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- Qirong Ho, James Cipar, +6 authors Eric P. Xing
- NIPS
- 2013

We propose a parameter server system for distributed ML, which follows a Stale Synchronous Parallel (SSP) model of computation that maximizes the time computational workers spend doing useful work onâ€¦ (More)

- Eric P. Xing, Qirong Ho, +7 authors Yaoliang Yu
- IEEE Trans. Big Data
- 2015

- Jinhui Yuan, Fei Gao, +6 authors Wei-Ying Ma
- WWW
- 2015

When building large-scale machine learning (ML) programs, such as massive topic models or deep neural networks with up to trillions of parameters and training examples, one usually assumes that suchâ€¦ (More)

- Henggang Cui, James Cipar, +9 authors Eric P. Xing
- USENIX Annual Technical Conference
- 2014

Many modern machine learning (ML) algorithms are iterative, converging on a final solution via many iterations over the input data. This paper explores approaches to exploiting these algorithmsâ€™â€¦ (More)

- Jinliang Wei, Wei Dai, +6 authors Eric P. Xing
- SoCC
- 2015

At the core of Machine Learning (ML) analytics is often an expert-suggested model, whose parameters are refined by iteratively processing a training dataset until convergence. The completion timeâ€¦ (More)

News clustering, categorization and analysis are key components of any news portal. They require algorithms capable of dealing with dynamic data to cluster, interpret and to temporally aggregate newsâ€¦ (More)

- Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth A. Gibson, Eric P. Xing
- AAAI
- 2015

As Machine Learning (ML) applications embrace greater data size and model complexity, practitioners turn to distributed clusters to satisfy the increased computational and memory demands. Effectiveâ€¦ (More)

- Henggang Cui, Alexey Tumanov, +8 authors Eric P. Xing
- SoCC
- 2014

Many large-scale machine learning (ML) applications use iterative algorithms to converge on parameter values that make the chosen model fit the input data. Often, this approach results in the sameâ€¦ (More)

- Amr Ahmed, Qirong Ho, Choon Hui Teo, Jacob Eisenstein, Alexander J. Smola, Eric P. Xing
- AISTATS
- 2011

We use C to denote a generic count of co-occurrences, for example, Ctdk is the number of words in document d at epoch t that are generated from topic k. We might remove a dimension to denoteâ€¦ (More)

- Seunghak Lee, Jin Kyu Kim, Xun Zheng, Qirong Ho, Garth A. Gibson, Eric P. Xing
- NIPS
- 2014

Distributed machine learning has typically been approached from a data parallel perspective, where big data are partitioned to multiple workers and an algorithm is executed concurrently overâ€¦ (More)