83 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- The University of TokyoJP3 papers
- Kyoto UniversityJP2 papers
- Purdue University West LafayetteUS2 papers
- Carnegie Mellon UniversityUS1 paper
- Hiroshima UniversityJP1 paper
- Japan Science and Technology AgencyJP1 paper
- Keio University Shonan FujisawaJP1 paper
- Massachusetts Institute of TechnologyUS1 paper
- Nara Institute of Science and TechnologyJP1 paper
- Osaka Prefecture UniversityJP1 paper
- Peking UniversityCN1 paper
- Tokyo Institute of TechnologyJP1 paper
13 papers
An accelerated proximal gradient method for multiobjective optimization
Hiroki Tanabe, Ellen H. Fukuda, Nobuo Yamashita
This paper presents an accelerated proximal gradient method for multiobjective optimization, in which each objective function is the sum of a continuously differentiable, convex fu…
Multiwave COVID-19 Prediction from Social Awareness using Web Search and Mobility Data
J. Xue, T. Yabe, K. Tsubouchi +2
Recurring outbreaks of COVID-19 have posed enduring effects on global society, which calls for a predictor of pandemic waves using various data with early availability. Existing pr…
NationalMood: Large-scale Estimation of People's Mood from Web Search Query and Mobile Sensor Data
Tadashi Okoshi, Wataru Sasaki, Hiroshi Kawane +1
The ability to estimate current affective statuses of web users has considerable potential towards the realization of user-centric opportune services. However, determining the type…
New merit functions for multiobjective optimization and their properties
Hiroki Tanabe, Ellen H. Fukuda, Nobuo Yamashita
A merit (gap) function is a map that returns zero at the solutions of problems and strictly positive values otherwise. Its minimization is equivalent to the original problem by def…
Syndromic surveillance using search query logs and user location information from smartphones against COVID-19 clusters in Japan
Shohei Hisada, Taichi Murayama, Kota Tsubouchi +4
[Background] Two clusters of coronavirus disease 2019 (COVID-19) were confirmed in Hokkaido, Japan in February 2020. To capture the clusters, this study employs Web search query lo…
Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior
Takahiro Yabe, Kota Tsubouchi, Toru Shimizu +2
Predicting the evacuation decisions of individuals before the disaster strikes is crucial for planning first response strategies. In addition to the studies on post-disaster analys…
Cross-comparative analysis of evacuation behavior after earthquakes using mobile phone data
Takahiro Yabe, Yoshihide Sekimoto, Kota Tsubouchi +1
Despite the importance of predicting evacuation mobility dynamics after large scale disasters for effective first response and disaster relief, our general understanding of evacuat…
Speaker Selective Beamformer with Keyword Mask Estimation
Yusuke Kida, Dung Tran, Motoi Omachi +2
This paper addresses the problem of automatic speech recognition (ASR) of a target speaker in background speech. The novelty of our approach is that we focus on a wakeup keyword, w…
Deep Learning Based Multi-modal Addressee Recognition in Visual Scenes with Utterances
Thao Minh Le, Nobuyuki Shimizu, Takashi Miyazaki +1
With the widespread use of intelligent systems, such as smart speakers, addressee recognition has become a concern in human-computer interaction, as more and more people expect suc…
Adapting Visual Question Answering Models for Enhancing Multimodal Community Q&A Platforms
Avikalp Srivastava, Hsin Wen Liu, Sumio Fujita
Question categorization and expert retrieval methods have been crucial for information organization and accessibility in community question & answering (CQA) platforms. Research in…
Diverse Stochasticity Leads a Colony of Ants to Optimal Foraging
Masashi Shiraishi, Rito Takeuchi, Hiroyuki Nakagawa +3
A mathematical model of garden ants (Laius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pher…
Chat Detection in an Intelligent Assistant: Combining Task-oriented and Non-task-oriented Spoken Dialogue Systems
Satoshi Akasaki, Nobuhiro Kaji
Recently emerged intelligent assistants on smartphones and home electronics (e.g., Siri and Alexa) can be seen as novel hybrids of domain-specific task-oriented spoken dialogue sys…
Incremental Skip-gram Model with Negative Sampling
Nobuhiro Kaji, Hayato Kobayashi
This paper explores an incremental training strategy for the skip-gram model with negative sampling (SGNS) from both empirical and theoretical perspectives. Existing methods of neu…