Riku Togashi

45 papers A* 13A 3B 2Misc 2Journal 20Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Beyond Match Maximization and Fairness: Retention-Optimized Two-Sided Matching.
CoRR
Ren Kishimoto, Rikiya Takehi, Koichi Tanaka, Masahiro Nomura, Riku Togashi, Yoji Tomita, Yuta Saito
2025 A* conf
Instance-wise Supervision-level Optimization in Active Learning.
CVPR
Shinnosuke Matsuo, Riku Togashi, Ryoma Bise, Seiichi Uchida, Masahiro Nomura
2025 J jnl
Instance-wise Supervision-level Optimization in Active Learning.
CoRR
Shinnosuke Matsuo, Riku Togashi, Ryoma Bise, Seiichi Uchida, Masahiro Nomura
2024 J jnl
LTSim: Layout Transportation-based Similarity Measure for Evaluating Layout Generation.
CoRR
Mayu Otani, Naoto Inoue, Kotaro Kikuchi, Riku Togashi
2024 — conf
Robust Nearest Neighbors for Source-Free Domain Adaptation Under Class Distribution Shift.
ECCV (72)
Antonio Tejero-de-Pablos, Riku Togashi, Mayu Otani, Shin'ichi Satoh
2024 A* conf
Safe Collaborative Filtering.
ICLR
Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura
2024 A* conf
Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems.
WWW
Riku Togashi, Kenshi Abe, Yuta Saito
2024 J jnl
Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems.
CoRR
Riku Togashi, Kenshi Abe, Yuta Saito
2023 A* conf
A Critical Reexamination of Intra-List Distance and Dispersion.
SIGIR
Naoto Ohsaka, Riku Togashi
2023 J jnl
A Critical Reexamination of Intra-List Distance and Dispersion.
CoRR
Naoto Ohsaka, Riku Togashi
2023 A* conf
Curse of "Low" Dimensionality in Recommender Systems.
SIGIR
Naoto Ohsaka, Riku Togashi
2023 J jnl
Curse of "Low" Dimensionality in Recommender Systems.
CoRR
Naoto Ohsaka, Riku Togashi
2023 A* conf
Exploration of Unranked Items in Safe Online Learning to Re-Rank.
SIGIR
Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi
2023 J jnl
Exploration of Unranked Items in Safe Online Learning to Re-Rank.
CoRR
Hiroaki Shiino, Kaito Ariu, Kenshi Abe, Riku Togashi
2023 A conf
Fast and Examination-agnostic Reciprocal Recommendation in Matching Markets.
RecSys
Yoji Tomita, Riku Togashi, Yuriko Hashizume, Naoto Ohsaka
2023 J jnl
Fast and Examination-agnostic Reciprocal Recommendation in Matching Markets.
CoRR
Yoji Tomita, Riku Togashi, Yuriko Hashizume, Naoto Ohsaka
2023 J jnl
Safe Collaborative Filtering.
CoRR
Riku Togashi, Tatsushi Oka, Naoto Ohsaka, Tetsuro Morimura
2023 A* conf
Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation.
CVPR
Mayu Otani, Riku Togashi, Yu Sawai, Ryosuke Ishigami, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Shin'ichi Satoh
2023 J jnl
Toward Verifiable and Reproducible Human Evaluation for Text-to-Image Generation.
CoRR
Mayu Otani, Riku Togashi, Yu Sawai, Ryosuke Ishigami, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Shin'ichi Satoh
2022 A* conf
AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval.
CVPR
Riku Togashi, Mayu Otani, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Tetsuya Sakai
2022 J jnl
AxIoU: An Axiomatically Justified Measure for Video Moment Retrieval.
CoRR
Riku Togashi, Mayu Otani, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Tetsuya Sakai
2022 J jnl
DM
IEEE Access
Shunsuke Kitada, Yuki Iwazaki, Riku Togashi, Hitoshi Iyatomi
2022 J jnl
DM
CoRR
Shunsuke Kitada, Yuki Iwazaki, Riku Togashi, Hitoshi Iyatomi
2022 J jnl
Fair Matrix Factorisation for Large-Scale Recommender Systems.
