Lin Chen



I am moving my homepage to https://lchen91.github.io/

Ph.D. candidate [Google Scholar]
Yale Institute for Network Science, Department of Electrical Engineering, Yale University

Lin Chen is currently a Ph.D. candidate in the Department of Electrical Engineering, Yale University, under the supervision of Professor Amin Karbasi. He received B.S. from Peking University in 2014. His research interests focus on machine learning theory. His Erdős number is 3 (Lin Chen -> Sanjoy Dasgupta -> Leonard J. Schulman -> Paul Erdős).

Email: lin.chen [at] yale [dot] edu  ORCID Researcher ID: 0000-0003-0349-6577.

Here is my CV. 

What’s New

Publications

The documents listed below have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

Bibtex file for all the papers below. 
See here for published codes.

Submitted Papers/Preprints

  1. Ruitu Xu, Lin Chen, Amin Karbasi, “Meta Learning in the Continuous Time Limit“.
  2. Lin Chen, Qian Yu, Hannah Lawrence, Amin Karbasi, “Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transition“. First two authors contributed equally to this work.
  3. Yifei Min, Lin Chen, Amin Karbasi, “The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization“.
  4. Kaigui Bian, Lin Chen, Yuanxing Zhang, Jung-Min “Jerry” Park, Xiaojiang Du, Xiaoming Li, “Heterogeneous Coexistence of Cognitive Radio Networks in TV White Space“.

