Roy H. Campbell - Department of Computer Science University of Illinois at Urbana-Champaign

Roy H. Campbell
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Contact Details

Name
Roy H. Campbell
Affiliation
Department of Computer Science University of Illinois at Urbana-Champaign
City
Urbana
Country
United States

Pubs By Year

Pub Categories

 
Computer Science - Computer Vision and Pattern Recognition (2)
 
Computer Science - Networking and Internet Architecture (1)
 
Computer Science - Computers and Society (1)
 
Computer Science - Neural and Evolutionary Computing (1)
 
Computer Science - Distributed; Parallel; and Cluster Computing (1)
 
Statistics - Machine Learning (1)
 
Computer Science - Learning (1)

Publications Authored By Roy H. Campbell

Convolutional autoregressive models have recently demonstrated state-of-the-art performance on a number of generation tasks. While fast, parallel training methods have been crucial for their success, generation is typically implemented in a na\"{i}ve fashion where redundant computations are unnecessarily repeated. This results in slow generation, making such models infeasible for production environments. Read More

During the past decade, machine learning has become extremely popular and can be found in many aspects of our every day life. Nowayadays with explosion of data while rapid growth of computation capacity, Distributed Deep Neural Networks (DDNNs) which can improve their performance linearly with more computation resources, have become hot and trending. However, there has not been an in depth study of the performance of these systems, and how well they scale. Read More

Neural networks are usually over-parameterized with significant redundancy in the number of required neurons which results in unnecessary computation and memory usage at inference time. One common approach to address this issue is to prune these big networks by removing extra neurons and parameters while maintaining the accuracy. In this paper, we propose NoiseOut, a fully automated pruning algorithm based on the correlation between activations of neurons in the hidden layers. Read More

2005Sep
Affiliations: 1Department of Computer Science University of Illinois at Urbana-Champaign, 2Department of Computer Science University of Illinois at Urbana-Champaign, 3Department of Computer Science University of Illinois at Urbana-Champaign, 4Department of Computer Science University of Illinois at Urbana-Champaign, 5Department of Computer Science University of Illinois at Urbana-Champaign, 6Department of Computer Science University of Illinois at Urbana-Champaign

Application-level peer-to-peer (P2P) network overlays are an emerging paradigm that facilitates decentralization and flexibility in the scalable deployment of applications such as group communication, content delivery, and data sharing. However the construction of the overlay graph topology optimized for low latency, low link and node stress and lookup performance is still an open problem. We present a design of an overlay constructed on top of a social network and show that it gives a sizable improvement in lookups, average round-trip delay and scalability as opposed to other overlay topologies. Read More