I’m a PhD student at the Barcelona Neural Networking Center, Universitat Politècnica de Catalunya (UPC). This is a personal project where I summarize key ideas research papers (mainly from the field of communication networks). Below you can find the full list of research papers and the links to their respective summaries.

If you want to know more about my projects, you can find me in Twitter @PaulAlmasan or in my personal page.

• Spatio-temporal analysis and prediction of cellular traffic in metropolis. Wang, X., Zhou, Z., Xiao, F., Xing, K., Yang, Z., Liu, Y., & Peng, C. IEEE Transactions on Mobile Computing, 2019. Summary

• DeepZip: Lossless Data Compression using Recurrent Neural Networks. M Goyal, K Tatwawadi, S Chandak, I Ochoa. DCC 2019. Summary

• Neural-Enhanced Live Streaming: Improving Live Video Ingest via Online Learning. H Zhu, J Kim, Y Jung, H Yeo, J Ye, D Han. SIGCOMM 2020. Summary

• Network Planning with Deep Reinforcement Learning. H Zhu, V Gupta, SS Ahuja, et. al. SIGCOMM 2021. Summary

• Experience-Driven Congestion Control: When Multi-Path TCP Meets Deep Reinforcement Learning. Z Xu, J Tang, C Yin, et. al. IEEE Journal on Selected Areas in Communications, 2019. Summary

• A Deep Reinforcement Learning Perspective on Internet Congestion Control. N Jay, N Rotman, B Godfrey, et. al. International Conference on Machine Learning, 2019. Summary

• Neural Adaptive Video Streaming with Pensieve. H Mao, R Netravali, M Alizadeh. SIGCOMM 2017. Summary

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• Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization. Q Cappart, T Moisan, LM Rousseau, et. al. ARXIV 2020. Summary

• Interpreting Deep Learning-Based Networking Systems. Z Meng, M Wang, J Bai, M Xu, et. al. SIGCOMM 2020. Summary

• Graph neural networks for scalable radio resource management: Architecture design and theoretical analysis. Y Shen, Y Shi, J Zhang, et. al. IEEE Journal on Selected Areas in Communications 2021. Summary

• Resource management with deep reinforcement learning. H Mao, M Alizadeh, I Menache, S Kandula. HotNets 2016. Summary

• CFR-RL: Traffic Engineering With Reinforcement Learning in SDN. J Zhang, M Ye, Z Guo, CY Yen, et. al. IEEE Journal on Selected Areas in Communications 2020. Summary

• TIDE: Time-relevant deep reinforcement learning for routing optimization. P Sun, Y Hu, J Lan, L Tian, M Chen. Future Generation Computer Systems 2019. Summary

• Neural Packet Classification. E Liang, H Zhu, X Jin, I Stoica. SIGCOMM 2019. Summary

• AuTO: Scaling Deep Reinforcement Learning for Datacenter-Scale Automatic Traffic Optimization. L Chen, J Lingys, K Chen, F Liu. SIGCOMM 2018. Summary

• Combining Deep Reinforcement Learning With Graph Neural Networks for Optimal VNF Placement. P Sun, J Lan, J Li, Z Guo, Y Hu. IEEE Communications Letters 2020. Summary

• Experience-driven Networking: A Deep Reinforcement Learning based Approach. Z Xu, J Tang, J Meng, W Zhang, Y Wang, et. al. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications. Summary