Videos and Slides: 6th MMDS Workshop on Algorithms for Modern Massive Data Sets

 The 6th MMDS Workshop on Algorithms for Modern Massive Data Sets was held June 21–24, 2016, in Berkeley, CA. It is an event that occurs every two years. Unlike the ML conferences,the KDD conferences or the Simons workshop, this meeting finds its voice in gathering folks around the issue of dealing with very large data. Video recordings of all the talks may be found on their YouTube channel. Download the full MMDS 2016 program here. The links to the videos and slides of most talks are listed below, Previous MMDS meetings with slides and videos can be found with the MMDS tag. enjoy !

 Tue, June 21

		Data Analysis and Statistical Data Analysis	*
08:00	09:45	Breakfast and registration	*
09:45	10:00	Welcome and opening remarks	Organizers
10:00	11:00	Meaningful Visual Exploration of Massive Data	Peter Wang
11:00	11:30	Scalable Collective Inference from Richly Structured Data ►show video	Lise Getoor
11:30	12:00	A Framework for Processing Large Graphs in Shared Memory ►show video	Julian Shun
12:00	02:00	Lunch	*
02:00	02:30	Minimax optimal subsampling for large sample linear regression ►show video	Aarti Singh
02:30	03:00	Randomized Low-Rank Approximation and PCA: Beyond Sketching ►show video	Cameron Musco
03:00	03:30	Restricted Strong Convexity Implies Weak Submodularity ►show video	Alex Dimakis
03:30	04:00	Coffee break	*
04:00	04:30	The Stability Principle for Information Extraction from Data ►show video	Bin Yu
04:30	05:00	New Results in Non-Convex Optimization for Large Scale Machine Learning ►show video	Constantine Caramanis
05:00	05:30	The Union of Intersections Method ►show video	Kristofer Bouchard
05:30	06:00	Head, Torso and Tail - Performance for modeling real data ►show video	Alex Smola
06:00	08:00	Dinner Reception
Wed, June 22		Industrial and Scientific Applications	*
09:00	10:00	New Methods for Designing and Analyzing Large Scale Randomized Experiment ►show video	Jasjeet Sekhon
10:00	10:30	Cooperative Computing for Autonomous Data Centers Storing Social Network Data ►show video	Jonathan Berry
10:30	11:00	Coffee break
11:00	11:30	Is manifold learning for toy data only? ►show video	Marina Meila
11:30	12:00	Exploring Galaxy Evolution through Manifold Learning	Jake VanderPlas
12:00	02:00	Lunch
02:00	02:30	Fast, flexible, and interpretable regression modeling ►show video	Daniela Witten
02:30	03:00	Randomized Composable Core-sets for Distributed Computation	Vahab Mirrokni
03:00	03:30	Local graph clustering algorithms: an optimization perspective ►show video	Kimon Fountoulakis
03:30	04:00	Coffee break
04:00	04:30	Using Principal Component Analysis to Estimate a High Dimensional Factor Model with High-Frequency Data ►show video	Dacheng Xiu
04:30	05:00	Identifying Broad and Narrow Financial Risk Factors with Convex Optimization: Part 1 ►show video	Lisa Goldberg
05:00	05:30	Identifying Broad and Narrow Financial Risk Factors with Convex Optimization: Part 2	Alex Shkolnik
05:30	06:00	Learning about business cycle conditions from four terabytes of data ►show video	Serena Ng
Thu, June 23		Novel Algorithmic Methods	*
09:00	10:00	Top 10 Data Analytics Problems in Science ►show video	Prabhat
10:00	10:30	Low-rank matrix factorizations at scale: Spark for scientific data analytics	Alex Gittens
10:30	11:00	Coffee break
11:00	11:30	Structure & Dynamics from Random Observations ►show video	Abbas Ourmazd
11:30	12:00	Stochastic Integration via Error-Correcting Codes	Dimitris Achlioptas
12:30	02:00	Lunch	*
02:00	02:30	Why Deep Learning Works: Perspectives from Theoretical Chemistry	Charles Martin
02:30	03:00	A theory of multineuronal dimensionality, dynamics and measurement ►show video	Surya Ganguli
03:00	03:30	Sub-sampled Newton Methods: Uniform and Non-Uniform Sampling ►show video	Fred Roosta
03:30	04:00	Coffee break	*
04:00	04:30	In-core computation of geometric centralities with HyperBall: A hundred billion nodes and beyond ►show video	Sebastiano Vigna
04:30	05:00	Higher-order clustering of networks	David Gleich
05:00	05:30	Mining Tools for Large-Scale Networks ►show video	Charalampos Tsourakakis
05:30	06:00	Building Scalable Predictive Modeling Platform for Healthcare Applications ►show video	Jimeng Sun
06:00	08:00	Dinner reception and poster session
Fri, June 24		Novel Matrix and Graph Methods	*
09:00	10:00	Scalable interaction with data: where artificial intelligence meets visualization	Christopher White
10:00	10:30	Ameliorating the Annotation Bottleneck	Christopher Re
10:30	11:00	Coffee break
11:00	11:30	Homophily and transitivity in dynamic network formation	Bryan Graham
11:30	12:00	Systemwide Commonalities in Market Liquidity	Mark Flood
12:30	02:00	Lunch	*
02:00	02:30	Train faster, generalize better: Stability of stochastic gradient descent	Moritz Hardt
02:30	03:00	Extracting governing equations from highly corrupted data	Rachel Ward
03:00	03:30	Nonparametric Network Smoothing	Cosma Shalizi
03:30	04:00	Coffee break	*
04:00	04:30	PCA from noisy linearly reduced measurements ►show video	Amit Singer and Joakim Anden
04:30	05:00	PCA with Model Misspecification ►show video	Robert Anderson
05:00	05:30	Fast Graphlet Decomposition ►show video	Ted Willke and Nesreen Ahmed

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