We have submitted “Modeling Rydberg Gases using Random Sequential Adsorption on Random Graphs.” This is joint work with Daan Rutten.
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Tag: networks
Almost Sure Convergence of Dropout Algorithms for Neural Networks
We have submitted Almost Sure Convergence of Dropout Algorithms for Neural Networks, and it is currently under review. This is joint work between Albert Senen-Cerda and myself.
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Data Communications Networking course
As an assistant professor, one of my new tasks is to teach. Recently, I finished my first teaching session of a Bachelor course for second year students from Electrical Engineering. Specifically, I was tasked with teaching EE2T21 (Part B) – Data Communications Networking.
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Announcing NExTWORKx
We proudly announce NExTWORKx, an intensive research collaboration between Delft University of Technology and Koninklijke KPN N.V. We have formulated a cutting-edge research program that aims to develop first-rate technologies in areas of 5G, blockchain and artificial intelligence. With the collaboration, both parties aspire to further develop the new disruptive technologies that have recently been seeing exponential growth in their application.
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Online network optimization using product-form Markov processes
We have submitted Online Network Optimization Using Product-Form Markov Processes, and it is currently under review. It is joint work between Jaron Sanders, Sem Borst, and Johan van Leeuwaarden.
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Achievable performance in product-form networks
We presented Achievable performance in product-form networks at Allerton 2012, which is joint work between Jaron Sanders, Sem C. Borst and Johan S.H. van Leeuwaarden. You can read it here. Abstract We characterize the achievable range of performance measures in product-form networks where one or more system parameters can be freely set by a network
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Online optimization of product-form networks
We presented Online optimization of product-form networks at Valuetools 2012, which is joint work between Jaron Sanders, Sem C. Borst and Johan S.H. van Leeuwaarden. You can read it here. Abstract We develop an online gradient algorithm for optimizing the performance of product-form networks through online adjustment of control parameters. The use of standard algorithms
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