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pro vyhledávání: '"Liu, Weidong"'
The prevalence of sarcasm in social media, conveyed through text-image combinations, presents significant challenges for sentiment analysis and intention mining. Existing multi-modal sarcasm detection methods have been proven to overestimate performa
Externí odkaz:
http://arxiv.org/abs/2406.16464
Ontologies provide formal representation of knowledge shared within Semantic Web applications. Ontology learning involves the construction of ontologies from a given corpus. In the past years, ontology learning has traversed through shallow learning
Externí odkaz:
http://arxiv.org/abs/2404.14991
Sequential recommender systems (SRSs) aim to suggest next item for a user based on her historical interaction sequences. Recently, many research efforts have been devoted to attenuate the influence of noisy items in sequences by either assigning them
Externí odkaz:
http://arxiv.org/abs/2404.13878
Autor:
Xu, Yuzhuang, Han, Xu, Yang, Zonghan, Wang, Shuo, Zhu, Qingfu, Liu, Zhiyuan, Liu, Weidong, Che, Wanxiang
Model quantification uses low bit-width values to represent the weight matrices of existing models to be quantized, which is a promising approach to reduce both storage and computational overheads of deploying highly anticipated LLMs. However, curren
Externí odkaz:
http://arxiv.org/abs/2402.11295
In recent years, privacy-preserving machine learning algorithms have attracted increasing attention because of their important applications in many scientific fields. However, in the literature, most privacy-preserving algorithms demand learning obje
Externí odkaz:
http://arxiv.org/abs/2401.01294
Autor:
Liang, Kongming, Wang, Xinran, Wang, Rui, Gao, Donghui, Jin, Ling, Liu, Weidong, Zhu, Xiatian, Ma, Zhanyu, Guo, Jun
Attribute labeling at large scale is typically incomplete and partial, posing significant challenges to model optimization. Existing attribute learning methods often treat the missing labels as negative or simply ignore them all during training, eith
Externí odkaz:
http://arxiv.org/abs/2312.07009
Recently, reinforcement learning has gained prominence in modern statistics, with policy evaluation being a key component. Unlike traditional machine learning literature on this topic, our work places emphasis on statistical inference for the paramet
Externí odkaz:
http://arxiv.org/abs/2310.02581
Communication games, which we refer to as incomplete information games that heavily depend on natural language communication, hold significant research value in fields such as economics, social science, and artificial intelligence. In this work, we e
Externí odkaz:
http://arxiv.org/abs/2309.04658
Publikováno v:
Chengshi guidao jiaotong yanjiu, Vol 27, Iss 9, Pp 198-202 (2024)
Objective With its powerful semantic processing and open organization capabilities, the knowledge graph lays the foundation for knowledge-based organization and intelligent applications in various fields. In order to improve the digitization and inte
Externí odkaz:
https://doaj.org/article/bd7f2eba40fa49d59560062b7d6e668d