Conference Papers

  1. [ICML] Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi, “More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models“, in ICML 2020. First two authors contributed equally to this work.
  2. [STOC] Lin Chen, Moran Feldman, and Amin Karbasi, “Unconstrained Submodular Maximization with Constant Adaptive Complexity“, in Proc. of STOC 2019. Authors listed in alphabetical order.
  3. [NeurIPS] Lin Chen, Hossein Esfandiari, Gang Fu, Vahab S. Mirrokni, “Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond“, in NeurIPS 2019.
  4. [NeurIPS] Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi, “Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback“, in NeurIPS 2019.
  5. [AISTATS] Lin Chen, Mingrui Zhang, Hamed Hassani, and Amin Karbasi, “Black Box Submodular Maximization: Discrete and Continuous Settings“, in AISTATS 2020. First two authors contributed equally to this work.
  6. [AISTATS] Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, and Amin Karbasi, “Quantized Frank-Wolfe: Faster Optimization, LowerCommunication, and Projection Free“, in AISTATS 2020.
  7. [ICML] MohammadHossein Bateni, Lin Chen, Hossein Esfandiari, Thomas Fu, Vahab S. Mirrokni, and Afshin Rostamizadeh, “Categorical Feature Compression via Submodular Optimization“, in Proc. of ICML 2019. Authors listed in alphabetical order. (Oral presentation)
  8. [AISTATS] Lin Chen, Mingrui Zhang, and Amin Karbasi, “Projection-Free Bandit Convex Optimization“, in Proc. of AISTATS 2019. First two authors contributed equally to this work.
  9. [ICML] Lin Chen, Moran Feldman, and Amin Karbasi, “Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?“, in Proc. of ICML 2018. Authors listed in alphabetical order. (Acceptance rate: 25.0%, long talk)
  10. [ICML] Lin Chen, Christopher Harshaw, Hamed Hassani, and Amin Karbasi, “Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity“, in Proc. of ICML 2018. (Acceptance rate: 25.0%, long talk)
  11. [AISTATS] Lin Chen, Hamed Hassani, and Amin Karbasi, “Online Continuous Submodular Maximization”, in Proc. of AISTATS 2018. (Oral presentation)[arxiv][github]
  12. [AISTATS] Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, and Amin Karbasi, “Comparison Based Learning from Weak Oracles”, in Proc. of AISTATS 2018.[arxiv]
  13. [NIPS] Lin Chen, Amin Karbasi, and Andreas Krause, “Interactive Submodular Bandit”, in Proc. of NIPS 2017. (Acceptance rate: 20.9%) [pdf]
  14. [UAI] Lin Chen, Amin Karbasi, and Forrest W Crawford, “Submodular Variational Inference for Network Reconstruction”, in Proc. of UAI 2017. [arxiv]
  15. [AAAI] Lin Chen, Hamed Hassani, and Amin Karbasi, “Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting“,in Proc. of 31st AAAI Conference on Artificial Intelligence (AAAI 2017), San Francisco, California, February 2017. (Acceptance rate: 24.6%, oral presentation) [arxiv][slides][github]
  16. [NIPS] Lin Chen, Amin Karbasi, Forrest W. Crawford, “Estimating the Size of a Large Network and its Communities from a Random Sample“, in Advances in Neural Information Processing Systems 29 (NIPS 2016), Barcelona, Spain, December 2016. (Acceptance rate: 22.7%) [arxiv][pdf]
  17. [AAAI] Lin Chen, Forrest W. Crawford, and Amin Karbasi, “Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling“, in Proc. of 30th AAAI Conference on Artificial Intelligence (AAAI 2016), Phoenix, Arizona, USA, February 2016. (Acceptance rate: 26%) [arxiv][pdf][slides]
  18. [UbiComp] Shuyu Shi, Lin Chen, Wenjun Hu, and Marco Gruteser, “Reading between Lines: High-rate, Non-intrusive Visual Codes within Regular Videos via ImplicitCode”, in Proc. of The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (ACM UbiComp 2015), Osaka, Japan, September 2015. (Acceptance rate: 22%, oral presentation)
  19. [INFOCOM] Zhiying Xu, Shuyu Shi, Alex X. Liu, Jun Zhao, Lin Chen, “An Adaptive and Fast Convergent Approach to Differentially Private Deep Learning“, in Proc. INFOCOM 2020.
  20. Yuanxing Zhang, Pengyu Zhao, Yushuo Guan, Lin Chen, Kaigui Bian, Lingyang Song, Bin Cui, Xiaoming Li, “Preference-aware Mask for Session-based Recommendation with Bidirectional Transformer”, in Proc. ICASSP 2020.
  21. Yuanxing Zhang, Kaigui Bian, Lin Chen, Shaoling Dong, Lingyang Song, and Xiaoming Li, “Early Detection of Rumors in Heterogeneous Mobile Social Network“, in Proc. of IEEE DSC 2018, Guangzhou, China, June 18-21, 2018. (Best Student Paper Award)
  22. Yushuo Guan, Yuanxing Zhang, Lin Chen, and Kaigui Bian, “A Neural Attack Model for Cracking Passwords in Adversarial Environments”, in IEEE/CIC ICCC 2019.
  23. Yuanxing Zhang, Lin Chen, Kaigui Bian, Lingyang Song, and Xiaoming Li, “Enabling Symbiotic Coexistence of Heterogeneous Cognitive Radio Networks”, in Proc. 2018 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) – Workshop: 5G and Spectrum Sharing (5G Spectrum).
  24. Yangbin Zhang, Kaigui Bian, Lin Chen, Pan Zhou, and Xiaoming Li, “Dynamic Slot-length Control for Reducing Neighbor Discovery Latency in Wireless Sensor Networks”, in Proc. of IEEE GLOBECOM 2017, Singapore, December 4-8, 2017.
  25. Yuanxing Zhang, Yichong Bai, Lin Chen, Kaigui Bian, and Xiaoming Li, “Influence Maximization in Messenger-based Social Networks“, in Proc. of IEEE GLOBECOM 2016, Washington, D.C., USA, December 4-8, 2016.
  26. Zhuqi Li, Lin Chen, Yichong Bai, Kaigui Bian, and Pan Zhou, “On Diffusion-restricted Social Network: A Measurement Study of WeChat Moments“, in Proc. of IEEE International Conference on Communications (IEEE ICC 2016), Kuala Lumpur, Malaysia, May 23-27, 2016.[arxiv]
  27. Lin Chen, Zhiping Xiao, Kaigui Bian, Shuyu Shi, Rui Li, and Yusheng Ji, “Skolem Sequence Based Self-adaptive Broadcast Protocol in Cognitive Radio Networks“, in Proc. of 2016 IEEE 83rd Vehicular Technology Conference (VTC2016-Spring), Nanjing, China, May 15–18, 2016.[arxiv]
  28. Lin Chen, Shuyu Shi, Kaigui Bian, and Yusheng Ji, “Optimizing Average-Maximum TTR Trade-off for Cognitive Radio Rendezvous“, in Proc. of  IEEE International Conference on Communications (IEEE ICC 2015), London, UK, June 2015. [pdf][arxiv]
  29. Hongji Yang, Lin Chen, Kaigui Bian, Yang Tian, Fan Ye, Wei Yan, Tong Zhao, and Xiaoming Li, “TapLock: Exploit Finger Tap Events for Enhancing Attack Resilience of Smartphone Passwords“, in Proc. of IEEE International Conference on Communications (IEEE ICC 2015), London, UK, June 2015.
  30. [INFOCOM] Lin Chen, Ruolin Fan, Kaigui Bian, Lin Chen, Mario Gerla, Tao Wang, and Xiaoming Li, “On Heterogeneous Neighbor Discovery in Wireless Sensor Networks”, in Proc. of the 34th Annual IEEE International Conference on Computer Communications (IEEE INFOCOM 2015), Hong Kong, China, April 2015. (Acceptance rate: 19%, oral presentation)[preprint][arxiv]
  31. [MobiHoc] Lin Chen, Kaigui Bian, Lin Chen, Cong Liu, Jung-Min “Jerry” Park, and Xiaoming Li, “A Group-theoretic Framework for Rendezvous in Heterogeneous Cognitive Radio Networks,” in Proc. of the 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing (ACM MobiHoc 2014), Philadelphia, PA, USA, Aug. 2014. (Acceptance rate: 18.9%, oral presentation) [pdf][acmdl][slides][bibtex]
  32. Lin Chen, Kaigui Bian, Lin Chen, Wei Yan, and Xiaoming Li, “On the Cascading Spectrum Contention Problem in Self-coexistence of Cognitive Radio Networks,” in Proc. First ACM Workshop on Cognitive Radio Architectures for Broadband (ACM CRAB 2013), in conjunction with ACM MobiCom 2013, Miami, FL, USA, Oct. 2013. [pdf][acmdl][slides][bibtex]

