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Welcome!

This is Lizhong Zheng. I am a professor in EECS at MIT. I work in the area of statistical data analysis. I make this page to keep some of the experiments and demos related to some of our recent research works. The goal is not only to show you the codes, but also some explanations on why we did it in the first place, together with a little math, as well as some pointers to help you to run and make it your own experiments. That got to be fun, ain't it! (This actually helps me to take a break from writing formal research papers, to write something casual instead, which is fun too!) 

The main question we try to answer on this page is: 

Why are neural networks so powerful?

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statistical relationship between the features and the labels that can be represented by this data structure.

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Mathinline
body\sqrt{2.t}
 

 

Code Block
themeConfluence
languagepython
import numpy as np 
import matplotlib.pyplot as plt 

from keras.models import Sequential 
from keras.layers import Dense, Activation 
from keras.optimizers import SGD
 
 X= np.zeros([N, Dx])  
    Labels=np.zeros([N, Cy]) # neural network takes the indicators instead of Y  
      
    for i in range(N):  
        X[i, :]=M[:, Y[i]]  
        Labels[i, Y[i]]=1  
      
    X=X+ np.random.normal(0, .5, X.shape)  

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