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Why didn't champion of the Go game manage to win the last game against AlphaGo, after winning the 4th one?

In the documentary about the match, it is said that after losing the 4th game, AlphaGo came back stronger and started to play in a weird way (not human-like) and it was pretty impossible to be beaten. Why and how did that happen?
Jay Critch
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How can we recognise musical notes in low-resolution or blurry images?

I was looking for an approach to recognise musical notes from photos. I found this repository https://github.com/mpralat/notesRecognizer. However, it doesn't seem good enough. If you look into the bad folder, you can see that just tiny variations of…
Toskan
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How do I improve accuracy and know when to stop training?

I am training a modified VGG-16 to classify crowd density (empty, low, moderate, high). 2 dropout layers were added at the end on the network each one after one of the last 2 FC layers. network settings: training data contain 4381 images…
norahik
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Why Q2 is a more or less independant estimate in Twin Delayed DDPG (TD3)?

Twin Delayed Deep Deterministic (TD3) policy gradient is inspired by both double Q-learning and double DQN. In double Q-learning, I understand that Q1 and Q2 are independent because they are trained on different samples. In double DQN, I understand…
Luke Guye
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Are on-line backpropagation iterations perpendicular to the constraint?

Raul Rojas' Neural Networks A Systematic Introduction, section 8.1.2 relates off-line backpropagation and on-line backpropagation with Gauss-Jacobi and Gauss-Seidel methods for finding the intersection of two lines. What I can't understand is how…
EmmanuelMess
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Why should we study causation in artificial intelligence?

Judea Pearl won the 2011 Turing Award For fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning. He is credited with the invention of Bayesian networks and a framework for…
nbro
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How can we use linear programming to solve an MDP?

Apparently, we can solve an MDP (that is, we can find the optimal policy for a given MDP) using a linear programming formulation. What's the basic idea behind this approach? I think you should start by explaining the basic idea behind a linear…
nbro
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What would be a good comprehensive source about the different forms of classical learning in mammals?

I am looking for a source that really discusses the classic rules of learning in depth. So classical conditioning, operant conditioning, imitation learning... I have found an infinite number of books that supposedly discuss these topics, but have…
Gurkenkönig
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What is a graph neural network?

What is a graph neural network (GNN)? Here are some sub-questions How is a GNN different from a NN? How exactly is a GNN related to graphs? What are the components of a GNN? What are the inputs and outputs of GNNs? How can GNNs be trained? Can we…
nbro
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Which neural network can count the number of objects in an image?

I'm looking for a neural network architecture that excels in counting objects. For example, CNN that can output the number of balls (or any other object) in a given image. I already found articles about crowd counting. I'm looking for articles about…
ron653
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What should the range of the output layer be when performing classification?

I am working on a MLP neural networks, using supervised learning (2 classes and multi-class classification problems). For the hidden layers, I am using $\tanh$ (which produces an output in the range $[-1, 1]$) and for the output layer a softmax…
LVoltz
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Is there a neural network with a varying number of neurons?

Is there some type of neural network that changes the number of neurons while training? Using this idea, the network can increase or decrease the number of neurons when the complexity of the inputs increases or decreases.
Aura Lee
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Why would someone use NEAT over other machine learning algorithms?

Why would someone use a neuroevolution algorithm, such as NEAT, over other machine learning algorithms? What situation would only apply to an algorithm such as NEAT, but no other machine learning algorithm?
Sebastian Dixon
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Is there an alternative to the use of target network?

In the context of Deep Q Network, a target network is usually utilized. The target network is a slow changing network with a changing rate as its hyperparameter. This includes both replacement update every $N$ iterations and slowly update every…
Phizaz
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What is the difference between DQN and AlphaGo Zero?

I have already implemented a relatively simple DQN on Pacman. Now I would like to clearly understand the difference between a DQN and the techniques used by AlphaGo zero/AlphaZero and I couldn't find a place where the features of both approaches are…
FenryrMKIII
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