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ORCIDMung Chiang
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- affiliation: Purdue University, USA
- affiliation (former): Princeton University, USA
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2020 – today
- 2024
[j122]Dong-Jun Han
, Seyyedali Hosseinalipour, David J. Love, Mung Chiang, Christopher G. Brinton:
Cooperative Federated Learning Over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading. IEEE J. Sel. Areas Commun. 42(5): 1080-1096 (2024)- [j121]Dong-Jun Han, Wenzhi Fang, Seyyedali Hosseinalipour, Mung Chiang, Christopher G. Brinton:
Orchestrating Federated Learning in Space-Air- Ground Integrated Networks: Adaptive Data Offloading and Seamless Handover. IEEE J. Sel. Areas Commun. 42(12): 3505-3520 (2024) - [j120]Zhan-Lun Chang, Seyyedali Hosseinalipour, Mung Chiang, Christopher G. Brinton:
Asynchronous Multi-Model Dynamic Federated Learning Over Wireless Networks: Theory, Modeling, and Optimization. IEEE Trans. Cogn. Commun. Netw. 10(5): 1989-2004 (2024) - [j119]Hyoyoung Lim, Jinsung Lee, Jongyun Lee, Sandesh Dhawaskar Sathyanarayana, Junseon Kim, Anh Nguyen, Kwang Taik Kim, Youngbin Im, Mung Chiang, Dirk Grunwald, Kyunghan Lee, Sangtae Ha:
An Empirical Study of 5G: Effect of Edge on Transport Protocol and Application Performance. IEEE Trans. Mob. Comput. 23(4): 3172-3186 (2024) - [j118]Dong-Jun Han, Do-Yeon Kim, Minseok Choi, David Nickel, Jaekyun Moon, Mung Chiang, Christopher G. Brinton:
Federated Split Learning With Joint Personalization-Generalization for Inference-Stage Optimization in Wireless Edge Networks. IEEE Trans. Mob. Comput. 23(6): 7048-7065 (2024) - [j117]Seyyedali Hosseinalipour, Su Wang, Nicolò Michelusi, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Mung Chiang:
Parallel Successive Learning for Dynamic Distributed Model Training Over Heterogeneous Wireless Networks. IEEE/ACM Trans. Netw. 32(1): 222-237 (2024) - [j116]Su Wang, Roberto Morabito, Seyyedali Hosseinalipour, Mung Chiang, Christopher G. Brinton:
Device Sampling and Resource Optimization for Federated Learning in Cooperative Edge Networks. IEEE/ACM Trans. Netw. 32(5): 4365-4381 (2024) - [c218]Dong-Jun Han, Seyyedali Hosseinalipour, David J. Love, Mung Chiang, Christopher G. Brinton:
Cooperative Federated Learning over Hybrid Terrestrial and Non-Terrestrial Networks. ICC 2024: 2992-2997 - [i69]Dong-Jun Han, Wenzhi Fang, Seyyedali Hosseinalipour, Mung Chiang, Christopher G. Brinton:
Orchestrating Federated Learning in Space-Air-Ground Integrated Networks: Adaptive Data Offloading and Seamless Handover. CoRR abs/2408.09522 (2024) - [i68]Xiang Li, Mustafa Abdallah, Yuan-Yao Lou, Mung Chiang, Kwang Taik Kim, Saurabh Bagchi:
Dynamic DAG-Application Scheduling for Multi-Tier Edge Computing in Heterogeneous Networks. CoRR abs/2409.10839 (2024) - [i67]Yuan-Yao Lou, Jonathan C. Spencer, Kwang Taik Kim, Mung Chiang:
Utilizing Priors in Sampling-based Cost Minimization. CoRR abs/2409.19834 (2024) - [i66]Yuan-Yao Lou, Jonathan C. Spencer, Kwang Taik Kim, Mung Chiang:
E-MPC: Edge-assisted Model Predictive Control. CoRR abs/2410.00695 (2024) - 2023
