Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Huh, Joon Suk"'
We study a data pricing problem, where a seller has access to $N$ homogeneous data points (e.g. drawn i.i.d. from some distribution). There are $m$ types of buyers in the market, where buyers of the same type $i$ have the same valuation curve $v_i:[N
Externí odkaz:
http://arxiv.org/abs/2407.05484
Autor:
Huh, Joon Suk, Kandasamy, Kirthevasan
We study a multi-round mechanism design problem, where we interact with a set of agents over a sequence of rounds. We wish to design an incentive-compatible (IC) online learning scheme to maximize an application-specific objective within a given clas
Externí odkaz:
http://arxiv.org/abs/2407.04898
We study a sequential profit-maximization problem, optimizing for both price and ancillary variables like marketing expenditures. Specifically, we aim to maximize profit over an arbitrary sequence of multiple demand curves, each dependent on a distin
Externí odkaz:
http://arxiv.org/abs/2403.01361
Autor:
Huh, Joon Suk
This work addresses the problem of revenue maximization in a repeated, unlimited supply item-pricing auction while preserving buyer privacy. We present a novel algorithm that provides differential privacy with respect to the buyer's input pair: item
Externí odkaz:
http://arxiv.org/abs/2305.11362
Autor:
Resch, Salonik, Gutierrez, Anthony, Huh, Joon Suk, Bharadwaj, Srikant, Eckert, Yasuko, Loh, Gabriel, Oskin, Mark, Tannu, Swamit
Variational quantum algorithms (VQAs) provide a promising approach to achieve quantum advantage in the noisy intermediate-scale quantum era. In this era, quantum computers experience high error rates and quantum error detection and correction is not
Externí odkaz:
http://arxiv.org/abs/2109.01714
Autor:
Seo, Junghoon, Huh, Joon Suk
Publikováno v:
2021 IEEE ICASSP International Conference on Acoustics, Speech, and Signal Processing
Partial label learning (PLL) is a class of weakly supervised learning where each training instance consists of a data and a set of candidate labels containing a unique ground truth label. To tackle this problem, a majority of current state-of-the-art
Externí odkaz:
http://arxiv.org/abs/2010.11600
Finding the minimum energy conformation of protein-like heteropolymers by Greedy Neighborhood Search
Autor:
Huh, Joon Suk
A global optimization method called Greedy Neighborhood Search (GNS) and a novel conformational sampling method using a spherical distribution is proposed to find the minimum energy conformation of a protein-like heteropolymer model called AB model.
Externí odkaz:
http://arxiv.org/abs/1612.00949