590Q schedule - Google Drive

1

CSE590q: Reading Seminar in Databases

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Mondays @ 1:30 by zoom
Topic: Embeddings of Structured Data

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4

Date

Topic

Presenter(s)

Paper

Slides

Notes

Slides

5

10/5/2020

Introduction

Alex

Neural Word Embedding as Implicit Matrix Factorization

https://drive.google.com/file/d/1-QJNWwXlgaaKcTwWKkAZj_Vt3bLLiIUN/view?usp=sharing

6

10/12/2020

Introduction (cont'd)

Dan

A Theory of Vector Embeddings of Structured Data, PODS'2020

Martin's slides

7

10/19/2020

TRANSE (KB embedding)

Vlad

Translating embeddings for modeling multi-relational data, NIPS'2013


1	CSE590q: Reading Seminar in Databases
2	Mondays @ 1:30 by zoom Topic: Embeddings of Structured Data
3
4	Date	Topic	Presenter(s)	Paper	Slides	Notes	Slides
5	10/5/2020	Introduction	Alex	Neural Word Embedding as Implicit Matrix Factorization	https://drive.google.com/file/d/1-QJNWwXlgaaKcTwWKkAZj_Vt3bLLiIUN/view?usp=sharing
6	10/12/2020	Introduction (cont'd)	Dan	A Theory of Vector Embeddings of Structured Data, PODS'2020	Martin's slides
7	10/19/2020	TRANSE (KB embedding)	Vlad	Translating embeddings for modeling multi-relational data, NIPS'2013		see also	https://drive.google.com/file/d/1in2XlZU0f-wTyhteZT59CgjMFDh8ajLQ/view?usp=sharing
8	10/26/2020	Survey on graph embeddings	Maureen	Representation learning on graphs: methods and applications, DEBUL'2017		see also the node2vec paper below	https://drive.google.com/file/d/1y8SN2YnBN_Nsp8zDnYF6_3JalbA_rRHd/view?usp=sharing
9	11/2/2020	Termite	Enhao	Termite: a system for tunneling through heterogeneous data			https://docs.google.com/presentation/d/163yZoMrWokhj6lJ6I_x7nTC8exQ4s6mtDgpeGda5UuU/edit?usp=sharing
10	11/9/2020	Application to Database Integration	Dong	Creating Embeddings of Heterogeneous Relational Datasets for Data Integration Tasks, SIGMOD'2020	slides
11	11/16/2020	Application to Fairness	Kyle	Operationalizing Individual Fairness with Pairwise Fair Representations, VLDB'2020
12	11/23/2020	GNN v.s 1-WL	Moe	Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks, AAAI'2019	Christopher's slides
13	11/30/2020	Connection between GNN and Logic	Remy	The Logical Expressiveness of Graph Neural Networks, ICLR'2020
14	12/7/2020	Discussion: lessons learned	Everyone	Meeting notes
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18	Other readings
19		Survey on graph kernels		A survey on graph kernels, 2019
20		Survey on kb embeddings		Knowledge Graph Embedding: A Survey of Approaches and Applications. TKDE'2017
21		Geometry of graphs		The geometry of graphs and some of its algorithmic applications. Combinatorica, 1995
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23		Database applications		Exploiting Latent Information in Relational Databases via Word Embedding, CIDR'2019
24				Using word embedding to enable semantic queries in relational databases, DEEM'2017	First application of embedding to databases
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26		the node2vec paper		node2vec: Scalable feature learning for net- works. KDD'2016
27		RESCAL (KB embedding)		A three-way model for collective learning on multi-relational data, ICML'2011		Perhaps experiment with the tool
28
29				Deep sets	see also other papers by Ravanbakhsh
30				Embeddings of E/R's
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32				Graph Representation Learning (book by Hamilton)
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