Zobrazeno 1 - 10
of 1 765
pro vyhledávání: '"Du, Liang"'
Persistent homology, a fundamental technique within Topological Data Analysis (TDA), captures structural and shape characteristics of graphs, yet encounters computational difficulties when applied to dynamic directed graphs. This paper introduces the
Externí odkaz:
http://arxiv.org/abs/2408.09123
Heterogeneous treatment effect (HTE) estimation is vital for understanding the change of treatment effect across individuals or subgroups. Most existing HTE estimation methods focus on addressing selection bias induced by imbalanced distributions of
Externí odkaz:
http://arxiv.org/abs/2407.03082
Kernel methods are extensively employed for nonlinear data clustering, yet their effectiveness heavily relies on selecting suitable kernels and associated parameters, posing challenges in advance determination. In response, Multiple Kernel Clustering
Externí odkaz:
http://arxiv.org/abs/2405.16447
The performance of Large Language Models (LLMs) relies heavily on the quality of prompts, which are often manually engineered and task-specific, making them costly and non-scalable. We propose a novel approach, Supervisory Prompt Training (SPT). SPT
Externí odkaz:
http://arxiv.org/abs/2403.18051
The Bayesian reconstruction entropy is considered an alternative to the Shannon-Jaynes entropy, as it does not exhibit the asymptotic flatness characteristic of the Shannon-Jaynes entropy and obeys the scale invariance. It is commonly utilized in con
Externí odkaz:
http://arxiv.org/abs/2401.00018
Autor:
Cheng, Zhenyu, Li, Ying, Lu, Hantao, Hu, Xiang, Huang, Zhongbing, Fiete, Gregory A., Du, Liang
Publikováno v:
Phys Rev B 109, 195121 (2024)
Doublon-holon dynamics is investigated in a pumped one-dimensional Hubbard model with a staggered on?site Coulomb interaction at half-filling. When the system parameters are set to be in the Mott insulating regime the equilibrium sublattice density o
Externí odkaz:
http://arxiv.org/abs/2311.13395
Large language models (LLMs) such as GPT-4 have exhibited remarkable performance in a variety of tasks, but this strong performance often comes with the high expense of using paid API services. In this paper, we are motivated to study building an LLM
Externí odkaz:
http://arxiv.org/abs/2310.03094
Click-through rate (CTR) prediction is a critical task in recommendation systems, serving as the ultimate filtering step to sort items for a user. Most recent cutting-edge methods primarily focus on investigating complex implicit and explicit feature
Externí odkaz:
http://arxiv.org/abs/2309.14891
As the ever-increasing token limits of large language models (LLMs) have enabled long context as input, prompting with single data samples might no longer an efficient way. A straightforward strategy improving efficiency is to batch data within the t
Externí odkaz:
http://arxiv.org/abs/2309.00384
Fair feature selection for classification decision tasks has recently garnered significant attention from researchers. However, existing fair feature selection algorithms fall short of providing a full explanation of the causal relationship between f
Externí odkaz:
http://arxiv.org/abs/2306.10336