Journal Papers

  1. Lin Chen, Ruolin Fan, Yangbin Zhang, Shuyu Shi, Kaigui Bian, Lin Chen, Pan Zhou, Mario Gerla, Tao Wang, and Xiaoming Li, “On Heterogeneous Duty Cycles for Neighbor Discovery in Wireless Sensor Networks”, in Ad Hoc Networks Journal, to appear.[pdf]
  2. Shuyu Shi, Stephan Sigg, Lin Chen, and Yusheng Ji. “Accurate Location Tracking from CSI-based Passive Device-free Probabilistic Fingerprinting“, in IEEE Transactions on Vehicular Technology (IEEE TVT), to appear.
  3. Lin Chen, Kaigui Bian, Xiaojiang Du, and Xiaoming Li, “Multi-channel Broadcast via Channel Hopping in Cognitive Radio Networks”, accepted by IEEE Transactions on Vehicular Technology (IEEE TVT), vol. 64, no. 7, July 2015.[pdf][ieeedl]
  4. Kaigui Bian, Jung-Min “Jerry” Park, Lin Chen, and Xiaoming Li, “Addressing the Hidden Terminal Problem for Heterogeneous Coexistence between TDM and CSMA Networks in White Space”, in IEEE Transactions on Vehicular Technology (IEEE TVT), vol. 63, no. 9, November 2014.[pdf][ieeedl]

Other Publications

  1. Lin Chen, Alexander Fabrikant, and Rachael Morgan, “A Method For Detecting Scheduled-Service Vehicles By Crowdsensing Of On-Board Beacons“, Technical Disclosure Commons, (November 13, 2017).