- [j115]Su Wang, Seyyedali Hosseinalipour, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Weifeng Su, Mung Chiang:
Toward Cooperative Federated Learning Over Heterogeneous Edge/Fog Networks. IEEE Commun. Mag. 61(12): 54-60 (2023) - [j114]Eric Ruzomberka, Kwang Taik Kim, Arnob Ghosh, David J. Love, Mung Chiang:
A Novel Framework for Cost Constrained Network Sharing. IEEE Trans. Mob. Comput. 22(8): 4422-4438 (2023) - [j113]Su Wang, Seyyedali Hosseinalipour, Maria Gorlatova, Christopher G. Brinton, Mung Chiang:
UAV-Assisted Online Machine Learning Over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach. IEEE Trans. Netw. Serv. Manag. 20(2): 1847-1865 (2023) - [j112]Bhargav Ganguly, Seyyedali Hosseinalipour, Kwang Taik Kim, Christopher G. Brinton, Vaneet Aggarwal, David J. Love, Mung Chiang:
Multi-Edge Server-Assisted Dynamic Federated Learning With an Optimized Floating Aggregation Point. IEEE/ACM Trans. Netw. 31(6): 2682-2697 (2023) - [c217]Roberto Morabito, Mallik Tatipamula, Sasu Tarkoma, Mung Chiang:
Edge AI Inference in Heterogeneous Constrained Computing: Feasibility and Opportunities. CAMAD 2023: 225-232 - [c216]Rohit Parasnis, Seyyedali Hosseinalipour, Yun-Wei Chu, Mung Chiang, Christopher G. Brinton:
Connectivity-Aware Semi-Decentralized Federated Learning over Time-Varying D2D Networks. MobiHoc 2023: 31-40 - [i65]Xiang Li, Mustafa Abdallah, Shikhar Suryavansh, Mung Chiang, Saurabh Bagchi:
DAG-based Task Orchestration for Edge Computing. CoRR abs/2301.09278 (2023) - [i64]Su Wang, Seyyedali Hosseinalipour, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Weifeng Su, Mung Chiang:
Towards Cooperative Federated Learning over Heterogeneous Edge/Fog Networks. CoRR abs/2303.08361 (2023) - [i63]Rohit Parasnis, Seyyedali Hosseinalipour, Yun-Wei Chu, Christopher G. Brinton, Mung Chiang:
Connectivity-Aware Semi-Decentralized Federated Learning over Time-Varying D2D Networks. CoRR abs/2303.08988 (2023) - [i62]Zhan-Lun Chang, Seyyedali Hosseinalipour, Mung Chiang, Christopher G. Brinton:
Asynchronous Multi-Model Federated Learning over Wireless Networks: Theory, Modeling, and Optimization. CoRR abs/2305.13503 (2023) - [i61]Roberto Morabito, Mallik Tatipamula, Sasu Tarkoma, Mung Chiang:
Edge AI Inference in Heterogeneous Constrained Computing: Feasibility and Opportunities. CoRR abs/2311.03375 (2023) - [i60]Su Wang, Roberto Morabito, Seyyedali Hosseinalipour, Mung Chiang, Christopher G. Brinton:
Device Sampling and Resource Optimization for Federated Learning in Cooperative Edge Networks. CoRR abs/2311.04350 (2023) - [i59]Dong-Jun Han, Seyyedali Hosseinalipour, David J. Love, Mung Chiang, Christopher G. Brinton:
Cooperative Federated Learning over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading. CoRR abs/2312.15361 (2023) - 2022
- [j111]Jonathan C. Spencer, Sanjiban Choudhury, Matthew Barnes, Matthew Schmittle, Mung Chiang, Peter J. Ramadge, Siddhartha S. Srinivasa:
Expert Intervention Learning. Auton. Robots 46(1): 99-113 (2022) - [c215]Satyavrat Wagle, Seyyedali Hosseinalipour, Naji Khosravan, Mung Chiang, Christopher G. Brinton:
