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Gaussian Process Networks

Gaussian Process Networks. Nir Friedman and Iftach Nachman UAI-2K. Abstract. Learning structures of Bayesian networks Evaluating the marginal likelihood of the data given a candidate structure. For continuous networks Gaussians, Gaussian mixtures were used as priors for parameters.

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Gaussian Process Networks

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  1. Erik Jonsson School of Engineering and Computer Science EE/CE 2310 – HON/002 Introduction to Digital Systems http://www.utdallas.edu/~pervin Thursday: Chapters T8,P5 Tuesday 2-28-12 FEARLESS Engineering www.utdallas.edu/~pervin

  2. REVIEW EXAMINATION I

  3. Chapter (T) EightBinary Arithmetic and Arithmetic Circuits Binary Addition Half Adder Full Adder http://www.cise.ufl.edu/~mssz/CompOrg/CDA-arith.html

  4. Quick Introduction to Chapter (T) Nine Flip-Flops and Other Multivibrators

  5. RS Flip-Flop

  6. Clocked RS Flip-Flop

  7. Timing Diagram

  8. D Flip-Flop

  9. JK Flip-Flop

  10. 7476 JK Flip-Flop IC

  11. Quick Introduction to Chapter (P) Five Functions and Stacks

  12. PUSH & POP $sp = Stack Pointer Points to the “top” of the stack (last value inserted) Always full words on stack Grows downward (toward lower addresses) PUSH: sub $sp,$sp,4 sw $reg,0($sp) POP: lw $reg,0($sp) add $sp,$sp,4

  13. Since this is assembler and we know what is happening, we can “cheat”: Three pushes: sub $sp,$sp,12 sw $reg1,8($sp) sw $reg2,4($sp) sw $reg3,0($sp) Three pops: lw $reg3,0($sp) lw $reg2,4($sp) lw $reg1,8($sp) add $sp,$sp,12 Thus we can reference words in the middle of the stack if we desire! This can be used to pass parameters to a function other than in $a0,…,$a3.

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