3 citations · 4 across the 4 of their papers we have counts for
7 papers
MetaSSD: Meta-Learned Self-Supervised Detection
Moon Jeong Park, Jungseul Ok, Yo-Seb Jeon +1
Deep learning-based symbol detector gains increasing attention due to the simple algorithm design than the traditional model-based algorithms such as Viterbi and BCJR. The supervis…
Gradient Inversion with Generative Image Prior
Jinwoo Jeon, Jaechang Kim, Kangwook Lee +2
Federated Learning (FL) is a distributed learning framework, in which the local data never leaves clients devices to preserve privacy, and the server trains models on the data via…
Multi-armed Bandit Algorithm against Strategic Replication
Suho Shin, Seungjoon Lee, Jungseul Ok
We consider a multi-armed bandit problem in which a set of arms is registered by each agent, and the agent receives reward when its arm is selected. An agent might strategically su…
Transfer Learning in Bandits with Latent Continuity
Hyejin Park, Seiyun Shin, Kwang-Sung Jun +1
Structured stochastic multi-armed bandits provide accelerated regret rates over the standard unstructured bandit problems. Most structured bandits, however, assume the knowledge of…
Exploration in Structured Reinforcement Learning
Jungseul Ok, Alexandre Proutiere, Damianos Tranos
We address reinforcement learning problems with finite state and action spaces where the underlying MDP has some known structure that could be potentially exploited to minimize the…
Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications (Extended Version)
Weiran Huang, Jungseul Ok, Liang Li +1
We study the Combinatorial Pure Exploration problem with Continuous and Separable reward functions (CPE-CS) in the stochastic multi-armed bandit setting. In a CPE-CS instance, we a…