Embedding Alignment for Unsupervised Federated Learning via Smart Data Exchange. GLOBECOM 2022: 492-497 - [c214]Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal:
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? ICLR 2022 - [c213]Xiang Li, Mustafa Abdallah, Shikhar Suryavansh, Mung Chiang, Kwang Taik Kim, Saurabh Bagchi:
DAG-based Task Orchestration for Edge Computing. SRDS 2022: 23-34 - [i58]Seyyedali Hosseinalipour, Su Wang, Nicolò Michelusi, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Mung Chiang:
Parallel Successive Learning for Dynamic Distributed Model Training over Heterogeneous Wireless Networks. CoRR abs/2202.02947 (2022) - [i57]Hung T. Nguyen, H. Vincent Poor, Mung Chiang:
Contextual Model Aggregation for Fast and Robust Federated Learning in Edge Computing. CoRR abs/2203.12738 (2022) - [i56]Bhargav Ganguly, Seyyedali Hosseinalipour, Kwang Taik Kim, Christopher G. Brinton, Vaneet Aggarwal, David J. Love, Mung Chiang:
Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Point. CoRR abs/2203.13950 (2022) - [i55]Satyavrat Wagle, Seyyedali Hosseinalipour, Naji Khosravan, Mung Chiang, Christopher G. Brinton:
Embedding Alignment for Unsupervised Federated Learning via Smart Data Exchange. CoRR abs/2208.02856 (2022) - [i54]Hung T. Nguyen, Steven Bottone, Kwang Taik Kim, Mung Chiang, H. Vincent Poor:
Interference Cancellation GAN Framework for Dynamic Channels. CoRR abs/2208.08019 (2022) - 2021
- [j110]Yixin Sun, Maria Apostolaki, Henry Birge-Lee, Laurent Vanbever, Jennifer Rexford, Mung Chiang, Prateek Mittal:
Securing internet applications from routing attacks. Commun. ACM 64(6): 86-96 (2021) - [j109]Hung T. Nguyen, Vikash Sehwag, Seyyedali Hosseinalipour, Christopher G. Brinton, Mung Chiang, H. Vincent Poor:
Fast-Convergent Federated Learning. IEEE J. Sel. Areas Commun. 39(1): 201-218 (2021) - [c212]Hung T. Nguyen, Steven Bottone, Kwang Taik Kim, Mung Chiang, H. Vincent Poor:
Adversarial Neural Networks for Error Correcting Codes. GLOBECOM 2021: 1-6 - [c211]Hung T. Nguyen, Roberto Morabito, Kwang Taik Kim, Mung Chiang:
On-the-fly Resource-Aware Model Aggregation for Federated Learning in Heterogeneous Edge. GLOBECOM 2021: 1-6 - [c210]Roberto Morabito, Mung Chiang:
Demo: Discover, Provision, and Orchestration of Machine Learning Inference Services in Heterogeneous Edge. ICDCS 2021: 1116-1119 - [c209]Vikash Sehwag, Mung Chiang, Prateek Mittal:
SSD: A Unified Framework for Self-Supervised Outlier Detection. ICLR 2021 - [c208]Su Wang, Mengyuan Lee, Seyyedali Hosseinalipour, Roberto Morabito, Mung Chiang, Christopher G. Brinton:
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation. INFOCOM 2021: 1-10 - [c207]Yihan Zou, Kwang Taik Kim, Xiaojun Lin, Mung Chiang:
Minimizing Age-of-Information in Heterogeneous Multi-Channel Systems: A New Partial-Index Approach. MobiHoc 2021: 11-20 - [c206]Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein:
RobustBench: a standardized adversarial robustness benchmark. NeurIPS Datasets and Benchmarks 2021 - [i53]Su Wang, Mengyuan Lee, Seyyedali Hosseinalipour, Roberto Morabito, Mung Chiang, Christopher G. Brinton:
