Tuesday, January 03, 2017

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
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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