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notes/Eigenproblems.ipynb
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1299
notes/Eigenproblems.ipynb
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notes/Least-Square Fitting.ipynb
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notes/Least-Square Fitting.ipynb
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notes/Quadratic-Gradient-Descent.ipynb
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notes/Quadratic-Gradient-Descent.ipynb
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@@ -586,7 +586,7 @@
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" # approximate gradient from this mini-batch\n",
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" # approximate gradient from this mini-batch\n",
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" ∇f̃ = (2/M)*(Ã'*(Ã*x - b̃))\n",
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" ∇f̃ = (2/M)*(Ã'*(Ã*x - b̃))\n",
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"\n",
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"\n",
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" # Adam update\n",
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" # Yogi update\n",
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" m = β₁*m + (1-β₁)*∇f̃\n",
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" m = β₁*m + (1-β₁)*∇f̃\n",
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" v = @. β₂*v - (1-β₂) * sign(v - ∇f̃^2) * (∇f̃^2)\n",
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" v = @. β₂*v - (1-β₂) * sign(v - ∇f̃^2) * (∇f̃^2)\n",
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" m̂ = m / (1 - β₁^t) # de-bias: normalize by total weights\n",
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" m̂ = m / (1 - β₁^t) # de-bias: normalize by total weights\n",
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