Professional Activities

  1. Area chair of ICLR 2021
  2. Reviewer of NeurIPS 2020 (6 papers)
  3. Reviewer of COLT 2020
  4. Reviewer of ISIT 2020
  5. Area chair of ICML 2020 (16 papers)
  6. Reviewer of ALT 2020
  7. Reviewer of AISTATS 2020 (7 papers)
  8. Reviewer of SODA 2019
  9. Reviewer of NeurIPS 2019 (5 papers)
  10. Reviewer of Neural Computation
  11. Reviewer of APPROX 2019
  12. Program committee member of DSAA2019 (5 papers)
  13. Program committee member of ACML 2019 (5 papers)
  14. Reviewer of FOCS 2019
  15. Program committee (PC) member of KDD 2019 (9 papers)
  16. Reviewer of JMLR (1 paper)
  17. Reviewer of ICML 2019 (5 papers)
  18. Reviewer of IEEE Letters of the Computer Society
  19. Reviewer of AISTATS 2019 (5 papers)
  20. Reviewer of NIPS 2018 (3 papers)
  21. Reviewer of GLOBECOM 2018
  22. Reviewer of IEEE Access (5 papers)
  23. Reviewer of Journal of Radio and Audio Media
  24. Reviewer of WWW 2018
  25. Reviewer of UbiComp 2017 (4 posters)
  26. Reviewer of EPJ Data Science
  27. Reviewer of Electronics Letters
  28. Reviewer of AAAI 2017 (2 papers)
  29. Reviewer of MOBIQUITOUS 2016 (2 papers)
  30. Reviewer of NIPS 2016 (3 papers)
  31. Reviewer of UbiComp 2016 (6 posters)
  32. Reviewer of VTC 2016 Fall (3 papers)
  33. Reviewer of IEEE Transactions on Mobile Computing (2 papers)
  34. Reviewer of IJCAI 2016 (3 papers)
  35. Reviewer of Journal of Computer Science and Technology (JCST)
  36. Reviewer of VTC 2016
  37. Reviewer of ICC 2016 Spring (3 papers)
  38. Reviewer of IEEE Communication Letters (2 papers)
  39. Reviewer of AAAI 2016 (4 papers)
  40. Reviewer of the 2015 International Conference on Wireless Communications and Signal Processing (WCSP 2015) (4 papers)
  41. Reviewer of TTCS 2015 (5 papers)
  42. Reviewer of UbiComp/ISWC 2015 (4 posters/demos)
  43. Reviewer of IEEE PIMRC 2015 (3 papers)
  44. Reviewer of IEEE/ACM Transactions on Networking (3 papers)
  45. Reviewer of SIGMETRICS 2015
  46. Reviewer of ICC 2015 (2 papers)
  47. Reviewer of AAAI 2015 (2 papers)
  48. Reviewer of IEEE Transactions on Vehicular Technology (4 papers)

Presentations

  1. Talk and poster presentation at ITA 2020, San Diego, CA, Feb 2020.
  2. Two poster presentations on 13th Annual Machine Learning Symposium, New York, NY, USA, March 1, 2019.

Teaching Experiences

  1. Teaching fellow for Computational Tools for Data Science (S&DS 262a / AMTH 262a / CPSC 262a), 2017 Fall.
  2. Teaching fellow for Randomized Algorithms (CPSC 469/569), 2016 Fall.
  3. Teaching fellow for Stochastic Process (ENAS 496 / ENAS 502 / MATH 251 / STAT 251 / STAT 551), 2016 Spring.

Employment

  1. Student researcher, Google, New York City, Dec 2018 – May 2019.
  2. Research intern, Google, New York City, 2018 summer.
  3. Research intern, Google, Mountain View, 2017 summer.

Selected Honors and Awards

Scholarships and Honors

  • Google Ph.D. Fellowship, Apr 2018
  • NIPS Travel Award 2017
  • Yale Conference Travel Fellowship Award, Feb 2017
  • One of 10 Best Bachelor’s Theses, School of EECS, Peking University, June 2014
  • Beijing Outstanding University Undergraduate, May 2014
  • Peking University Outstanding Undergraduate, May 2014
  • Academic Rising Star, School of EECS, Peking University, May 2014

Competitions

  • Meritorious Winner, Mathematical Contest in Modeling (MCM), Consortium for Mathematics and Its Applications (COMAP), the United States, 2013 (*)
  • 1st Prize in Beijing, China Undergraduate Mathematical Contest in Modeling (CUMCM), China Society for Industrial and Applied Mathematics (CSIAM), 2012 (*)
  • 3rd Prize, the 11th Peking University Programming Contest cum the Selective Trial for the ACM/ICPC Team of Peking University, 2012
  • 3rd Prize, the 10th Peking University Programming Contest cum the Selective Trial for the ACM/ICPC Team of Peking University, 2011
  • 2nd Prize, National High School Mathematics Olympiad of China, 2009