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation. CoRR abs/2101.00787 (2021) - [i52]Vikash Sehwag, Mung Chiang, Prateek Mittal:
SSD: A Unified Framework for Self-Supervised Outlier Detection. CoRR abs/2103.12051 (2021) - [i51]Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal:
Improving Adversarial Robustness Using Proxy Distributions. CoRR abs/2104.09425 (2021) - [i50]Su Wang, Seyyedali Hosseinalipour, Maria Gorlatova, Christopher G. Brinton, Mung Chiang:
UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach. CoRR abs/2106.15734 (2021) - [i49]Hung T. Nguyen, Roberto Morabito, Kwang Taik Kim, Mung Chiang:
On-the-fly Resource-Aware Model Aggregation for Federated Learning in Heterogeneous Edge. CoRR abs/2112.11485 (2021) - [i48]Hung T. Nguyen, Steven Bottone, Kwang Taik Kim, Mung Chiang, H. Vincent Poor:
Adversarial Neural Networks for Error Correcting Codes. CoRR abs/2112.11491 (2021) - 2020
- [j108]Seyyedali Hosseinalipour, Christopher G. Brinton, Vaneet Aggarwal, Huaiyu Dai, Mung Chiang:
From Federated to Fog Learning: Distributed Machine Learning over Heterogeneous Wireless Networks. IEEE Commun. Mag. 58(12): 41-47 (2020) - [j107]Maria Gorlatova, Hazer Inaltekin, Mung Chiang:
Characterizing task completion latencies in multi-point multi-quality fog computing systems. Comput. Networks 181: 107526 (2020) - [j106]Mung Chiang, Rachid El Azouzi, Lin Gao, Jianwei Huang, Carlee Joe-Wong, Soumya Sen:
Guest Editorial: Smart Data Pricing for Next-Generation Networks. IEEE J. Sel. Areas Commun. 38(4): 641-644 (2020) - [c205]Yixin Sun, Kangkook Jee, Suphannee Sivakorn, Zhichun Li, Cristian Lumezanu, Lauri Korts-Pärn, Zhenyu Wu, Junghwan Rhee, Chung Hwan Kim, Mung Chiang, Prateek Mittal:
Detecting Malware Injection with Program-DNS Behavior. EuroS&P 2020: 552-568 - [c204]Nawanol Theera-Ampornpunt, Shikhar Suryavansh, Sameer Manchanda, Rajesh Krishna Panta, Kaustubh Joshi, Mostafa H. Ammar, Mung Chiang, Saurabh Bagchi:
AppStreamer: Reducing Storage Requirements of Mobile Games through Predictive Streaming. EWSN 2020: 37-48 - [c203]Kwang Taik Kim, Carlee Joe-Wong, Mung Chiang:
Coded Edge Computing. INFOCOM 2020: 237-246 - [c202]Yihan Zou, Kwang Taik Kim, Xiaojun Lin, Mung Chiang, Zhi Ding, Risto Wichman, Jyri Hämäläinen:
Low-Overhead Joint Beam-Selection and Random-Access Schemes for Massive Internet-of-Things with Non-Uniform Channel and Load. INFOCOM 2020: 2126-2135 - [c201]Jonathan C. Spencer, Sanjiban Choudhury, Matt Barnes, Matthew Schmittle, Mung Chiang, Peter J. Ramadge, Siddhartha S. Srinivasa:
Learning from Interventions: Human-robot interaction as both explicit and implicit feedback. Robotics: Science and Systems 2020 - [i47]Somali Chaterji, Parinaz Naghizadeh, Muhammad Ashraful Alam, Saurabh Bagchi, Mung Chiang, David Corman, Brian J. Henz, Suman Jana, Na Li, Shaoshuai Mou, Meeko Oishi, Chunyi Peng, Tiark Rompf, Ashutosh Sabharwal, Shreyas Sundaram, James Weimer, Jennifer Weller:
Resilient Cyberphysical Systems and their Application Drivers: A Technology Roadmap. CoRR abs/2001.00090 (2020) - [i46]Nawanol Theera-Ampornpunt, Shikhar Suryavansh, Sameer Manchanda, Rajesh K. Panta, Kaustubh Joshi, Mostafa H. Ammar, Mung Chiang, Saurabh Bagchi:
