WeiYa's Work Yard

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

Additive Model with Linear Smoother

December 07, 2021

This note is for Buja, A., Hastie, T., & Tibshirani, R. (1989). Linear Smoothers and Additive Models. The Annals of Statistics, 17(2), 453–510. JSTOR.

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Asymptotics of Cross Validation

December 03, 2021

This note is for Austern, M., & Zhou, W. (2020). Asymptotics of Cross-Validation. ArXiv:2001.11111 [Math, Stat].

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Review on Random Matrix Theory

December 01, 2021

This note is for Paul, D., & Aue, A. (2014). Random matrix theory in statistics: A review. Journal of Statistical Planning and Inference, 150, 1–29.

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Probabilistic Principal Curves

November 22, 2021

This note is for Chang, K.-Y., & Ghosh, J. (2001). A unified model for probabilistic principal surfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(1), 22–41., but only involves the principal curves.

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Regularization-Free Principal Curves

November 21, 2021

The note is for Gerber, S., & Whitaker, R. (2013). Regularization-Free Principal Curve Estimation. 18.

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Invariant Risk Minimization

November 19, 2021 0 Comments

This note is for Arjovsky, M., Bottou, L., Gulrajani, I., & Lopez-Paz, D. (2020). Invariant Risk Minimization. ArXiv:1907.02893 [Cs, Stat].

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Causal Inference by Invariant Prediction

November 19, 2021 0 Comments

This note is for Peters, J., Bühlmann, P., & Meinshausen, N. (2016). Causal inference by using invariant prediction: Identification and confidence intervals. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 78(5), 947–1012.

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Infinite Relational Model

November 18, 2021 (Update: ) 0 Comments

This note is based on Kemp, C., Tenenbaum, J. B., Griffiths, T. L., Yamada, T., & Ueda, N. (n.d.). Learning Systems of Concepts with an Infinite Relational Model. 8. and Saad, F. A., & Mansinghka, V. K. (2021). Hierarchical Infinite Relational Model. ArXiv:2108.07208 [Cs, Stat].

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Multidimensional Monotone Bayesian Additive Regression Tree

November 17, 2021 0 Comments

This note is for Chipman, H. A., George, E. I., McCulloch, R. E., & Shively, T. S. (2021). mBART: Multidimensional Monotone BART. ArXiv:1612.01619 [Stat].

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Debiased ML via NN for GLM

November 16, 2021 0 Comments

This is the note for Chernozhukov, V., Newey, W. K., Quintas-Martinez, V., & Syrgkanis, V. (2021). Automatic Debiased Machine Learning via Neural Nets for Generalized Linear Regression. ArXiv:2104.14737 [Econ, Math, Stat].

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Biclustering on Gene Expression Data

November 10, 2021 0 Comments

The note is based on Padilha, V. A., & Campello, R. J. G. B. (2017). A systematic comparative evaluation of biclustering techniques. BMC Bioinformatics, 18(1), 55.

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Asymptotic Properties of High-Dimensional Random Forests

November 09, 2021 0 Comments

This note is Chi, C.-M., Vossler, P., Fan, Y., & Lv, J. (2021). Asymptotic Properties of High-Dimensional Random Forests. ArXiv:2004.13953 [Math, Stat]..

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Bayesian Leave-One-Out Cross Validation

October 20, 2021 0 Comments

This note is for Magnusson, M., Andersen, M., Jonasson, J., & Vehtari, A. (2019). Bayesian leave-one-out cross-validation for large data. Proceedings of the 36th International Conference on Machine Learning, 4244–4253.

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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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