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no code implementations • 27 Sep 2023 • Kuo-Hao Ho, Ruei-Yu Jheng, Ji-Han Wu, Fan Chiang, Yen-Chi Chen, Yuan-Yu Wu, I-Chen Wu

Interestingly in our experiments, our approach even reaches zero gap for 49 among 50 JSP instances whose job numbers are more than 150 on 20 machines.

no code implementations • 19 Mar 2023 • Zeyu Wei, Yen-Chi Chen

We introduce a new regression framework designed to deal with large-scale, complex data that lies around a low-dimensional manifold.

1 code implementation • 16 Oct 2021 • Yikun Zhang, Yen-Chi Chen

The set of local modes and the ridge lines estimated from a dataset are important summary characteristics of the data-generating distribution.

2 code implementations • 29 Apr 2021 • Yikun Zhang, Yen-Chi Chen

This paper studies the linear convergence of the subspace constrained mean shift (SCMS) algorithm, a well-known algorithm for identifying a density ridge defined by a kernel density estimator.

2 code implementations • 21 Apr 2021 • Zeyu Wei, Yen-Chi Chen

We introduce a density-based clustering method called skeleton clustering that can detect clusters in multivariate and even high-dimensional data with irregular shapes.

1 code implementation • 25 Jan 2021 • Yikun Zhang, Yen-Chi Chen

Under the (generalized) EM framework, we provide a new proof for the ascending property of density estimates and demonstrate the global convergence of directional mean shift sequences.

1 code implementation • 23 Oct 2020 • Yikun Zhang, Yen-Chi Chen

Directional data consist of observations distributed on a (hyper)sphere, and appear in many applied fields, such as astronomy, ecology, and environmental science.

no code implementations • 27 Jan 2020 • Tristan Cazenave, Yen-Chi Chen, Guan-Wei Chen, Shi-Yu Chen, Xian-Dong Chiu, Julien Dehos, Maria Elsa, Qucheng Gong, Hengyuan Hu, Vasil Khalidov, Cheng-Ling Li, Hsin-I Lin, Yu-Jin Lin, Xavier Martinet, Vegard Mella, Jeremy Rapin, Baptiste Roziere, Gabriel Synnaeve, Fabien Teytaud, Olivier Teytaud, Shi-Cheng Ye, Yi-Jun Ye, Shi-Jim Yen, Sergey Zagoruyko

Since DeepMind's AlphaZero, Zero learning quickly became the state-of-the-art method for many board games.

no code implementations • 5 Nov 2019 • Brian Nord, Andrew J. Connolly, Jamie Kinney, Jeremy Kubica, Gautaum Narayan, Joshua E. G. Peek, Chad Schafer, Erik J. Tollerud, Camille Avestruz, G. Jogesh Babu, Simon Birrer, Douglas Burke, João Caldeira, Douglas A. Caldwell, Joleen K. Carlberg, Yen-Chi Chen, Chuanfei Dong, Eric D. Feigelson, V. Zach Golkhou, Vinay Kashyap, T. S. Li, Thomas Loredo, Luisa Lucie-Smith, Kaisey S. Mandel, J. R. Martínez-Galarza, Adam A. Miller, Priyamvada Natarajan, Michelle Ntampaka, Andy Ptak, David Rapetti, Lior Shamir, Aneta Siemiginowska, Brigitta M. Sipőcz, Arfon M. Smith, Nhan Tran, Ricardo Vilalta, Lucianne M. Walkowicz, John ZuHone

The field of astronomy has arrived at a turning point in terms of size and complexity of both datasets and scientific collaboration.

no code implementations • 24 Apr 2019 • Yen-Chi Chen, Mauricio Sadinle

Pattern-mixture models provide a transparent approach for handling missing data, where the full-data distribution is factorized in a way that explicitly shows the parts that can be estimated from observed data alone, and the parts that require identifying restrictions.

Methodology Statistics Theory Statistics Theory

no code implementations • 12 Jul 2018 • Yen-Chi Chen

We also investigate the CIs by inverting the likelihood ratio test, the score test, and the Wald test, and we show that the resulting CIs may be very different.

1 code implementation • 4 Apr 2018 • Eric Berry, Yen-Chi Chen, Jessi Cisewski-Kehe, Brittany Terese Fasy

First, we review the various functional summaries in the literature and propose a unified framework for the functional summaries.

Methodology

no code implementations • 29 Nov 2017 • Yen-Chi Chen, Y. Samuel Wang, Elena A. Erosheva

Variational inference is a general approach for approximating complex density functions, such as those arising in latent variable models, popular in machine learning.

no code implementations • 11 Oct 2017 • Ruqian Chen, Yen-Chi Chen, Wei Guo, Ashis G. Banerjee

We introduce the concept of community trees that summarizes topological structures within a network.

no code implementations • 13 Oct 2016 • Yunhua Xiang, Yen-Chi Chen

In this paper, we study how the mean shift algorithm can be used to denoise a dataset.

no code implementations • NeurIPS 2016 • Jisu Kim, Yen-Chi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry Wasserman

A cluster tree provides a highly-interpretable summary of a density function by representing the hierarchy of its high-density clusters.

no code implementations • 8 Oct 2015 • Yen-Chi Chen, Daren Wang, Alessandro Rinaldo, Larry Wasserman

Persistence diagrams are two-dimensional plots that summarize the topological features of functions and are an important part of topological data analysis.

1 code implementation • 29 Jun 2015 • Yen-Chi Chen, Christopher R. Genovese, Larry Wasserman

The Morse-Smale complex of a function $f$ decomposes the sample space into cells where $f$ is increasing or decreasing.

no code implementations • NeurIPS 2015 • Yen-Chi Chen, Christopher R. Genovese, Shirley Ho, Larry Wasserman

We introduce the concept of coverage risk as an error measure for density ridge estimation.

no code implementations • 3 May 2015 • Martin Azizyan, Yen-Chi Chen, Aarti Singh, Larry Wasserman

We study the risk of mode-based clustering.

no code implementations • 4 Dec 2014 • Yen-Chi Chen, Christopher R. Genovese, Ryan J. Tibshirani, Larry Wasserman

Modal regression estimates the local modes of the distribution of $Y$ given $X=x$, instead of the mean, as in the usual regression sense, and can hence reveal important structure missed by usual regression methods.

no code implementations • 6 Jun 2014 • Yen-Chi Chen, Christopher R. Genovese, Larry Wasserman

Mode clustering is a nonparametric method for clustering that defines clusters using the basins of attraction of a density estimator's modes.

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