CoRR
Riku Togashi, Kenshi Abe
2022 A conf
Matching Theory-based Recommender Systems in Online Dating.
RecSys
Yoji Tomita, Riku Togashi, Daisuke Moriwaki
2022 J jnl
Matching Theory-based Recommender Systems in Online Dating.
CoRR
Yoji Tomita, Riku Togashi, Daisuke Moriwaki
2022 A* conf
Optimal Correction Cost for Object Detection Evaluation.
CVPR
Mayu Otani, Riku Togashi, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Shin'ichi Satoh
2022 J jnl
Optimal Correction Cost for Object Detection Evaluation.
CoRR
Mayu Otani, Riku Togashi, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, Shin'ichi Satoh
2021 A conf
Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph.
WSDM
Riku Togashi, Mayu Otani, Shin'ichi Satoh
2021 A* conf
Density-Ratio Based Personalised Ranking from Implicit Feedback.
WWW
Riku Togashi, Masahiro Kato, Mayu Otani, Shin'ichi Satoh
2021 J jnl
Density-Ratio Based Personalised Ranking from Implicit Feedback.
CoRR
Riku Togashi, Masahiro Kato, Mayu Otani, Shin'ichi Satoh
2021 A* conf
Scalable Personalised Item Ranking through Parametric Density Estimation.
SIGIR
Riku Togashi, Masahiro Kato, Mayu Otani, Tetsuya Sakai, Shin'ichi Satoh
2021 J jnl
Scalable Personalised Item Ranking through Parametric Density Estimation.
CoRR
Riku Togashi, Masahiro Kato, Mayu Otani, Tetsuya Sakai, Shin'ichi Satoh
2020 J jnl
Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph.
CoRR
Riku Togashi, Mayu Otani, Shin'ichi Satoh
2020 B conf
Automatic Evaluation of Iconic Image Retrieval based on Colour, Shape, and Texture.
ICMR
Riku Togashi, Sumio Fujita, Tetsuya Sakai
2020 A* conf
Visual Intents vs. Clicks, Likes, and Purchases in E-commerce.
SIGIR
Riku Togashi, Tetsuya Sakai
2019 — conf
Closing the Gap Between Query and Database through Query Feature Transformation in C2C e-Commerce Visual Search.
eCOM@SIGIR
Takuma Yamaguchi, Kosuke Arase, Riku Togashi, Shunya Ueta
2019 Misc conf
Generalising Kendall's Tau for Noisy and Incomplete Preference Judgements.
ICTIR
Riku Togashi, Tetsuya Sakai
2019 B conf
Uplift Modeling for Cost Effective Coupon Marketing in C-to-C E-Commerce.
ICTAI
Akihiro Shimizu, Riku Togashi, Antony Lam, Nam Van Huynh
2018 Misc conf
Classifying Community QA Questions That Contain an Image.
ICTIR
Kenta Tamaki, Riku Togashi, Sosuke Kato, Sumio Fujita, Hideyuki Maeda, Tetsuya Sakai
2017 — conf
Dual Constrained Question Embeddings with Relational Knowledge Bases for Simple Question Answering.
IJCNLP(2)
Kaustubh Kulkarni, Riku Togashi, Hideyuki Maeda, Sumio Fujita
2017 — conf
Enhancing Knowledge Graph Embedding with Probabilistic Negative Sampling.
WWW (Companion Volume)
Vibhor Kanojia, Hideyuki Maeda, Riku Togashi, Sumio Fujita
2017 — conf
Euclidean Image Embedding in view of Similarity Ranking in Auction Search by Image.
WWW (Companion Volume)
Riku Togashi, Hideyuki Maeda, Vibhor Kanojia, Kousuke Morimoto, Sumio Fujita
2017 A* conf
LSTM vs. BM25 for Open-domain QA: A Hands-on Comparison of Effectiveness and Efficiency.
SIGIR
Sosuke Kato, Riku Togashi, Hideyuki Maeda, Sumio Fujita, Tetsuya Sakai
2017 J jnl
Relevance Score of Triplets Using Knowledge Graph Embedding - The Pigweed Triple Scorer at WSDM Cup 2017.
CoRR
Vibhor Kanojia, Riku Togashi, Hideyuki Maeda