Zobrazeno 1 - 10
of 1 113
pro vyhledávání: '"WANG, YIJIA"'
Accurate power load forecasting is crucial for improving energy efficiency and ensuring power supply quality. Considering the power load forecasting problem involves not only dynamic factors like historical load variations but also static factors suc
Externí odkaz:
http://arxiv.org/abs/2409.17889
In recent years, multi-view outlier detection (MVOD) methods have advanced significantly, aiming to identify outliers within multi-view datasets. A key point is to better detect class outliers and class-attribute outliers, which only exist in multi-v
Externí odkaz:
http://arxiv.org/abs/2408.07819
Autor:
Seaborn, Katie, Itagaki, Tatsuya, Watanabe, Mizuki, Wang, Yijia, Geng, Ping, Fujii, Takao, Mandai, Yuto, Kojima, Miu, Yoshida, Suzuka
Publikováno v:
CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (2024), Article No.: 95, 1-8
Dark patterns and deceptive designs (DPs) are user interface elements that trick people into taking actions that benefit the purveyor. Such designs are widely deployed, with special varieties found in certain nations like Japan that can be traced to
Externí odkaz:
http://arxiv.org/abs/2405.08831
Autor:
Wang, Yijia, Seaborn, Katie
Publikováno v:
CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (2024), Article No.: 210, 1-9
Kawaii computing is a new term for a steadily growing body of work on the Japanese notion of "cute" in human-computer interaction (HCI) research and practice. Kawaii is distinguished from general notions of cute by its experiential and culturally-sen
Externí odkaz:
http://arxiv.org/abs/2405.08244
Autor:
Dong, Chaosheng, Wang, Yijia
This paper studies generalized inverse reinforcement learning (GIRL) in Markov decision processes (MDPs), that is, the problem of learning the basic components of an MDP given observed behavior (policy) that might not be optimal. These components inc
Externí odkaz:
http://arxiv.org/abs/2402.07246
A novel population-based optimization method is proposed in this paper, the Calico Salmon Migration Algorithm (CSMA), which is inspired by the natural behavior of calico salmon during their migration for mating. The CSMA optimization process comprise
Externí odkaz:
http://arxiv.org/abs/2311.05971
Autor:
Chu, Zhixuan, Guo, Huaiyu, Zhou, Xinyuan, Wang, Yijia, Yu, Fei, Chen, Hong, Xu, Wanqing, Lu, Xin, Cui, Qing, Li, Longfei, Zhou, Jun, Li, Sheng
Large language models (LLMs) show promise for natural language tasks but struggle when applied directly to complex domains like finance. LLMs have difficulty reasoning about and integrating all relevant information. We propose a data-centric approach
Externí odkaz:
http://arxiv.org/abs/2310.17784
We propose a general framework for decoding quantum error-correcting codes with generative modeling. The model utilizes autoregressive neural networks, specifically Transformers, to learn the joint probability of logical operators and syndromes. This
Externí odkaz:
http://arxiv.org/abs/2307.09025
When studying interacting systems, computing their statistical properties is a fundamental problem in various fields such as physics, applied mathematics, and machine learning. However, this task can be quite challenging due to the exponential growth
Externí odkaz:
http://arxiv.org/abs/2305.01874
It is very difficult to forecast the production rate of oil wells as the output of a single well is sensitive to various uncertain factors, which implicitly or explicitly show the influence of the static, temporal and spatial properties on the oil we
Externí odkaz:
http://arxiv.org/abs/2302.11195