WeiYa's Work Yard

A dog, who fell into the ocean of statistics, tries to write down his ideas and notes to save himself.

Benign Overfitting in Linear Regression

October 11, 2021 0 Comments

This note is for Bartlett, P. L., Long, P. M., Lugosi, G., & Tsigler, A. (2020). Benign Overfitting in Linear Regression. ArXiv:1906.11300 [Cs, Math, Stat].

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Multiple Descent of Minimum-Norm Interpolants

October 11, 2021 0 Comments

This note is for Liang, T., Rakhlin, A., & Zhai, X. (2020). On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels. ArXiv:1908.10292 [Cs, Math, Stat].

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Exploring DNN via Layer-Peeled Model

September 25, 2021 0 Comments

This note is for Fang, C., He, H., Long, Q., & Su, W. J. (2021). Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training. ArXiv:2101.12699 [Cs, Math, Stat].

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Conformal Inference

September 22, 2021 0 Comments

The note is based on Lei, J., G’Sell, M., Rinaldo, A., Tibshirani, R. J., & Wasserman, L. (2018). Distribution-Free Predictive Inference for Regression. Journal of the American Statistical Association, 113(523), 1094–1111. and Tibshirani, R. J., Candès, E. J., Barber, R. F., & Ramdas, A. (2019). Conformal Prediction Under Covariate Shift. Proceedings of the 33rd International Conference on Neural Information Processing Systems, 2530–2540.

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Bayesian Sparse Multiple Regression

September 16, 2021 0 Comments

This note is for Chakraborty, A., Bhattacharya, A., & Mallick, B. K. (2020). Bayesian sparse multiple regression for simultaneous rank reduction and variable selection. Biometrika, 107(1), 205–221.

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Cross-Validation for High-Dimensional Ridge and Lasso

September 16, 2021 0 Comments

This note collects several references on the research of cross-validation.

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Local Tracklets Filtering and Global Tracklets Association

July 05, 2021 (Update: ) 0 Comments

This note is for Xing, J., Ai, H., & Lao, S. (2009). Multi-object tracking through occlusions by local tracklets filtering and global tracklets association with detection responses. 2009 IEEE Conference on Computer Vision and Pattern Recognition, 1200–1207.

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Multiple Object Tracking via Minimizing Energy

July 05, 2021 0 Comments

The note is for Milan, Anton, Stefan Roth, and Konrad Schindler. “Continuous Energy Minimization for Multitarget Tracking.” IEEE Transactions on Pattern Analysis and Machine Intelligence 36, no. 1 (January 2014): 58–72.

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Knowledge Graph and Electronic Medical Records

June 29, 2021 0 Comments

This note covers several papers on Knowledge Graph and Electronic Medical Records.

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Self-organized Maps of Document Collections

June 12, 2021 0 Comments

This note is for Kaski, S., Honkela, T., Lagus, K., & Kohonen, T. (1998). WEBSOM – Self-organizing maps of document collections

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Biomedical Named Entity Recognition

June 10, 2021 0 Comments

This note is for Tian, Y., Shen, W., Song, Y., Xia, F., He, M., & Li, K. (2020). Improving biomedical named entity recognition with syntactic information. BMC Bioinformatics, 21(1), 539.

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Summarize Medical Conversations

June 10, 2021 0 Comments

This note is for Song, Y., Tian, Y., Wang, N., & Xia, F. (2020). Summarizing Medical Conversations via Identifying Important Utterances. Proceedings of the 28th International Conference on Computational Linguistics, 717–729.

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Word Segmentation and Medical Concept Recognition for Chinese Medical Texts

June 10, 2021 0 Comments

This note is for Liu, Y., Tian, Y., Chang, T.-H., Wu, S., Wan, X., & Song, Y. (2021). Exploring Word Segmentation and Medical Concept Recognition for Chinese Medical Texts. Proceedings of the 20th Workshop on Biomedical Language Processing, 213–220.

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Unsupervised Multi-granular Chinese Word Segmentation via Graph Partition

June 03, 2021 0 Comments

This note is for Yuan, Z., Liu, Y., Yin, Q., Li, B., Feng, X., Zhang, G., & Yu, S. (2020). Unsupervised multi-granular Chinese word segmentation and term discovery via graph partition. Journal of Biomedical Informatics, 110, 103542.

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End-to-End Instance Segmentation

May 27, 2021 0 Comments

This note is for ISTR: End-to-End Instance Segmentation with Transformers.

