Connecting to Instances Using Advanced Methods | Compute Engine Documentation | Google Cloud この存在を知らなくて, gcp上ではvimで編集してた. Hostnameに外部IPアドレス入れてユーザ名指定して, ~/.sshの中にあるkeyのpathを書けば普通にいけたらし…
KDD 2018 | SpotLight: Detecting Anomalies in Streaming Graphs 読んだ.
タイトル : Neural Relational Inference for Interacting Systems 著者 Thomas N. Kipf (1) Ethan Fetaya (2, 3) Kuan-Chieh Wang (2, 3) Max Welling (1, 4) Richard Zemel (2, 3, 4) University of Amsterdam University of Toronto Vector Institute Can…
http://www.kdd.org/kdd2018/accepted-papers/view/large-scale-learnable-graph-convolutional-networks http://pengcui.thumedialab.com/papers/NE-Hierarchical.pdf https://www.comp.nus.edu.sg/~xiangnan/papers/sigir18-bipartiteNE.pdf
タイトル : Semi-Supervised Classification with Graph Convolutional Networks 著者 Thomas N. Kipf (1) Max Welling (1, 2) 1 University of Amsterdam 2 Canadian Institute for Advanced Research (CIFAR) ICLR2017 Graph系でよく見かける人たち. ↓本論…
色々と思うところがあったので、忘れないように自戒もこめてメモする。 重みの初期値は大事と改めて実感したのでいくつか適当に載せる。 詳しい内容は書かないが、有名どころとその論文だけ載せる。 Keras使ってるわけじゃないけど、これ見たら早いのでこれ…
行列分解 特異値分解 (SVD) Cold Start Isomap
日本語で書いていくことにした。英語で書くのが煩わしさに繋がっていた気がする、そもそも英語で書く意味あんまなかった。 今回の論文↓ タイトル : Why does unsupervised pre-training help deep learning? (2010) http://www.jmlr.org/papers/volume11/erh…
[1409.3215] Sequence to Sequence Learning with Neural Networks github.com The above github is the implementation of seq2seq with Chainer.
http://web.engr.illinois.edu/~cchen156/SID.html CVPR 2018
Training with large minibatches is bad for your health.More importantly, it's bad for your test error.Friends dont let friends use minibatches larger than 32. https://t.co/hxx2rGhIG1 — Yann LeCun (@ylecun) April 26, 2018 [1804.07612] Revis…
[1609.02907] Semi-Supervised Classification with Graph Convolutional Networks ICLR 2017
This is Jure's good slide about graph representaiton learning. This slide helps me understanding of recent embedding learning and do survey about it. It is very useful. Graph Representation Learning from Jure Leskovec www.slideshare.net
[1706.02216] Inductive Representation Learning on Large Graphs (NIPS 2017) This paper's contribution is mainly to generate a function, which extracts a feature represeantation on unseen nodes and graphs. They trained model by a graph, and …
[1710.03059] Learning Graph Representations with Embedding Propagation (NIPS 2017) [1403.6652] DeepWalk: Online Learning of Social Representations (KDD 2014) [1503.03578] LINE: Large-scale Information Network Embedding (WWW 2015) [1402.112…
