Saturday, September 29, 2018
Yuan Zhou, hardness of robust graph isomorphism, Lassere gaps, and asymmetry of random graphs
Given two graphs which are almost isomorphic, is it possible to find a bijection which preserves most of the edges between the two? This is the algorithmic task of Robust Graph Isomorphism, which is a natural approximation variation of the Graph Isomorphism problem. In this talk, we show that no polynomial-time algorithm solves this problem, conditioned on Feige's Random 3XOR Hypothesis. In addition, we show that the Lasserre/SOS SDP hierarchy, the most powerful SDP hierarchy known, fails quite spectacularly on this problem: it needs a linear number of rounds to distinguish two isomorphic graphs from two far-from-isomorphic graphs. Along the way, we venture into the theory of random graphs by showing that a random graph is robustly asymmetric whp, meaning that any permutation which is close to an automorphism is itself close to the identity permutation. Joint work with Ryan O'Donnell, John Wright, and Chenggang Wu.
Wednesday, September 26, 2018
meta analysis using R
Friday, September 21, 2018
Tuesday, September 18, 2018
Justin will lead a discussion on Hinton’s capsule networks, and show us how to setup Lookout cluster using Jupyter notebook.
Justin’s instruction at
Capsule Networks which are an improvement to CNNs and can work with a fraction of the training data because of how it learns.
The conceptual overview: https://openreview.net/pdf?id=HJWLfGWRb
The training method: https://arxiv.org/abs/1710.09829
A less academic explanation: https://medium.com/ai³-theory-practice-business/understanding-hintons-capsule-networks-part-i-intuition-b4b559d1159b
Github collections on Capsule networks
Friday, September 14, 2018