Takeshi Kurashima
12 papers · 2018–2026 · 3 venues · across top CS/AI venues
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Achievements
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๐บ๏ธ Taxonomy Completionist (31) ๐ Academic Marathon ยท Sprint ๐ Conference Polyglot ยท Bronze ๐ Interdisciplinary Bridge ยท Silver ๐ฃ Hot Topic Early Bird
๐
Keyword Champion
(2)
๐งฌ
Topic Evolution
๐
Trend Setter
๐
Conference Pioneer
๐
Century Club ยท Bronze
๐๏ธ
Keyword Collector
(78)
Venues
Top co-authors
Research topics
Machine Learning
(10)
Mathematics & Optimization
(8)
Artificial Intelligence
(6)
Optimization
(6)
Optimization & Theory
(6)
Core AI
(4)
Data Science & Analytics
(3)
Bayesian & Probabilistic ยท Machine Learning
(3)
Core Methods
(3)
Learning Types
(3)
Application Areas
(2)
Applications
(2)
Bayesian & Probabilistic ยท Artificial Intelligence
(2)
Mathematics
(2)
Probability
(2)
Keywords
probabilistic model
(2)
decision making
(2)
collective graphical model
(2)
combinatorial optimization
(2)
map inference
(2)
gaussian process
(2)
probabilistic modeling
(2)
spatial data
(2)
present bia
(2)
time inconsistency
(2)
behavioral economics
(2)
expectation maximization
(1)
bayesian inference
(1)
privacy preservation
(1)
bipartite matching
(1)
transfer learning
(1)
semi-supervised learning
(1)
uncertainty quantification
(1)
multivariate regression
(1)
em algorithm
(1)
Papers
Delta Matters: An Analytically Tractable Model for betaโdelta Discounting Agents
AAAI 2026
A Continuous-time Tractable Model for Present-biased Agents
AAAI 2025
Analytically Tractable Models for Decision Making under Present Bias
AAAI 2024
Reassessing Evaluation Functions in Algorithmic Recourse: An Empirical Study from a Human-Centered Perspective
IJCAI 2024
Integrated Optimization of Bipartite Matching and Its Stochastic Behavior: New Formulation and Approximation Algorithm via Min-cost Flow Optimization
AAAI 2021
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm
NeurIPS 2021
Exact and Efficient Inference for Collective Flow Diffusion Model via Minimum Convex Cost Flow Algorithm
AAAI 2020
Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data
IJCAI 2020
Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities
AAAI 2019
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs
NeurIPS 2019
A Fast and Accurate Method for Estimating People Flow from Spatiotemporal Population Data
IJCAI 2018
Estimating Latent People Flow without Tracking Individuals
IJCAI 2018