Slides: MMDS 2014: Workshop on Algorithms for Modern Massive Data Sets

And you thought you'd have a nice and uneventful end of the week, uh !

well, it looks like all the slides of the MMDS 2014: Workshop on Algorithms for Modern Massive Data Sets have been recently released, they are all here (I just added a link to each authors' website)

Data Analysis and Statistical Data Analysis

• Large Scale Machine Learning at Verizon Ashok Srivastava
• Communication Cost in Big Data Processing Dan Suciu
• Content-based search in 50TB of consumer-produced videos Gerald Friedland
• Myria: Scalable Analytics as a Service Bill Howe
• Computing stationary distribution, locally Devavrat Shah
• Spectral algorithms for graph mining and analysis Yiannis Koutis
• Network community detection Jiashun Jin
• Optimal CUR Matrix Decompositions David Woodruff
• Dimensionality reduction via sparse matrices Jelani Nelson
• Influence sampling for generalized linear models Jinzhu Jia

Industrial and Scientific Applications

• Counterfactual reasoning and massive data sets Leon Bottou
• Connected Components in MapReduce and Beyond Sergei Vassilvitskii
• Distributing Large-scale Recommendation Algorithms: from GPUs to the Cloud Xavier Amatriain
• Disentangling sources of risk in massive financial portfolios Jeffrey Bohn
• Localized Methods for Diffusions in Large Graphs David Gleich
• FAST-PPR: Scaling Personalized PageRank Estimation for Large Graphs Ashish Goel
• Locally-biased and semi-supervised eigenvectors Michael Mahoney
• Optimal Shrinkage of Fast Singular Values Matan Gavish
• Dimension Independent Matrix Square using MapReduce Reza Zadeh

Novel Algorithmic Approaches

• Analyzing Big Graphs via Sketching and Streaming Andrew McGregor
• Large-Scale Inference in Time Domain Astrophysics Joshua Bloom
• Exploring "forgotten" one-shot learning Alek Kolcz
• Modeling Dynamics of Opinion Formation in Social Networks Sreenivas Gollapudi
• Multi-reference Alignment: Estimating Group Transformations using Semidefinite Programming Amit Singer
• IPython: a language-independent framework for computation and data Fernando Perez
• Reducing Communication in Parallel Graph Computations Aydin Buluc
• Large Scale Graph-Parallel Computation for Machine Learning: Applications and Systems Joseph Gonzalez
• CUR Factorization via Discrete Empirical Interpolation Mark Embree
• Leverage scores: Sensitivity and an App Ilse Ipsen
• libSkylark: Sketching-based Accelerated Numerical Linear Algebra and Machine Learning for Distributed-memory Systems Vikas Sindhwani

Novel Matrix and Graph Methods

• Large-Scale Numerical Computation Using a Data Flow Engine Matei Zaharia
• Automatic discovery of cell types and microcircuitry from neural connectomics Eric Jonas
• Beyond Locality Sensitive Hashing Alexandr Andoni
• Combinatorial optimization and sparse computation for large scale data mining Dorit Hochbaum
• Public Participation in International Security - Open Source Treaty Verification Christopher Stubbs
• The Hearts and Minds of Data Science Cecilia Aragon
• The fall and rise of geometric centralities Sebastiano Vigna
• Mixed Regression Constantine Caramanis
• No Free Lunch for Stress Testers: Toward a Normative Theory of Scenario-Based Risk Assessment Lisa Goldberg

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