Understanding the Efficacy of Over-Parameterization in Neural Networks

Understanding the Efficacy of Over-Parameterization in Neural Networks Understanding the Efficacy of Over-Parameterization in Neural Networks: Mechanisms, Theories, and Practical Implications Introduction Deep neural networks (DNNs) have become the cornerstone of modern artificial intelligence, driving advancements in computer vision, natural language processing, and myriad other domains. A key, albeit counter-intuitive, property of contemporary DNNs is their immense over-parameterization: these models often contain orders of magnitude more parameters than the number of training examples, yet they generalize remarkably well to unseen data. This phenomenon stands in stark contrast to classical statistical learning theory, which posits that models with excessive complexity relative to the available data are prone to overfitting and poor generalization. Intriguingly, empirical evidence shows that increasing the number of parameters in DNNs can lead ...

Advanced Integration Techniques with SageMath: Visual Guides, Riemann Sums, Step-by-Step Examples, and Real-World Applications(Part 5)

📉 Mastering Improper Integrals with SageMath: From ∞ to Real Insight

Improper integrals pop up whenever the limits of integration stretch to infinity or the integrand becomes unbounded. These integrals appear in physics, engineering, probability theory, and even philosophical debates about infinity! 😲

In this post, we'll explore three types of improper integrals using SageMath:

Each example includes:


🔍 Type 1: — Infinity on the Horizon

🔢 Example 1:

Let’s integrate sin(x) from 0 to .

This integral diverges, since the sine function oscillates endlessly.

👉 Your Turn: Replace sin(x) with exp(-x)—does it converge? Why?


🔢 Example 2:

Explore ​

👉 Challenge: Try adjusting the lower limit to x=1. Does divergent still hold?


🔁 Type 2: — Across the Infinite Plane

🔢 Example 3:

🧠 Try This: Change the exponent to 2 or 1.5. When does it still converge?


📊 Visual Comparison Lab:

Consider the oscillatory integral:

As a increases, oscillations tighten.

🔬 Mini-Lab: 

Try plotting sin(a*x^2) instead. What changes? Which function is more "averaged out" over infinity?


⚠️ Type 3:— Discontinuous at a Boundary

🔢 Example 4:

💡 Zoom In:

Try plotting from x=0.01 to x=1. Notice how the curve shoots up near zero.


🔎 Zoomed View of Singularities

🔢 Example:

Here, the function spikes sharply at x=1. Zooming in to the interval (1,1.1) magnifies this behavior.

🎯 Zoom Lab: Try plotting on (1.001, 1.1) to really feel the singularity. What happens as


🌱 The   Threshold

Let’s analyze:

p

Behavior

p≤1

Diverges

p>1

Converges

Why is p=1 the tipping point?

Because the area under 1/x grows without bound—its decay is just too slow. Once p>1, the function shrinks fast enough to trap the area.

🧠 Concept Check: 

Sketch or mentally picture the decay for p = 0.5. Why does it fail to converge?


🎯 Interactive Challenge: Singular but Convergent?

Try this classic:

Despite the singularity at x=0, the integral converges!

🧪 Extra Task: Now try

 What’s the threshold p value here?


🤔 Explore Tan(x) and Cot(x)

Functions like tan(x) and cot(x) have vertical asymptotes at multiples of π. These are great for seeing bounded intervals with internal singularities.

👉 Test Case:

(Hint: vertical asymptote at )

What does SageMath say? Does it warn you? Does it split the integral?


💬 Reflection Prompts

  • Symbolic vs Numeric: 

            SageMath defaults to symbolic integration. If that fails (e.g., due to singularities or non-                        elementary antiderivatives), it tries numeric.

  • Your Role: 

           Try using  after  when symbolic output is too messy or returns unevaluated.

🔜 What’s Next?

Coming soon: Special Functions from Improper Integrals!

🧬 Gamma Function

  • Generalizes the factorial
  • Used in probability and statistics (e.g., waiting times, exponential families)

🧬 Beta Function

  • Appears in Bayesian inference, physics, and combinatorics
  • Defined using a bounded improper integral

💡 Sneak Peek Challenge:

Try computing:

Can SageMath handle it? What does it return?


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