Recent Posts

• January 11, 2016

  Computational Inference in Logistic Regression

  Logistic regression is one of the most commonly used techniques to analyze binarydata. The classical method to estimate the parameters is through Newton-Rapson. Here I’m demonstratingthe alternative method: Bayesian method (MCMC) and make a compar...

• December 23, 2015

  Linsanity

  Last Saturday night I watched a documentary film called linsanity starred Jeremy Lin who is the model Asian American NBA player.There are too many articles analyzing linsanity phenomenon and I don’t think I’m the right person to talk much about so...

• December 07, 2015

  Learning from Imbalanced Data

  I once gave a short talk during lab’s Machine Learning seminar regarding classification algorithms in imbalanced data. Technically speaking, any data set that exhibits an unequal distribution between its classes can be considered imbalanced.(He H,...

• December 04, 2015

  DREAM Big Data Challenge

  Last summer I and my colleagues in Ontario Institute for Cancer Research teamed up together as Chipmunks, participated in one of DREAM big data challenges: Acute Myeloid Leukemia Outcome Prediction Challenge (AML). Similar to Kaggle, we were asked...

• December 01, 2015

  Adaptive Thresholding

  Motivated by applications in a wide range of fields in signal processing, social science, finance, genetics etc, statistical inference in high dimensional data is a problem of greatinterest. Covariance matrix plays an important role in many fundam...