi, Kenshi Abe, Yuta Saito
Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems. WWW (2024)
Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura
Safe Collaborative Filtering. ICLR (2024)
Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura
Safe Collaborative Filtering. CoRR (2023)
Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi
Exploration of Unranked Items in Safe Online Learning to Re-Rank. SIGIR (2023)
Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi
Exploration of Unranked Items in Safe Online Learning to Re-Rank. CoRR (2023)
Yoji Tomita, Riku Togashi, Yuriko Hashizume, Naoto Ohsaka
Fast and Examination-agnostic Reciprocal Recommendation in Matching Markets. CoRR (2023)
Naoto Ohsaka, Riku Togashi
A Critical Reexamination of Intra-List Distance and Dispersion. CoRR (2023)
Mayu Otani, Riku Togashi, Yu Sawai, Ryosuke Ishigami, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Shin'ichi Satoh
Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation. CoRR (2023)
Yoji Tomita, Riku Togashi, Yuriko Hashizume, Naoto Ohsaka
Fast and Examination-agnostic Reciprocal Recommendation in Matching Markets. RecSys (2023)
Naoto Ohsaka, Riku Togashi
Curse of "Low" Dimensionality in Recommender Systems. CoRR (2023)
Naoto Ohsaka, Riku Togashi
A Critical Reexamination of Intra-List Distance and Dispersion. SIGIR (2023)
Naoto Ohsaka, Riku Togashi
Curse of "Low" Dimensionality in Recommender Systems. SIGIR (2023)
Mayu Otani, Riku Togashi, Yu Sawai, Ryosuke Ishigami, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Shin'ichi Satoh
Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation. CVPR (2023)
Riku Togashi, Mayu Otani, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Tetsuya Sakai
AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval. CoRR (2022)
Mayu Otani, Riku Togashi, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Shin'ichi Satoh
Optimal Correction Cost for Object Detection Evaluation. CVPR (2022)
Shunsuke Kitada, Yuki Iwazaki, Riku Togashi, Hitoshi Iyatomi
: Deep Multimodal Sequence Sets With Hierarchical Modality Attention. IEEE Access 10 (2022)
Shunsuke Kitada, Yuki Iwazaki, Riku Togashi, Hitoshi Iyatomi
: Deep Multi-Modal Sequence Sets with Hierarchical Modality Attention. CoRR (2022)
Yoji Tomita, Riku Togashi, Daisuke Moriwaki
Matching Theory-based Recommender Systems in Online Dating. RecSys (2022)
Yoji Tomita, Riku Togashi, Daisuke Moriwaki
Matching Theory-based Recommender Systems in Online Dating. CoRR (2022)
Mayu Otani, Riku Togashi, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Shin'ichi Satoh
Optimal Correction Cost for Object Detection Evaluation. CoRR (2022)
Riku Togashi, Kenshi Abe
Fair Matrix Factorisation for Large-Scale Recommender Systems. CoRR (2022)
Riku Togashi, Mayu Otani, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Tetsuya Sakai
AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval. CVPR (2022)
Riku Togashi, Masahiro Kato, Mayu Otani, Tetsuya Sakai, Shin'ichi Satoh
Scalable Personalised Item Ranking through Parametric Density Estimation. CoRR (2021)
Riku Togashi, Masahiro Kato, Mayu Otani, Tetsuya Sakai, Shin'ichi Satoh
Scalable Personalised Item Ranking through Parametric Density Estimation. SIGIR (2021)
Riku Togashi, Masahiro Kato, Mayu Otani, Shin'ichi Satoh
Density-Ratio Based Personalised Ranking from Implicit Feedback. WWW (2021)
Riku Togashi, Masahiro Kato, Mayu Otani, Shin'ichi Satoh
Density-Ratio Based Personalised Ranking from Implicit Feedback. CoRR (2021)
Riku Togashi, Mayu Otani, Shin'ichi Satoh
Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph. WSDM (2021)
Riku Togashi, Mayu Otani, Shin'ichi Satoh
Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph. CoRR (2020)
Riku Togashi, Sumio Fujita, Tetsuya Sakai
Automatic Evaluation of Iconic Image Retrieval based on Colour, Shape, and Texture. ICMR (2020)
Riku Togashi, Tetsuya Sakai
Visual Intents vs. Clicks, Likes, and Purchases in E-commerce. SIGIR (2020)
Takuma Yamaguchi, Kosuke Arase, Riku Togashi, Shunya Ueta
Closing the Gap Between Query and Database through Query Feature Transformation in C2C e-Commerce Visual Search. eCOM@SIGIR (2019)
Riku Togashi, Tetsuya Sakai
Generalising Kendall's Tau for Noisy and Incomplete Preference Judgements. ICTIR (2019)
Akihiro Shimizu, Riku Togashi, Antony Lam, Nam Van Huynh
Uplift Modeling for Cost Effective Coupon Marketing in C-to-C E-Commerce. ICTAI (2019)
Kenta Tamaki, Riku Togashi, Sosuke Kato, Sumio Fujita, Hideyuki Maeda, Tetsuya Sakai
Classifying Community QA Questions That Contain an Image. ICTIR (2018)
Vibhor Kanojia, Hideyuki Maeda, Riku Togashi, Sumio Fujita
Enhancing Knowledge Graph Embedding with Probabilistic Negative Sampling. WWW (Companion Volume) (2017)
Kaustubh Kulkarni, Riku Togashi, Hideyuki Maeda, Sumio Fujita
Dual Constrained Question Embeddings with Relational Knowledge Bases for Simple Question Answering. IJCNLP(2) (2017)
Vibhor Kanojia, Riku Togashi, Hideyuki Maeda
Relevance Score of Triplets Using Knowledge Graph Embedding - The Pigweed Triple Scorer at WSDM Cup 2017. CoRR (2017)
Sosuke Kato, Riku Togashi, Hideyuki Maeda, Sumio Fujita, Tetsuya Sakai
LSTM vs. BM25 for Open-domain QA: A Hands-on Comparison of Effectiveness and Efficiency. SIGIR (2017)
Riku Togashi, Hideyuki Maeda, Vibhor Kanojia, Kousuke Morimoto, Sumio Fujita
Euclidean Image Embedding in view of Similarity Ranking in Auction Search by Image. WWW (Companion Volume) (2017)