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Technical Talks Session 1
Ishika Singh · Laura Rieger · Rasmus Høegh · Hanlin Lu · Wonyong Jeong

Sat Jul 18 06:35 AM -- 07:25 AM (PDT) @
in Federated Learning for User Privacy and Data Confidentiality »
  1. Wonyong Jeong, Jaehong Yoon, Eunho Yang and Sung Ju Hwang. Federated Semi-Supervised Learning with Inter-Client Consistency
  2. Ishika Singh, Haoyi Zhou, Kunlin Yang, Meng Ding, Bill Lin and Pengtao Xie. Differentially-private Federated Neural Architecture Search
  3. Laura Rieger, Rasmus Malik Thaarup Høegh and Lars Kai Hansen. Client Adaptation improves Federated Learning with Simulated Non-IID Clients
  4. Hanlin Lu, Changchang Liu, Ting He, Shiqiang Wang and Kevin S. Chan. Sharing Models or Coresets: A Study based on Membership Inference Attack

Author Information

Ishika Singh (Computer Science, Indian Institute of Technology Kanpur, India)

My research agenda pertains to modeling interpretable intelligent machines with ethics and emotions incorporated. I also have some inclination towards mathematics, hence I pursued research work in theoretical ML as well. Particularly, I spend time in: Human-Centered AI Distributed Learning and Optimization NLP and RL

Laura Rieger (Technical University of Denmark)
Rasmus Høegh (Technical University of Denmark (DTU))
Hanlin Lu (Pennsylvania State University)
Wonyong Jeong (KAIST)

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