Kaichun Mo daerduoCarey

NIPS Notes

Simple Intro by Blei mostly going over review paper of Jordan
Later introduce SVI (Stochastic VI) as a remedy to solve VI tractably with large dataset.
Review the black box inference -assumption free VI- http://www.jmlr.org/proceedings/papers/v33/ranganath14.pdf
Key idea is replacing gradient and the expectation in VI formulation. Since expectation reqiuires exponential family assumption to work replacing expectation and gradient solves this if overall method is stochastic since your samples are unbiased gradient estimates satisfying Robinson-Monroe conditions however the variance is very large and it requires even further tricks

	import numpy as np
	import os
	import h5py
	import json
	from subprocess import call
	import progressbar
	from collections import deque
	import time
	import random
	from colors import colors

	# install trimesh: pip install trimesh
	import trimesh
	# I assume you know numpy
	import numpy as np


	# this func helps export the point cloud as a ply file
	def export_ply(out, v):
	with open(out, 'w') as fout:
	fout.write('ply\n');

	import os
	import sys
	import h5py
	import numpy as np
	from progressbar import ProgressBar
	from commons import check_mkdir

	def load_gt_h5(fn):
	""" Output: pts B x N x 3 float32
	gt_mask B x K x N bool

	# Copyright (C) 2012 Daniel Maturana
	# This file is part of binvox-rw-py.
	#
	# binvox-rw-py is free software: you can redistribute it and/or modify
	# it under the terms of the GNU General Public License as published by
	# the Free Software Foundation, either version 3 of the License, or
	# (at your option) any later version.
	#
	# binvox-rw-py is distributed in the hope that it will be useful,
	# but WITHOUT ANY WARRANTY; without even the implied warranty of

	# Copyright (C) 2012 Daniel Maturana
	# This file is part of binvox-rw-py.
	#
	# binvox-rw-py is free software: you can redistribute it and/or modify
	# it under the terms of the GNU General Public License as published by
	# the Free Software Foundation, either version 3 of the License, or
	# (at your option) any later version.
	#
	# binvox-rw-py is distributed in the hope that it will be useful,
	# but WITHOUT ANY WARRANTY; without even the implied warranty of

	#!/usr/bin/python3
	# -- coding: utf-8 --
	'''
	MOVED FROM /orions4-zfs/projects/rqi/Code/3dcnn/lfd/run_parallel.py
	PLEASE CHECK ORIGINAL FILE FOR UPDATES!
	'''

	import os
	import sys
	import datetime

	# These lists are later turned into target properties on main caffe library target
	set(Caffe_LINKER_LIBS "")
	set(Caffe_INCLUDE_DIRS "")
	set(Caffe_DEFINITIONS "")
	set(Caffe_COMPILE_OPTIONS "")

	# ---[ Boost
	set(BOOST_ROOT /data/kaichun/local)
	find_package(Boost 1.61 REQUIRED COMPONENTS system thread filesystem serialization program_options)
	list(APPEND Caffe_INCLUDE_DIRS PUBLIC ${Boost_INCLUDE_DIRS})

	import json
	import os
	import re
	import urlparse
	import uuid

	import urllib2
	import time

	from http import download_safe