no code implementations • 16 Apr 2024 • Wei-Chung Shia, Yu-Len Huang, Yi-Chun Chen, Hwa-Koon Wu, Dar-Ren Chen
The simulation results indicated that this technology is helpful in discriminating positive from negative margins in the intra-operative setting.
no code implementations • 14 Dec 2023 • Yi-Chun Chen, Arnav Jhala
Our contributions to the community are: a dataset of annotated manga books, a multi-modal analysis of visual panels and text in a constrained and popular medium through high-level features, and a systematic process for incorporating subjective narrative patterns in computational models.
no code implementations • 14 Dec 2023 • Yi-Chun Chen, Arnav Jhala
Among static visual narratives such as comics and manga, there are distinct visual styles in terms of presentation.
no code implementations • 14 Dec 2023 • Yi-Chun Chen, Arnav Jhala
We present a theory-inspired visual narrative generator that incorporates comic-authoring idioms, which transfers the conceptual principles of comics into system layers that integrate the theories to create comic content.
no code implementations • 8 Feb 2023 • Yi-Chun Chen, Dmitry Mitrofanov
The identification of choice models is crucial for understanding consumer behavior, designing marketing policies, and developing new products.
no code implementations • 28 Oct 2022 • Yi-Chun Chen, Gaoji Hu, Xiangqian Yang
Agents learn private information (signals) from an information designer about the allocation payoff to the principal.
no code implementations • 22 Sep 2022 • Soumen Banerjee, Yi-Chun Chen
We study a full implementation problem with hard evidence where the state is common knowledge but agents face uncertainty about the evidence endowments of other agents.
no code implementations • 13 Oct 2021 • Yi-Chun Chen, Takashi Kunimoto, Yifei Sun, Siyang Xiong
The theory of full implementation has been criticized for using integer/modulo games which admit no equilibrium (Jackson (1992)).
no code implementations • 26 May 2021 • Soumen Banerjee, Yi-Chun Chen, Yifei Sun
In a richer model of evidence due to <cite>KT2012</cite>, we establish pure-strategy implementation with two or more agents in a direct revelation mechanism.
no code implementations • 4 Feb 2021 • Yi-Chun Chen, Manuel Mueller-Frank, Mallesh M Pai
The classic wisdom-of-the-crowd problem asks how a principal can "aggregate" information about the unknown state of the world from agents without understanding the information structure among them.
no code implementations • 29 Dec 2020 • Daniel Stanley Tan, Yi-Chun Chen, Trista Pei-Chun Chen, Wei-Chao Chen
In this paper, we propose a framework called TrustMAE to address the problem of product defect classification.
no code implementations • 18 Dec 2020 • Yu-Wen Chen, Sourav Medya, Yi-Chun Chen
In this paper, we aim to identify and understand the impact of various factors on O3 formation and predict the O3 concentrations under different pollution-reduced and climate change scenarios.
no code implementations • 18 Oct 2020 • Yi-Chun Chen, Xiangqian Yang
We also show that in an ex ante symmetric setting, an asymmetric information structure is never seller-worst but can generate a strictly higher surplus for the buyers than the symmetric buyer-optimal information structure.
no code implementations • 25 Apr 2019 • Yi-Chun Chen, Velibor V. Mišić
In this model, each customer type is associated with a binary decision tree, which represents a decision process for making a purchase based on checking for the existence of specific products in the assortment.
1 code implementation • 23 Nov 2017 • Shih-Han Chou, Yi-Chun Chen, Kuo-Hao Zeng, Hou-Ning Hu, Jianlong Fu, Min Sun
The negative log reconstruction loss of the reverse sentence (referred to as "irrelevant loss") is jointly minimized to encourage the reverse sentence to be different from the given sentence.
1 code implementation • 19 Sep 2017 • Kunal Menda, Yi-Chun Chen, Justin Grana, James W. Bono, Brendan D. Tracey, Mykel J. Kochenderfer, David Wolpert
The incorporation of macro-actions (temporally extended actions) into multi-agent decision problems has the potential to address the curse of dimensionality associated with such decision problems.
1 code implementation • 8 Dec 2015 • Yi-Chun Chen, Tim Allan Wheeler, Mykel John Kochenderfer
Learning Bayesian networks from raw data can help provide insights into the relationships between variables.