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Liang Shan 0016

dblp:344/9501 · DBLP profile ↗
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5ranked-venue papers
2as first author
5since 2021 · last 2025
0009-0001-6558-812XORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Theory of computation · 2 · 2 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Algorithmic game theory and mechanism design · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design › mechanism design
truthful mechanism
0.812024
On Truthful Item-Acquiring Mechanisms for Reward Maximization · WWW 2024
Algorithmic game theory and mechanism design › mechanism design
bayesian mechanism design
0.712023
Optimal Pricing Schemes for Identical Items with Time-Sensitive Buyers · AAAI 2023
Algorithmic game theory and mechanism design › pricing
pricing mechanism
0.712023
Optimal Pricing Schemes for Identical Items with Time-Sensitive Buyers · AAAI 2023
Algorithmic game theory and mechanism design › mechanism design
incentive compatibility
0.212024
On Truthful Item-Acquiring Mechanisms for Reward Maximization · WWW 2024

Methods — techniques the papers use, named apart from their topics

menu size analysis · 0.8mechanism design · 0.8
YearPublicationVenuePosition
2025 On the Oscillations in Cournot Games with Best Response Strategies
Zhengyang Liu 0002, Liang Shan 0016, Zihe Wang 0001
COCOON (1)3
2025 Environmental Policies within Cournot Oligopoly
Liang Shan 0016, Zhengyang Liu 0002, Haoqiang Huang, Zihe Wang 0001
AAMAS1
2025 Striking the balance: Optimizing pricing schemes for time-sensitive buyers
Zhengyang Liu 0002, Liang Shan 0016, Zihe Wang 0001
Theor. Comput. Sci.2
2024 On Truthful Item-Acquiring Mechanisms for Reward Maximization
abstract
In this research, we study the problem that a collector acquires items from the owner based on the item qualities the owner declares and an independent appraiser's assessments. The owner is interested in maximizing the probability that the collector acquires the items and is the only one who knows the items' factual quality. The appraiser performs her duties with impartiality, but her assessment may be subject to random noises, so it may not accurately reflect the factual quality of the items. The main challenge lies in devising mechanisms that prompt the owner to reveal accurate information, thereby optimizing the collector's expected reward. We consider the menu size of mechanisms as a measure of their practicability and study its impact on the attainable expected reward. For the single-item setting, we design optimal mechanisms with a monotone increasing menu size. Although the reward gap between the simplest and optimal mechanisms is bounded, we show that simple mechanisms with a small menu size cannot ensure any positive fraction of the optimal reward of mechanisms with a larger menu size. For the multi-item setting, we show that an ordinal mechanism that only takes the owner's ordering of the items as input is not incentive-compatible. We then propose a set of Union mechanisms that combine single-item mechanisms. Moreover, we run experiments to examine these mechanisms' robustness against the independent appraiser's assessment accuracy and the items' acquiring rate.
Liang Shan 0016, Shuo Zhang 0034, Jie Zhang 0008, Zihe Wang 0001
WWW1
2023 Optimal Pricing Schemes for Identical Items with Time-Sensitive Buyers
abstract
Time or money? That is a question! In this paper, we consider this dilemma in the pricing regime, in which we try to find the optimal pricing scheme for identical items with heterogenous time-sensitive buyers. We characterize the revenue-optimal solution and propose an efficient algorithm to find it in a Bayesian setting. Our results also demonstrate the tight ratio between the value of wasted time and the seller's revenue, as well as that of two common-used pricing schemes, the k-step function and the fixed pricing. To explore the nature of the optimal scheme in the general setting, we present the closed forms over the product distribution and show by examples that positive correlation between the valuation of the item and the cost per unit time could help increase revenue. To the best of our knowledge, it is the first step towards understanding the impact of the time factor as a part of the buyer cost in pricing problems, in the computational view.
Zhengyang Liu 0002, Liang Shan 0016, Zihe Wang 0001
AAAI2