The following pages link to Spark (Q35424):
Displaying 41 items.
- The transmission process: a combinatorial stochastic process for the evolution of transmission trees over networks (Q332431) (← links)
- A greedy feature selection algorithm for big data of high dimensionality (Q669273) (← links)
- Scheduling MapReduce jobs on identical and unrelated processors (Q778521) (← links)
- Mining maximal frequent patterns in transactional databases and dynamic data streams: a Spark-based approach (Q781917) (← links)
- A distributed Frank-Wolfe framework for learning low-rank matrices with the trace norm (Q1631800) (← links)
- Large scale implementations for Twitter sentiment classification (Q1662631) (← links)
- A distributed framework for trimmed kernel \(k\)-means clustering (Q1669597) (← links)
- A distributed \(K\)-means segmentation algorithm applied to \textit{Lobesia botrana} recognition (Q1674955) (← links)
- A new distributed alignment-free approach to compare whole proteomes (Q1676313) (← links)
- Adaptive fault detection and diagnosis using parsimonious Gaussian mixture models trained with distributed computing techniques (Q1796632) (← links)
- A survey of challenges for runtime verification from advanced application domains (beyond software) (Q2008293) (← links)
- Efficient scientific workflow scheduling for deadline-constrained parallel tasks in cloud computing environments (Q2023158) (← links)
- Distributed linear regression by averaging (Q2039793) (← links)
- The role of randomness in the broadcast congested clique model (Q2051760) (← links)
- Effective implementations of topic modeling algorithms (Q2064399) (← links)
- High-performance statistical computing in the computing environments of the 2020s (Q2092893) (← links)
- Graph reconstruction in the congested clique (Q2186818) (← links)
- On scheduling coflows (Q2211360) (← links)
- TCEP: transitions in operator placement to adapt to dynamic network environments (Q2229957) (← links)
- Distributed simultaneous inference in generalized linear models via confidence distribution (Q2293540) (← links)
- A three-way cluster ensemble approach for large-scale data (Q2302803) (← links)
- Composable models for online Bayesian analysis of streaming data (Q2329734) (← links)
- GPU-accelerated Gibbs sampling: a case study of the horseshoe probit model (Q2329768) (← links)
- Scaling up Bayesian variational inference using distributed computing clusters (Q2411280) (← links)
- Latent space inference of Internet-scale networks (Q2810894) (← links)
- Vispark: GPU-accelerated distributed visual computing using Spark (Q2830639) (← links)
- A distributed and incremental SVD algorithm for agglomerative data analysis on large networks (Q2834696) (← links)
- (Q4558555) (← links)
- Scaling-up reasoning and advanced analytics on BigData (Q4559832) (← links)
- BAYESIAN ANALYSIS OF BIG DATA IN INSURANCE PREDICTIVE MODELING USING DISTRIBUTED COMPUTING (Q4563820) (← links)
- Computation semantics of the functional scientific workflow language Cuneiform (Q4577807) (← links)
- A programming model and foundation for lineage-based distributed computation (Q4577814) (← links)
- Efficient Ranking and Selection in Parallel Computing Environments (Q4604911) (← links)
- On the optimality of averaging in distributed statistical learning (Q4606521) (← links)
- Scatter matrix concordance as a diagnostic for regressions on subsets of data (Q4970196) (← links)
- Accounting for Factor Variables in Big Data Regression (Q4986359) (← links)
- Brief Announcement: MapReduce Algorithms for Massive Trees (Q5002852) (← links)
- Round Compression for Parallel Matching Algorithms (Q5130844) (← links)
- Optimizing streaming graph partitioning via a heuristic greedy method and caching strategy (Q5858999) (← links)
- Simple, Deterministic, Constant-Round Coloring in Congested Clique and MPC (Q5860478) (← links)
- Multidimensional Array Data Management (Q5886004) (← links)
