Denis Yakovenko yakovenkodenis

Disclaimer 1: Первую которая "про то чего мы достигли" я таки пропустил.

Disclaimer 2: Многие доклады смотрелись и отчёты писались в состоянии алкогольного опьянения.

1. Ben Alpert - What Lies Ahead

Сейчас посмотрел Ben Alpert - What Lies Ahead она про то какие идеи они имеют о дальнейшем развитии. И они делят на UX-идеи и DX-идеи. В UX у них:

##Sequence to Sequence -- Video to Text

Paper : ICCV 2015 PDF

Download Model: S2VT_VGG_RGB_MODEL (333MB)

Project Page

Description

In this gist I would like to describe an idea for GraphQL subscriptions. It was inspired by conversations about subscriptions in the GraphQL slack channel and different GH issues, like #89 and #411.

Conceptual Model

At the moment GraphQL allows 2 types of queries:

query
mutation

Reference implementation also adds the third type: subscription. It does not have any semantics yet, so here I would like to propose one possible semantics interpretation and the reasoning behind it.

	import json
	from random import randint


	class RSA(object):

	def __init__(self):
	self.p, self.q = self.gen_p_q()
	self.N = self.p * self.q
	self.phi = self.euler_function(self.p, self.q)

	import bitarray
	import itertools
	from collections import deque


	class DES(object):

	_initial_permutation = [
	58, 50, 42, 34, 26, 18, 10, 2,
	60, 52, 44, 36, 28, 20, 12, 4,

	import binascii
	import itertools


	def xor_strings(a, b):
	return ''.join(
	[chr(ord(x) ^ ord(y)) for x, y in zip(a, itertools.cycle(b))])


	def xor_hex_strings(a, b):

	import numpy as np


	def cipher(text, alphabet='abcdefghijklmnopqrstuvwxyz', key=0):
	result = ""
	alphabet = alphabet.lower()
	n = len(alphabet)
	for char in text:
	if char.isalpha():
	new_char = alphabet[(alphabet.find(char.lower()) + key) % n]

	SELECT blocked_locks.pid AS blocked_pid,
	blocked_activity.usename AS blocked_user,
	now() - blocked_activity.query_start
	AS blocked_duration,
	blocking_locks.pid AS blocking_pid,
	blocking_activity.usename AS blocking_user,
	now() - blocking_activity.query_start
	AS blocking_duration,
	blocked_activity.query AS blocked_statement,
	blocking_activity.query AS blocking_statement

	# The network is used for the video description experiments in [1].
	# Please consider citing [1] if you use this example in your work.
	#
	# [1] S. Venugopalan, H. Xu, J. Donahue, M. Rohrbach, R. Mooney, K.Saenko.
	# "Translating Videos to Natural Language using Deep Recurrrent Neural
	# Networks." NAACL-HLT 2015.

	name: "mean_fc7_to_lstm"
	layer {
	name: "data"

	quicksort :: (Ord a) => [a] -> [a]
	quicksort [] = []
	quicksort (x:xs) =
	let smallerSorted = quicksort (filter (<=x) xs)
	biggerSorted = quicksort (filter (>x) xs)
	in smallerSorted ++ [x] ++ biggerSorted