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Information Theory

Information Theory. Entropy: Conditional Entropy: Mutual Information:. Optimal Sensor Parameter Selection. MMI: Maximum Mutual Information. Example: 12 Coin Problem. Problem. Need to learn: Need to solve:. Observation Model. Can be learnt over many experiments

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Information Theory

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Presentation Transcript

  1. Information Theory • Entropy: • Conditional Entropy: • Mutual Information:

  2. Optimal Sensor Parameter Selection • MMI: Maximum Mutual Information

  3. Example: 12 Coin Problem

  4. Problem • Need to learn: • Need to solve:

  5. Observation Model • Can be learnt over many experiments • Or, modelled by recognition system

  6. Solve argmax problem • Integral difficult to compute: • Discretise • Or, use Monte Carlo methods to estimate • Even if we can compute the MI, we also need to maximise. • Local maxima possible

  7. Experimental Results MI Max MI

  8. Experimental Results

  9. Experimental Results

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