Zobrazeno 1 - 10
of 194 408
pro vyhledávání: '"MLE"'
Autor:
Ekren, Ibrahim, Nadtochiy, Sergey
In this paper, we consider a general partially observed diffusion model with periodic coefficients and with non-degenerate diffusion component. The coefficients of such a model depend on an unknown (static and deterministic) parameter which needs to
Externí odkaz:
http://arxiv.org/abs/2412.03380
Autor:
Zhang, Tonglin
Exact MLE for generalized linear mixed models (GLMMs) is a long-standing problem unsolved until today. The proposed research solves the problem. In this problem, the main difficulty is caused by intractable integrals in the likelihood function when t
Externí odkaz:
http://arxiv.org/abs/2410.08492
We revisit the recently introduced Local Glivenko-Cantelli setting, which studies distribution-dependent uniform convegence rates of the Maximum Likelihood Estimator (MLE). In this work, we investigate generalizations of this setting where arbitrary
Externí odkaz:
http://arxiv.org/abs/2410.02835
Autor:
Ye, Chong, Bernardes, Cesar A., Qian, Wei-Liang, Padula, Sandra S., Yue, Rui-Hong, Hama, Yogiro, Kodama, Takeshi
In this study, we use the maximum likelihood estimator (MLE) to explore factorization and event-plane correlations in relativistic heavy-ion collisions. Our analyses incorporate both numerical simulations and publicly available data from the CMS Coll
Externí odkaz:
http://arxiv.org/abs/2408.14347
Autor:
Zhong, Ziliang Samuel, Ling, Shuyang
Orthogonal group synchronization aims to recover orthogonal group elements from their noisy pairwise measurements. It has found numerous applications including computer vision, imaging science, and community detection. Due to the orthogonal constrain
Externí odkaz:
http://arxiv.org/abs/2408.05944
Autor:
Chan, Jun Shern, Chowdhury, Neil, Jaffe, Oliver, Aung, James, Sherburn, Dane, Mays, Evan, Starace, Giulio, Liu, Kevin, Maksin, Leon, Patwardhan, Tejal, Weng, Lilian, Mądry, Aleksander
We introduce MLE-bench, a benchmark for measuring how well AI agents perform at machine learning engineering. To this end, we curate 75 ML engineering-related competitions from Kaggle, creating a diverse set of challenging tasks that test real-world
Externí odkaz:
http://arxiv.org/abs/2410.07095
Autor:
Yue, Zuogong, Solo, Victor
We develop hard clustering based on likelihood rather than distance and prove convergence. We also provide simulations and real data examples.
Externí odkaz:
http://arxiv.org/abs/2409.06938
Autor:
Yang, Yuepeng, Ma, Cong
The Rasch model, a classical model in the item response theory, is widely used in psychometrics to model the relationship between individuals' latent traits and their binary responses on assessments or questionnaires. In this paper, we introduce a ne
Externí odkaz:
http://arxiv.org/abs/2406.13989
Autor:
Emezue, Chris
Structured prediction tasks, like machine translation, involve learning functions that map structured inputs to structured outputs. Recurrent Neural Networks (RNNs) have historically been a popular choice for such tasks, including in natural language
Externí odkaz:
http://arxiv.org/abs/2405.11819
Autor:
Greenberg, Danna1, Hibbert, Paul2
Publikováno v:
Academy of Management Learning & Education. Jun2022, Vol. 21 Issue 2, p161-166. 6p.
