Zobrazeno 1 - 10
of 6 219
pro vyhledávání: '"chen, Fan"'
In this paper, we develop a unified framework for lower bound methods in statistical estimation and interactive decision making. Classical lower bound techniques -- such as Fano's inequality, Le Cam's method, and Assouad's lemma -- have been central
Externí odkaz:
http://arxiv.org/abs/2410.05117
Throughout its lifecycle, a large language model (LLM) generates a substantially larger carbon footprint during inference than training. LLM inference requests vary in batch size, prompt length, and token generation number, while cloud providers empl
Externí odkaz:
http://arxiv.org/abs/2410.02950
Autor:
Huang, Yubo, Feng, Wenhao, Lai, Xin, Wang, Zixi, Xu, Jingzehua, Zhang, Shuai, He, Hongjie, Chen, Fan
Advanced facial recognition technologies and recommender systems with inadequate privacy technologies and policies for facial interactions increase concerns about bioprivacy violations. With the proliferation of video and live-streaming websites, pub
Externí odkaz:
http://arxiv.org/abs/2409.19306
Autor:
Chen, Fan, Yuan, Xiying
A graph is said to be $H$-free if it does not contain $H$ as a subgraph. Brualdi-Hoffman-Tur\'{a}n type problem is to determine the maximum spectral radius of an $H$-free graph $G$ with give size $m$. The $F_k$ is the graph consisting of $k$ triangle
Externí odkaz:
http://arxiv.org/abs/2409.14138
Autor:
Shen, Yaojie, Wang, Xinyao, Niu, Yulei, Zhou, Ying, Tang, Lexin, Zhang, Libo, Chen, Fan, Wen, Longyin
Preference Optimization (PO), is gaining popularity as an alternative choice of Proximal Policy Optimization (PPO) for aligning Large Language Models (LLMs). Recent research on aligning LLMs iteratively with synthetic or partially synthetic data show
Externí odkaz:
http://arxiv.org/abs/2409.08845
This paper presents a novel volume of fluid ghost-cell immersed boundary (IB) method for two-phase free surface flow interacting with structures. To circumvent the disturbance occurring around the intersection area of the IB and free surface when usi
Externí odkaz:
http://arxiv.org/abs/2409.08810
Let $\Gamma=(K_n,H)$ be a signed complete graph whose negative edges induce a subgraph $H$. Let $A(\Gamma)$ be the adjacency matrix of the signed graph $\Gamma$. The largest eigenvalue of $A(\Gamma)$ is called the index of $\Gamma$. In this paper, th
Externí odkaz:
http://arxiv.org/abs/2409.01923
Current quantum generative adversarial networks (QGANs) still struggle with practical-sized data. First, many QGANs use principal component analysis (PCA) for dimension reduction, which, as our studies reveal, can diminish the QGAN's effectiveness. S
Externí odkaz:
http://arxiv.org/abs/2409.02212
Autor:
fu, Zhenxiao, Chen, Fan
Quantum Neural Networks (QNNs), now offered as QNN-as-a-Service (QNNaaS), have become key targets for model extraction attacks. State-of-the-art methods use ensemble learning to train accurate substitute QNNs, but our analysis reveals significant lim
Externí odkaz:
http://arxiv.org/abs/2409.02207
Autor:
Deng, Zhaoli, Liu, Wen, Wang, Fanyi, Zhang, Junkang, Chen, Fan, Zhang, Meng, Zhang, Wendong, Mi, Zhenpeng
Portrait Fidelity Generation is a prominent research area in generative models, with a primary focus on enhancing both controllability and fidelity. Current methods face challenges in generating high-fidelity portrait results when faces occupy a smal
Externí odkaz:
http://arxiv.org/abs/2408.09248