8 citations · 17 across the 8 of their papers we have counts for
8 papers
An Information-Theoretic Proof of the Kac--Bernstein Theorem
J. Jon Ryu, Young-Han Kim
A short, information-theoretic proof of the Kac--Bernstein theorem, which is stated as follows, is presented: For any independent random variables and , if and a…
On Universal Portfolios with Continuous Side Information
Alankrita Bhatt, J. Jon Ryu, Young-Han Kim
A new portfolio selection strategy that adapts to a continuous side-information sequence is presented, with a universal wealth guarantee against a class of state-constant rebalance…
Parameter-free Online Linear Optimization with Side Information via Universal Coin Betting
J. Jon Ryu, Alankrita Bhatt, Young-Han Kim
A class of parameter-free online linear optimization algorithms is proposed that harnesses the structure of an adversarial sequence by adapting to some side information. These algo…
Minimax Optimal Algorithms with Fixed--Nearest Neighbors
J. Jon Ryu, Young-Han Kim
This paper presents how to perform minimax optimal classification, regression, and density estimation based on fixed- nearest neighbor (NN) searches. We consider a distributed l…
Learning with Succinct Common Representation Based on Wyner's Common Information
J. Jon Ryu, Yoojin Choi, Young-Han Kim +2
A new bimodal generative model is proposed for generating conditional and joint samples, accompanied with a training method with learning a succinct bottleneck representation. The…
Nearest neighbor density functional estimation from inverse Laplace transform
J. Jon Ryu, Shouvik Ganguly, Young-Han Kim +2
A new approach to -consistent estimation of a general density functional using -nearest neighbor distances is proposed, where the functional under consideration is in the f…
Energy-Based Sequence GANs for Recommendation and Their Connection to Imitation Learning
Jaeyoon Yoo, Heonseok Ha, Jihun Yi +5
Recommender systems aim to find an accurate and efficient mapping from historic data of user-preferred items to a new item that is to be liked by a user. Towards this goal, energy-…
NASCUP: Nucleic Acid Sequence Classification by Universal Probability
Sunyoung Kwon, Gyuwan Kim, Byunghan Lee +3
Motivated by the need for fast and accurate classification of unlabeled nucleotide sequences on a large scale, we developed NASCUP, a new classification method that captures statis…