AppStreamer: Reducing Storage Requirements of Mobile Games through Predictive Streaming. CoRR abs/2001.08169 (2020) - [i45]Yixin Sun, Maria Apostolaki, Henry Birge-Lee, Laurent Vanbever, Jennifer Rexford, Mung Chiang, Prateek Mittal:
Securing Internet Applications from Routing Attacks. CoRR abs/2004.09063 (2020) - [i44]Seyyedali Hosseinalipour, Christopher G. Brinton, Vaneet Aggarwal, Huaiyu Dai, Mung Chiang:
From Federated Learning to Fog Learning: Towards Large-Scale Distributed Machine Learning in Heterogeneous Wireless Networks. CoRR abs/2006.03594 (2020) - [i43]Vikash Sehwag, Rajvardhan Oak, Mung Chiang, Prateek Mittal:
Time for a Background Check! Uncovering the impact of Background Features on Deep Neural Networks. CoRR abs/2006.14077 (2020) - [i42]Hung T. Nguyen, Vikash Sehwag, Seyyedali Hosseinalipour, Christopher G. Brinton, Mung Chiang, H. Vincent Poor:
Fast-Convergent Federated Learning. CoRR abs/2007.13137 (2020) - [i41]Parinaz Naghizadeh, Carlee Joe-Wong, Mung Chiang:
Paid Prioritization with Content Competition. CoRR abs/2007.14574 (2020) - [i40]Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein:
RobustBench: a standardized adversarial robustness benchmark. CoRR abs/2010.09670 (2020) - [i39]Shikhar Suryavansh, Chandan Bothra, Kwang Taik Kim, Mung Chiang, Chunyi Peng, Saurabh Bagchi:
I-BOT: Interference-Based Orchestration of Tasks for Dynamic Unmanaged Edge Computing. CoRR abs/2011.05925 (2020)
2010 – 2019
- 2019
- [j105]Soumya Sen, Carlee Joe-Wong, Sangtae Ha, Mung Chiang:
Time-Dependent Pricing for Multimedia Data Traffic: Analysis, Systems, and Trials. IEEE J. Sel. Areas Commun. 37(7): 1504-1517 (2019) - [j104]Weiyu Chen, Christopher G. Brinton, Da Cao, Amanda Mason-Singh, Charlton Lu, Mung Chiang:
Early Detection Prediction of Learning Outcomes in Online Short-Courses via Learning Behaviors. IEEE Trans. Learn. Technol. 12(1): 44-58 (2019) - [c200]Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal:
Analyzing the Robustness of Open-World Machine Learning. AISec@CCS 2019: 105-116 - [c199]Yihan Zou, Kwang Taik Kim, Zhi Ding, Risto Wichman, Jyri Hämäläinen, Xiaojun Lin, Mung Chiang:
Low-Overhead Multi-Antenna-Enabled Random Access for Machine-Type Communications with Low Mobility. GLOBECOM 2019: 1-6 - [c198]Yuwei Tu, Christopher G. Brinton, Andrew S. Lan, Mung Chiang:
Adaptive Remediation with Multi-modal Content. HCI (32) 2019: 455-468 - [c197]Patrick Hansen, Richard Junior Bustamante, Tsung-Yen Yang, Elizabeth Tenorio, Christopher G. Brinton, Mung Chiang, Andrew S. Lan:
Predicting the Timing and Quality of Responses in Online Discussion Forums. ICDCS 2019: 1931-1940 - [c196]Parinaz Naghizadeh, Maria Gorlatova, Andrew S. Lan, Mung Chiang:
Hurts to Be Too Early: Benefits and Drawbacks of Communication in Multi-Agent Learning. INFOCOM 2019: 622-630 - [c195]Pranvera Kortoçi, Liang Zheng, Carlee Joe-Wong, Mario Di Francesco, Mung Chiang:
Fog-based Data Offloading in Urban IoT Scenarios. INFOCOM 2019: 784-792 - [c194]Surin Ahn, Maria Gorlatova, Parinaz Naghizadeh, Mung Chiang:
