yobi byte yobibyte

## proceedings.csv

          
            Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization
            Francis Bach
            https://papers.nips.cc/paper/7286-efficient-algorithms-for-non-convex-isotonic-regression-through-submodular-optimization

            
              Structure-Aware Convolutional Neural Networks
              Jianlong Chang
              https://papers.nips.cc/paper/7287-structure-aware-convolutional-neural-networks

            
              Kalman Normalization: Normalizing Internal Representations Across Network Layers
              Guangrun Wang
              https://papers.nips.cc/paper/7288-kalman-normalization-normalizing-internal-representations-across-network-layers

            
              HOGWILD!-Gibbs can be PanAccurate
              Constantinos Daskalakis
              https://papers.nips.cc/paper/7289-hogwild-gibbs-can-be-panaccurate

            
              Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
              Seonghyeon Nam
              https://papers.nips.cc/paper/7290-text-adaptive-generative-adversarial-networks-manipulating-images-with-natural-language

            
              IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis
              Huaibo Huang
              https

## proceedings.py
import csv
import urllib
from bs4 import BeautifulSoup

url_to_parse = 'https://papers.nips.cc/book/advances-in-neural-information-processing-systems-31-2018'
page = urllib.request.urlopen(url_to_parse)
soup = BeautifulSoup(page, 'html.parser')

with open('proceedings.csv', 'w') as csvfile:
    wr = csv.writer(csvfile, delimiter=',')
Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization	Francis Bach	https://papers.nips.cc/paper/7286-efficient-algorithms-for-non-convex-isotonic-regression-through-submodular-optimization
Structure-Aware Convolutional Neural Networks	Jianlong Chang	https://papers.nips.cc/paper/7287-structure-aware-convolutional-neural-networks
Kalman Normalization: Normalizing Internal Representations Across Network Layers	Guangrun Wang	https://papers.nips.cc/paper/7288-kalman-normalization-normalizing-internal-representations-across-network-layers
HOGWILD!-Gibbs can be PanAccurate	Constantinos Daskalakis	https://papers.nips.cc/paper/7289-hogwild-gibbs-can-be-panaccurate
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language	Seonghyeon Nam	https://papers.nips.cc/paper/7290-text-adaptive-generative-adversarial-networks-manipulating-images-with-natural-language
IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis	Huaibo Huang	https
	import csv
	import urllib
	from bs4 import BeautifulSoup

	url_to_parse = 'https://papers.nips.cc/book/advances-in-neural-information-processing-systems-31-2018'
	page = urllib.request.urlopen(url_to_parse)
	soup = BeautifulSoup(page, 'html.parser')

	with open('proceedings.csv', 'w') as csvfile:
	wr = csv.writer(csvfile, delimiter=',')