Monthly Archives: February 2012
Cutting Your Losses: Loss Functions & the Sum of Squares Loss
The material for this post has been migrated to my GitHub pages site. See you there!
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Algorithms Classification Data Preprocessing Density Estimation Derivations Feature Learning fMRI Gradient Descent LaTeX Machine Learning MATLAB Maximum Likelihood MCMC Neural Networks Neuroscience Optimization Proofs Regression Sampling Sampling Methods Simulations Statistics Theory Tips & Tricks Uncategorized-
Recent Posts
- The OG Clever Machine Has Moved
- Derivation: Maximum Likelihood for Boltzmann Machines
- A Gentle Introduction to Artificial Neural Networks
- Derivation: Derivatives for Common Neural Network Activation Functions
- Derivation: Error Backpropagation & Gradient Descent for Neural Networks
- Model Selection: Underfitting, Overfitting, and the Bias-Variance Tradeoff
- Supplemental Proof 1
- The Statistical Whitening Transform
- Covariance Matrices and Data Distributions
- fMRI In Neuroscience: Efficiency of Event-related Experiment Designs
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