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https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/mltdnn.pdf
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# Paper-ResNet
Deep Residual Learning for Image RecognitionProblem Deep networks are more difficult to train [vanishing/exploding gradients problem], rethinking deep representation is really importa…
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Hi,
I found the list missed some recent papers:
>[Multimodal Integration] [2022 Nature Biotechnology] Multi-omics single-cell data integration and regulatory inference with graph-linked embedding
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Hi, I appreciate your work.
I would be happy if you answer my questions.
1) What is the advantage of DINER in learning 2D images, when the model size (hash table + MLP) leads to only little comp…
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Motif search for heterogeneous networks - especially temporal heterogeneous networks - has fundamental scalability challenges. [Neural Subgraph Matching](https://arxiv.org/abs/2007.03092) proposes a t…
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1996 fantasies: [The World-Wide Web as a Super-Brain: from metaphor to model](https://web.archive.org/web/20160304113729/http://pespmc1.vub.ac.be/papers/WWW-Super-Brain.pdf) in: Cybernetics and System…
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Assignment 2 aims to find misinformation on social network, i.e., identify profiles that
are mistakenly recorded as human/non-human profiles
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## Extend Matrix Class to Support Multiple Channels in Image Data
### Background
Our current implementation of the `Matrix` class in the machine learning library is limited to handling image data …
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Introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction; formulation of learning problems; representation, over-fitting, generalizatio…
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there is interesting literature from psy/cognitive science how system 2 might work. it's not describing thorough cognitive architectures, but is relevant nonetheless. I'll grab some and drop them here…