Skip-Connection Instruction
A Practical Guide to Using Skip Connections Part 1: The “Why” - What Problems Do They Solve? Before adding them, it’s crucial to understand why they are so effective. Solving the Vanishing Gradient Problem: Problem: In very deep networks, the gradient (the signal used for learning) must be backpropagated from the final layer to the initial layers. With each step backward through a layer, the gradient is multiplied by the layer’s weights. If these weights are small (less than 1), the gradient can shrink exponentially, becoming so tiny that the early layers learn extremely slowly or not at all. This is the vanishing gradient problem. Solution: A skip connection creates a direct path for the gradient to flow. It’s like an “information highway” that bypasses several layers. The gradient is passed back through the addition/concatenation operation, providing a direct, uninterrupted path to the earlier layers, keeping the signal strong. Solving the Degradation Problem: ...