15 citations · 20 across the 10 of their papers we have counts for
11 papers
A Riemannian Geometry for Low-rank Adaptation
Shoichiro Takeda, Shin'ya Yamaguchi, Satoshi Suzuki +1
Low-rank adaptation (LoRA) is widely used as a parameter-efficient fine-tuning technique for pre-trained deep neural networks, which approximates the weight update via full fine-tu…
A Tractable Continuous-Time Model for Designing Interventions for Time-Inconsistent Agents
Yasunori Akagi, Hideaki Kim, Daichi Fushihara +3
Designing effective goals and rewards for time-inconsistent agents is a central problem in many long-term tasks, such as learning, exercise, work, and project completion. An agent…
Delta Matters: An Analytically Tractable Model for - Discounting Agents
Yasunori Akagi, Takeshi Kurashima
Humans exhibit time-inconsistent behavior, in which planned actions diverge from executed actions. Understanding time inconsistency and designing appropriate interventions is a key…
A Continuous-time Tractable Model for Present-biased Agents
Yasunori Akagi, Hideaki Kim, Takeshi Kurashima
Present bias, the tendency to overvalue immediate rewards while undervaluing future ones, is a well-known barrier to achieving long-term goals. As artificial intelligence and behav…
Joint Pricing and Matching for Resource Allocation Platforms via Min-cost Flow Problem
Yuya Hikima, Yasunori Akagi, Hideaki Kim
Stochastic matching is the stochastic version of the well-known matching problem, which consists in maximizing the rewards of a matching under a set of probability distributions as…
Optimal Transport with Cyclic Symmetry
Shoichiro Takeda, Yasunori Akagi, Naoki Marumo +1
We propose novel fast algorithms for optimal transport (OT) utilizing a cyclic symmetry structure of input data. Such OT with cyclic symmetry appears universally in various real-wo…
Analytically Tractable Models for Decision Making under Present Bias
Yasunori Akagi, Naoki Marumo, Takeshi Kurashima
Time-inconsistency is a characteristic of human behavior in which people plan for long-term benefits but take actions that differ from the plan due to conflicts with short-term ben…
Aggregated Multi-output Gaussian Processes with Knowledge Transfer Across Domains
Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata +4
Aggregate data often appear in various fields such as socio-economics and public security. The aggregate data are associated not with points but with supports (e.g., spatial region…
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm
Yasunori Akagi, Naoki Marumo, Hideaki Kim +2
The importance of aggregated count data, which is calculated from the data of multiple individuals, continues to increase. Collective Graphical Model (CGM) is a probabilistic appro…
Probabilistic Optimal Transport based on Collective Graphical Models
Yasunori Akagi, Yusuke Tanaka, Tomoharu Iwata +2
Optimal Transport (OT) is being widely used in various fields such as machine learning and computer vision, as it is a powerful tool for measuring the similarity between probabilit…
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs
Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata +4
We propose a probabilistic model for inferring the multivariate function from multiple areal data sets with various granularities. Here, the areal data are observed not at location…