Personalized augmented reality via fog-based imitation learning. IoT-Fog@IoTDI 2019: 11-15 - [c193]Shikhar Suryavansh, Chandan Bothra, Mung Chiang, Chunyi Peng, Saurabh Bagchi:
Tango of edge and cloud execution for reliability. MECC@Middleware 2019: 10-15 - [i38]Vikash Sehwag, Arjun Nitin Bhagoji, Liwei Song, Chawin Sitawarin, Daniel Cullina, Mung Chiang, Prateek Mittal:
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples. CoRR abs/1905.01726 (2019) - 2018
- [j103]Yongjiu Du, Yan Shi, Ehsan Aryafar, Pengfei Cui, Joseph Camp, Mung Chiang:
SAMU: design and implementation of frequency selectivity-aware multi-user MIMO for WLANs. EURASIP J. Wirel. Commun. Netw. 2018: 297 (2018) - [j102]Arsalan Mosenia, Jad F. Bechara, Tao Zhang, Prateek Mittal, Mung Chiang:
ProCMotive: Bringing Programmability and Connectivity into Isolated Vehicles. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2(1): 26:1-26:31 (2018) - [j101]Hazer Inaltekin, Maria Gorlatova, Mung Chiang:
Virtualized Control Over Fog: Interplay Between Reliability and Latency. IEEE Internet Things J. 5(6): 5030-5045 (2018) - [j100]Yang Yang, Xiumei Yang, Wenzhan Song, John K. Zao, Mung Chiang:
Special issue on fog networks. J. Commun. Networks 20(3): 233-236 (2018) - [j99]Ryan Wails, Yixin Sun, Aaron Johnson, Mung Chiang, Prateek Mittal:
Tempest: Temporal Dynamics in Anonymity Systems. Proc. Priv. Enhancing Technol. 2018(3): 22-42 (2018) - [j98]Christopher G. Brinton, Swapna Buccapatnam, Liang Zheng, Da Cao, Andrew S. Lan, Felix Ming Fai Wong, Sangtae Ha, Mung Chiang, H. Vincent Poor:
On the Efficiency of Online Social Learning Networks. IEEE/ACM Trans. Netw. 26(5): 2076-2089 (2018) - [c192]Da Cao, Andrew S. Lan, Weiyu Chen, Christopher G. Brinton, Mung Chiang:
Learner Behavioral Feature Refinement and Augmentation Using GANs. AIED (2) 2018: 41-46 - [c191]Tsung-Yen Yang, Christopher G. Brinton, Prateek Mittal, Mung Chiang, Andrew S. Lan:
Learning Informative and Private Representations via Generative Adversarial Networks. IEEE BigData 2018: 1534-1543 - [c190]Mohammad Shahrad, Arsalan Mosenia, Liwei Song, Mung Chiang, David Wentzlaff, Prateek Mittal:
Acoustic Denial of Service Attacks on Hard Disk Drives. ASHES@CCS 2018: 34-39 - [c189]Vikash Sehwag, Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Mung Chiang, Prateek Mittal:
Not All Pixels are Born Equal: An Analysis of Evasion Attacks under Locality Constraints. CCS 2018: 2285-2287 - [c188]Andrew S. Lan, Mung Chiang, Christoph Studer:
Linearized binary regression. CISS 2018: 1-6 - [c187]Weiyu Chen, Andrew S. Lan, Da Cao, Christopher G. Brinton, Mung Chiang:
Behavioral Analysis at Scale: Learning Course Prerequisite Structures from Learner Clickstreams. EDM 2018 - [c186]Andrew S. Lan, Mung Chiang, Christoph Studer:
An Estimation and Analysis Framework for the Rasch Model. ICML 2018: 2889-2897 - [c185]Ruijiu Mao, Vaneet Aggarwal, Mung Chiang:
Stochastic non-preemptive co-flow scheduling with time-indexed relaxation. INFOCOM Workshops 2018: 385-390 - [c184]Liang Zheng, Carlee Joe-Wong, Matthew Andrews, Mung Chiang:
