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  • What is the fringe in the context of search algorithms?
    In English, the fringe is (also) defined as the outer, marginal, or extreme part of an area, group, or sphere of activity In the context of AI search algorithms, the state (or search) space is usually represented as a graph, where nodes are states and the edges are the connections (or actions) between the corresponding states
  • What are the differences between A* and greedy best-first search?
    What are the differences between the A* algorithm and the greedy best-first search algorithm? Which one should I use? Which algorithm is the better one, and why?
  • What is the difference between tree search and graph search?
    There is always a lot of confusion about this concept, because the naming is misleading, given that both tree and graph searches produce a tree (from which you can derive a path) while exploring the search space, which is usually represented as a graph Differences Firstly, we have to understand that the underlying problem (or search space) is almost always represented as a graph (although the
  • Why is A* optimal if the heuristic function is admissible?
    A heuristic is admissible if it never overestimates the true cost to reach the goal node from n n If a heuristic is consistent, then the heuristic value of n n is never greater than the cost of its successor, n′ n ′, plus the successor's heuristic value Why is A*, using tree or graph searches, optimal, if it uses an admissible heuristic?
  • How does the uniform-cost search algorithm work?
    What is the uniform-cost search (UCS) algorithm? How does it work? I would appreciate seeing a graphical execution of the algorithm How does the frontier evolve in the case of UCS?
  • machine learning - What is a fully convolution network? - Artificial . . .
    Fully convolution networks A fully convolution network (FCN) is a neural network that only performs convolution (and subsampling or upsampling) operations Equivalently, an FCN is a CNN without fully connected layers Convolution neural networks The typical convolution neural network (CNN) is not fully convolutional because it often contains fully connected layers too (which do not perform the
  • Which courses in computer science and logic are relevant to Machine . . .
    optionally, courses in logic, but be aware that this is almost a fringe area in AI now, and essentially irrelevant to a PhD in machine learning The parts you need are usually covered in a broad survey AI course
  • What are alternatives to PCA for time series data?
    I have some data (20 stock price time series) and want to compare different approaches for dimensionality reduction other than PCA (I want to fit only 2 variables in my AR model) I've tried autoen


















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