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Titlebook: Representation Discovery using Harmonic Analysis; Sridhar Mahadevan Book 2008 Springer Nature Switzerland AG 2008

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樓主: frustrate
11#
發(fā)表于 2025-3-23 12:40:23 | 只看該作者
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發(fā)表于 2025-3-23 15:31:40 | 只看該作者
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發(fā)表于 2025-3-23 21:47:57 | 只看該作者
Multiscale Bases on Graphs,ocalized in frequency, but their support is .. Consequently, Fourier bases are relatively poor at approximating piecewise-smooth functions with local discontinuities. Fourier analysis also does not reveal multiscale regularities. These limitations of Fourier analysis have only recently been overcome
14#
發(fā)表于 2025-3-23 22:19:36 | 只看該作者
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發(fā)表于 2025-3-24 05:33:58 | 只看該作者
Case Study: State-Space Planning,79]. Markov decision processes [98] have emerged as the standard mathematical framework to model sequential decision-making in a variety of areas, ranging from game-playing [116], manufacturing [33], robotics [77,89], and scheduling [127]. Solving a Markov decision process requires computing and app
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發(fā)表于 2025-3-24 06:48:24 | 只看該作者
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發(fā)表于 2025-3-24 13:54:58 | 只看該作者
Case Study: Natural Language,l (IR) from large document corpora [83]. In this chapter, we describe the application of representation discovery to IR and learning from text. Specifically, we describe a new . approach to the problem of learning hierarchical topic models from a given corpora of text documents. We begin with a clas
18#
發(fā)表于 2025-3-24 15:28:57 | 只看該作者
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發(fā)表于 2025-3-24 19:56:45 | 只看該作者
Fourier Bases on Graphs, In the analysis phase, linear functionals provide “measurements” of a given function, and in the synthesis phase, these measurements are then combined with the dual bases to reconstitute the original function.
20#
發(fā)表于 2025-3-25 00:47:35 | 只看該作者
1939-4608 n intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific b
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