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- Aapo Kyrola, Guy E. Blelloch, Carlos Guestrin
- OSDI
- 2012

Current systems for graph computation require a distributed computing cluster to handle very large real-world problems, such as analysis on social networks or the web graph. While distributedâ€¦ (More)

Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insufficiently expressiveâ€¦ (More)

- Priya Goyal, Piotr DollÃ¡r, +6 authors Kaiming He
- ArXiv
- 2017

Deep learning thrives with large neural networks and large datasets. However, larger networks and larger datasets result in longer training times that impede research and development progress.â€¦ (More)

- Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Carlos Guestrin
- ICML
- 2011

We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds for Shotgun whichâ€¦ (More)

While high-level data parallel frameworks, like MapReduce, simplify the design and implementation of large-scale data processing systems, they do not naturally or efficiently support many importantâ€¦ (More)

- Raymond Cheng, Ji Hong, +7 authors Enhong Chen
- EuroSys
- 2012

Kineograph is a distributed system that takes a stream of incoming data to construct a continuously changing graph, which captures the relationships that exist in the data feed. As a computingâ€¦ (More)

- Julian Shun, Guy E. Blelloch, +4 authors Kanat Tangwongsan
- SPAA
- 2012

This announcement describes the problem based benchmark suite (PBBS). PBBS is a set of benchmarks designed for comparing parallel algorithmic approaches, parallel programming language styles, andâ€¦ (More)

- Aapo Kyrola
- RecSys
- 2013

Random walks on graphs are a staple of many ranking and recommendation algorithms. Simulating random walks on a graph which fits in memory is trivial, but massive graphs pose a problem: the latencyâ€¦ (More)

- Aapo Kyrola, Carlos Guestrin
- ArXiv
- 2014

We propose a new data structure, Parallel Adjacency Lists (PAL), for efficiently managing graphs with billions of edges on disk. The PAL structure is based on the graph storage model of GraphChiâ€¦ (More)

- Aapo Kyrola
- 2014

Current systems for graph computation require a distributed computing cluster to handle very large real-world problems, such as analysis on social networks or the web graph. While distributedâ€¦ (More)