Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Lian, Jiayi"'
Autor:
Lian, Jiayi
In data science, machine learning methods, such as deep learning and other AI algorithms, have been widely used in many applications. These machine learning methods often have complicated model structures with a large number of model parameters and a
Externí odkaz:
http://hdl.handle.net/10919/115953
We investigate pseudo-polynomial time algorithms for Subset Sum. Given a multi-set $X$ of $n$ positive integers and a target $t$, Subset Sum asks whether some subset of $X$ sums to $t$. Bringmann proposes an $\tilde{O}(n + t)$-time algorithm [Bringma
Externí odkaz:
http://arxiv.org/abs/2402.14493
We propose an $\widetilde{O}(n + 1/\eps)$-time FPTAS (Fully Polynomial-Time Approximation Scheme) for the classical Partition problem. This is the best possible (up to a polylogarithmic factor) assuming SETH (Strong Exponential Time Hypothesis) [Abbo
Externí odkaz:
http://arxiv.org/abs/2402.11426
Publikováno v:
Statistica Sinica 2023
The modified Cholesky decomposition is popular for inverse covariance estimation, but often needs pre-specification on the full information of variable ordering. In this work, we propose a block Cholesky decomposition (BCD) for estimating inverse cov
Externí odkaz:
http://arxiv.org/abs/2308.09256
We investigate polynomial-time approximation schemes for the classic 0-1 knapsack problem. The previous algorithm by Deng, Jin, and Mao (SODA'23) has approximation factor $1 + \eps$ with running time $\widetilde{O}(n + \frac{1}{\eps^{2.2}})$. There i
Externí odkaz:
http://arxiv.org/abs/2308.07821
We investigate pseudopolynomial-time algorithms for Bounded Knapsack and Bounded Subset Sum. Recent years have seen a growing interest in settling their fine-grained complexity with respect to various parameters. For Bounded Knapsack, the number of i
Externí odkaz:
http://arxiv.org/abs/2307.12582
Artificial intelligence (AI) systems have become increasingly popular in many areas. Nevertheless, AI technologies are still in their developing stages, and many issues need to be addressed. Among those, the reliability of AI systems needs to be demo
Externí odkaz:
http://arxiv.org/abs/2111.05391
Autor:
Zhu, Shuying, He, Jing, Yin, Liliang, Zhou, Jiawei, Lian, Jiayi, Ren, Yanli, Zhang, Xinling, Yuan, Jinghua, Wang, Gang, Li, Xiaoping
Publikováno v:
In Urologic Oncology: Seminars and Original Investigations September 2024 42(9):275-287
Publikováno v:
In Food Bioscience February 2024 57
Artificial intelligent (AI) algorithms, such as deep learning and XGboost, are used in numerous applications including computer vision, autonomous driving, and medical diagnostics. The robustness of these AI algorithms is of great interest as inaccur
Externí odkaz:
http://arxiv.org/abs/2010.15551