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pro vyhledávání: '"Zhang, Qingyang"'
Autor:
Zhang, Qingyang
Chatterjee (2021) introduced a novel independence test that is rank-based, asymptotically normal and consistent against all alternatives. One limitation of Chatterjee's test is its low statistical power for detecting monotonic relationships. To addre
Externí odkaz:
http://arxiv.org/abs/2406.16859
Autor:
Zhang, Qingyang
This study investigates the extension of distance variance, a validated spread metric for continuous and binary variables [Edelmann et al., 2020, Ann. Stat., 48(6)], to quantify the spread of general categorical variables. We provide both geometric a
Externí odkaz:
http://arxiv.org/abs/2405.06813
Autor:
Zhang, Qingyang, Wei, Yake, Han, Zongbo, Fu, Huazhu, Peng, Xi, Deng, Cheng, Hu, Qinghua, Xu, Cai, Wen, Jie, Hu, Di, Zhang, Changqing
Multimodal fusion focuses on integrating information from multiple modalities with the goal of more accurate prediction, which has achieved remarkable progress in a wide range of scenarios, including autonomous driving and medical diagnosis. However,
Externí odkaz:
http://arxiv.org/abs/2404.18947
Autor:
Zhang, Qingyang
Pearson's Chi-squared test, though widely used for detecting association between categorical variables, exhibits low statistical power in large sparse contingency tables. To address this limitation, two novel permutation tests have been recently deve
Externí odkaz:
http://arxiv.org/abs/2403.17882
Autor:
Zhang, Qingyang
We introduce a new type of influence function, the asymptotic expected sensitivity function, which is often equivalent to but mathematically more tractable than the traditional one based on the Gateaux derivative. To illustrate, we study the robustne
Externí odkaz:
http://arxiv.org/abs/2401.05281
Many complicated real-world tasks can be broken down into smaller, more manageable parts, and planning with prior knowledge extracted from these simplified pieces is crucial for humans to make accurate decisions. However, replicating this process rem
Externí odkaz:
http://arxiv.org/abs/2312.11027
Scaling high-quality tutoring remains a major challenge in education. Due to growing demand, many platforms employ novice tutors who, unlike experienced educators, struggle to address student mistakes and thus fail to seize prime learning opportuniti
Externí odkaz:
http://arxiv.org/abs/2310.10648
Goal-Conditioned Hierarchical Reinforcement Learning (GCHRL) is a promising paradigm to address the exploration-exploitation dilemma in reinforcement learning. It decomposes the source task into subgoal conditional subtasks and conducts exploration a
Externí odkaz:
http://arxiv.org/abs/2307.12063
Autor:
Zhang, Qingyang, Wu, Haitao, Zhang, Changqing, Hu, Qinghua, Fu, Huazhu, Zhou, Joey Tianyi, Peng, Xi
The inherent challenge of multimodal fusion is to precisely capture the cross-modal correlation and flexibly conduct cross-modal interaction. To fully release the value of each modality and mitigate the influence of low-quality multimodal data, dynam
Externí odkaz:
http://arxiv.org/abs/2306.02050
Dynamic multi-objective optimisation (DMO) handles optimisation problems with multiple (often conflicting) objectives in varying environments. Such problems pose various challenges to evolutionary algorithms, which have popularly been used to solve c
Externí odkaz:
http://arxiv.org/abs/2305.12752