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A pHMM Algorithm for Correcting Long Reads

May 26, 2021 0 Comments

This note is for Firtina, C., Bar-Joseph, Z., Alkan, C., & Cicek, A. E. (2018). Hercules: A profile HMM-based hybrid error correction algorithm for long reads. Nucleic Acids Research, 46(21), e125.

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Permutation Tests and Randomization Tests

May 22, 2021 0 Comments

This note is for Hemerik, J., & Goeman, J. J. (2020). Another look at the Lady Tasting Tea and differences between permutation tests and randomization tests. International Statistical Review, insr.12431.

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Hypothesis Testing on A Nuisance Parameter

May 11, 2021 0 Comments

This note is for DAVIES, R. B. (1987). Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika, 74(1), 33–43.

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Multivariate Adaptive Regression Splines

May 10, 2021 0 Comments

This note is for Friedman, J. H. (1991). Multivariate Adaptive Regression Splines. The Annals of Statistics, 19(1), 1–67.

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Generalized Degrees of Freedom

May 03, 2021 0 Comments

This note is for Ye, J. (1998). On Measuring and Correcting the Effects of Data Mining and Model Selection. Journal of the American Statistical Association, 93(441), 120–131..

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Instance Segmentation with Cosine Embeddings

April 25, 2021 (Update: ) 0 Comments

This note is for Payer, C., Štern, D., Neff, T., Bischof, H., & Urschler, M. (2018). Instance Segmentation and Tracking with Cosine Embeddings and Recurrent Hourglass Networks. ArXiv:1806.02070 [Cs].

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Star Formation

March 13, 2021 0 Comments

This note is for Chapter 19 of Astronomy Today, 8th Edition.

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Monetone B-spline Smoothing

March 09, 2021 (Update: ) 0 Comments

This note is based on He, X., & Shi, P. (1998). Monotone B-Spline Smoothing. Journal of the American Statistical Association, 93(442), 643–650., and the reproduced simulations are based on the updated algorithm, Ng, P., & Maechler, M. (2007). A fast and efficient implementation of qualitatively constrained quantile smoothing splines. Statistical Modelling, 7(4), 315–328.

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Sequence Alignment in EHR

November 12, 2020 (Update: )

This note is for Huang, M., Shah, N. D., & Yao, L. (2019). Evaluating global and local sequence alignment methods for comparing patient medical records. BMC Medical Informatics and Decision Making, 19(6), 263.

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Efficient ICP Variants

November 07, 2020 (Update: )

This note is for Rusinkiewicz, S., & Levoy, M. (2001). Efficient variants of the ICP algorithm. Proceedings Third International Conference on 3-D Digital Imaging and Modeling, 145–152..

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Iterative Closest Point

November 07, 2020

This note is for Besl, P. J., & McKay, N. D. (1992). Method for registration of 3-D shapes. Sensor Fusion IV: Control Paradigms and Data Structures, 1611, 586–606..

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Principal Curves

September 28, 2020 (Update: )

This post is mainly based on Hastie, T., & Stuetzle, W. (1989). Principal Curves. Journal of the American Statistical Association.

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Particle Tracking as Linear Assignment Problem

September 24, 2020 (Update: )

This post is based on Jaqaman, K., Loerke, D., Mettlen, M., Kuwata, H., Grinstein, S., Schmid, S. L., & Danuser, G. (2008). Robust single-particle tracking in live-cell time-lapse sequences. Nature Methods, 5(8), 695–702.

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Global Tracking via the Viterbi Algorithm

August 27, 2020

This post is for Magnusson, K. E. G., Jalden, J., Gilbert, P. M., & Blau, H. M. (2015). Global Linking of Cell Tracks Using the Viterbi Algorithm. IEEE Transactions on Medical Imaging, 34(4), 911–929.

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An objective comparison of cell-tracking algorithms

August 21, 2020

This note is for Ulman, V., Maška, M., Magnusson, K. E. G., Ronneberger, O., Haubold, C., Harder, N., Matula, P., Matula, P., Svoboda, D., Radojevic, M., Smal, I., Rohr, K., Jaldén, J., Blau, H. M., Dzyubachyk, O., Lelieveldt, B., Xiao, P., Li, Y., Cho, S.-Y., … Ortiz-de-Solorzano, C. (2017). An objective comparison of cell-tracking algorithms. Nature Methods, 14(12), 1141–1152.

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