Optimizing Data Plans: Usage Dynamics in Mobile Data Networks. INFOCOM 2018: 2474-2482 - [c183]Mikhail Khodak, Liang Zheng, Andrew S. Lan, Carlee Joe-Wong, Mung Chiang:
Learning Cloud Dynamics to Optimize Spot Instance Bidding Strategies. INFOCOM 2018: 2762-2770 - [c182]Andrew S. Lan, Jonathan C. Spencer, Ziqi Chen, Christopher G. Brinton, Mung Chiang:
Personalized Thread Recommendation for MOOC Discussion Forums. ECML/PKDD (2) 2018: 725-740 - [c181]Aakanksha Chowdhery, Mung Chiang:
Model Predictive Compression for Drone Video Analytics. SECON Workshops 2018: 19-23 - [c180]Surin Ahn, Maria Gorlatova, Parinaz Naghizadeh, Mung Chiang, Prateek Mittal:
Adaptive Fog-Based Output Security for Augmented Reality. VR/AR Network@SIGCOMM 2018: 1-6 - [i37]Ryan Wails, Yixin Sun, Aaron Johnson, Mung Chiang, Prateek Mittal:
Tempest: Temporal Dynamics in Anonymity Systems. CoRR abs/1801.01932 (2018) - [i36]Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Prateek Mittal, Mung Chiang:
Rogue Signs: Deceiving Traffic Sign Recognition with Malicious Ads and Logos. CoRR abs/1801.02780 (2018) - [i35]Ruijiu Mao, Vaneet Aggarwal, Mung Chiang:
Stochastic Non-preemptive Co-flow Scheduling with Time-Indexed Relaxation. CoRR abs/1802.03700 (2018) - [i34]Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia, Mung Chiang, Prateek Mittal:
DARTS: Deceiving Autonomous Cars with Toxic Signs. CoRR abs/1802.06430 (2018) - [i33]Andrew S. Lan, Mung Chiang, Christoph Studer:
An Estimation and Analysis Framework for the Rasch Model. CoRR abs/1806.03551 (2018) - [i32]Andrew S. Lan, Jonathan C. Spencer, Ziqi Chen, Christopher G. Brinton, Mung Chiang:
Personalized Thread Recommendation for MOOC Discussion Forums. CoRR abs/1806.08468 (2018) - [i31]Maria Gorlatova, Hazer Inaltekin, Mung Chiang:
Characterizing Task Completion Latencies in Fog Computing. CoRR abs/1811.02638 (2018) - 2017
- [j97]Michael Wang, Jiasi Chen, Ehsan Aryafar, Mung Chiang:
A Survey of Client-Controlled HetNets for 5G. IEEE Access 5: 2842-2854 (2017) - [j96]Mung Chiang, Sangtae Ha, Chih-Lin I, Fulvio Risso, Tao Zhang:
Fog Computing and Networking: Part 1. IEEE Commun. Mag. 55(4): 16-17 (2017) - [j95]Mung Chiang, Sangtae Ha, Chih-Lin I, Fulvio Risso, Tao Zhang:
Clarifying Fog Computing and Networking: 10 Questions and Answers. IEEE Commun. Mag. 55(4): 18-20 (2017) - [j94]Mung Chiang, Sangtae Ha, Chih-Lin I, Fulvio Risso, Tao Zhang:
Fog Computing and Networking: Part 2. IEEE Commun. Mag. 55(8): 13 (2017) - [j93]Liang Zheng, Carlee Joe-Wong, Chee Wei Tan, Sangtae Ha, Mung Chiang:
Customized Data Plans for Mobile Users: Feasibility and Benefits of Data Trading. IEEE J. Sel. Areas Commun. 35(4): 949-963 (2017) - [j92]Mihaela van der Schaar, Richard G. Baraniuk, Mung Chiang, Jonathan Huang, Shengdong Zhao:
Introduction to the Issue on Signal Processing and Machine Learning. IEEE J. Sel. Top. Signal Process. 11(5): 713-715 (2017) - [j91]Tsung-Yen Yang, Christopher G. Brinton, Carlee Joe-Wong, Mung Chiang:
Behavior-Based Grade Prediction for MOOCs Via Time Series Neural Networks. IEEE J. Sel. Top. Signal Process. 11(5): 716-728 (2017) - [j90]Alireza Keshavarz-Haddad, Ehsan Aryafar, Michael Wang, Mung Chiang:
HetNets Selection by Client