Andrew Clegg is responsible for me finding out that the videos of MMDS 2014: Workshop on Algorithms for Modern Massive Data Sets are out and they are all on the MMDS channel. All the slides are here. I have listed the videos here (and corrected at least one title).

- Leon Bottou's talk (on the same topic he presented in Season 1 of the Paris Machine Learning Meetup)

- Content-based search in 50TB of consumer-produced videos Gerald Friedland
- Influence sampling for generalized linear models Jinzhu Jia
- Communication Cost in Big Data Processing Dan Suciu
- Public Participation in International Security - Open Source Treaty Verification Christopher Stubbs
- Automatic discovery of cell types and microcircuitry from neural connectomics Eric Jonas
- Reducing Communication in Parallel Graph Computations Aydin Buluc
- Spectral algorithms for graph mining and analysis Yiannis Koutis
- Modeling Dynamics of Opinion Formation in Social Networks Sreenivas Gollapudi
- Network community detection Jiashun Jin
- Leverage scores: Sensitivity and an App Ilse Ipsen
- No Free Lunch for Stress Testers: Toward a Normative Theory of Scenario-Based ... Lisa Goldberg
- Large-Scale Numerical Computation Using a Data Flow Engine Matei Zaharia
- IPython: a language-independent framework for computation and data Fernando Perez
- The fall and rise of geometric centralities Sebastiano Vigna
- FAST-PPR: Scaling Personalized PageRank Estimation for Large Graphs Peter Lofgren (Ashish Goel)
- Large Scale Machine Learning at Verizon Ashok Srivastava
- Large-Scale Inference in Time Domain Astrophysics Joshua Bloom
- libSkylark: Sketching-based Accelerated Numerical Linear Algebra and ... - Vikas Sindhwani
- Multi-reference Alignment: Estimating Group Transformations using Semidefinite ... Amit Singer
- Optimal CUR Matrix Decompositions - David Woodruff
- CUR Factorization via Discrete Empirical Interpolation Mark Embree
- Combinatorial optimization and sparse computation for large scale data mining Dorit Hochbaum
- Disentangling sources of risk in massive financial portfolios Jeffrey Bohn
- Large Scale Graph-Parallel Computation for Machine Learning: Applications and Systems, Ankur Dave
- Beyond Locality Sensitive Hashing Alexandr Andoni
- Dimensionality reduction via sparse matrices Jelani Nelson
- Exploring "forgotten" one-shot learning Alek Kolcz
- Myria: Scalable Analytics as a Service Bill Howe
- Optimal Shrinkage of Fast Singular Values Matan Gavish
- Analyzing Big Graphs via Sketching and Streaming Andrew McGregor
- Localized Methods for Diffusions in Large Graphs David Gleich
- Locally-biased and semi-supervised eigenvectors Michael Mahoney
- Distributing Large-scale Recommendation Algorithms: from GPUs to the Cloud Xavier Amatriain
- Counterfactual reasoning and massive data sets Leon Bottou
- Connected Components in MapReduce and Beyond Sergei Vassilvitskii
- Dimension Independent Matrix Square using MapReduce Reza Zadeh

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