Joseph Gonzalez

According to our database1, Joseph Gonzalez authored at least 39 papers between 2009 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

2019
Scaling Video Analytics Systems to Large Camera Deployments.
Proceedings of the 20th International Workshop on Mobile Computing Systems and Applications, 2019

Deep Mixture of Experts via Shallow Embedding.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Contextual Multi-Armed Bandits for Link Adaptation in Cellular Networks.
Proceedings of the 2019 Workshop on Network Meets AI & ML, 2019

A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering.
Proceedings of the International Conference on Robotics and Automation, 2019

Serverless Computing: One Step Forward, Two Steps Back.
Proceedings of the CIDR 2019, 2019

2018
Letter from the Special Issue Editor.
IEEE Data Eng. Bull., 2018

Research for practice: prediction-serving systems.
Commun. ACM, 2018

IDK Cascades: Fast Deep Learning by Learning not to Overthink.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

RLlib: Abstractions for Distributed Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

SkipNet: Learning Dynamic Routing in Convolutional Networks.
Proceedings of the Computer Vision - ECCV 2018, 2018

Fast Semantic Segmentation on Video Using Block Motion-Based Feature Interpolation.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017
Opaque: An Oblivious and Encrypted Distributed Analytics Platform.
Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, 2017

Clipper: A Low-Latency Online Prediction Serving System.
Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, 2017

Selecting the best VM across multiple public clouds: a data-driven performance modeling approach.
Proceedings of the 2017 Symposium on Cloud Computing, SoCC 2017, Santa Clara, CA, USA, 2017


Random projection design for scalable implicit smoothing of randomly observed stochastic processes.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Multi-Task Learning for Straggler Avoiding Predictive Job Scheduling.
J. Mach. Learn. Res., 2016

Apache Spark: a unified engine for big data processing.
Commun. ACM, 2016

GraphFrames: an integrated API for mixing graph and relational queries.
Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems, Redwood Shores, CA, USA, June 24, 2016

2015
Faster Jobs in Distributed Data Processing using Multi-Task Learning.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox.
Proceedings of the CIDR 2015, 2015

Efficient data reduction for large-scale genetic mapping.
Proceedings of the 6th ACM Conference on Bioinformatics, 2015

2014
From graphs to tables the design of scalable systems for graph analytics.
Proceedings of the 23rd International World Wide Web Conference, 2014

GraphX: Graph Processing in a Distributed Dataflow Framework.
Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation, 2014

Parallel Double Greedy Submodular Maximization.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

GABB Introduction.
Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014

Efficient and accurate clustering for large-scale genetic mapping.
Proceedings of the 2014 IEEE International Conference on Bioinformatics and Biomedicine, 2014

2013
GraphX: a resilient distributed graph system on Spark.
Proceedings of the First International Workshop on Graph Data Management Experiences and Systems, 2013

Optimistic Concurrency Control for Distributed Unsupervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

MLI: An API for Distributed Machine Learning.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013


2012
Distributed GraphLab: A Framework for Machine Learning in the Cloud.
PVLDB, 2012

Scalable inference in latent variable models.
Proceedings of the Fifth International Conference on Web Search and Web Data Mining, 2012

PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs.
Proceedings of the 10th USENIX Symposium on Operating Systems Design and Implementation, 2012

2011
Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

2010
GraphLab: A New Framework For Parallel Machine Learning.
Proceedings of the UAI 2010, 2010

2009
Residual Splash for Optimally Parallelizing Belief Propagation.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Distributed Parallel Inference on Large Factor Graphs.
Proceedings of the UAI 2009, 2009


  Loading...