22 citations · 46 across the 7 of their papers we have counts for
7 papers
Contextual Decision-Making with Knapsacks Beyond the Worst Case
Zhaohua Chen, Rui Ai, Mingwei Yang +3
We study the framework of a dynamic decision-making scenario with resource constraints. In this framework, an agent, whose target is to maximize the total reward under the initial…
QuaLA-MiniLM: a Quantized Length Adaptive MiniLM
Shira Guskin, Moshe Wasserblat, Chang Wang +1
Limited computational budgets often prevent transformers from being used in production and from having their high accuracy utilized. A knowledge distillation approach addresses the…
Dynamic Budget Throttling in Repeated Second-Price Auctions
Zhaohua Chen, Chang Wang, Qian Wang +6
In today's online advertising markets, a crucial requirement for an advertiser is to control her total expenditure within a time horizon under some budget. Among various budget con…
No-regret Learning in Repeated First-Price Auctions with Budget Constraints
Rui Ai, Chang Wang, Chenchen Li +3
Recently the online advertising market has exhibited a gradual shift from second-price auctions to first-price auctions. Although there has been a line of works concerning online b…
Budget-Constrained Auctions with Unassured Priors: Strategic Equivalence and Structural Properties
Zhaohua Chen, Mingwei Yang, Chang Wang +5
In today's online advertising markets, it is common for advertisers to set long-term budgets. Correspondingly, advertising platforms adopt budget control methods to ensure that adv…
Hybrid Differentially Private Federated Learning on Vertically Partitioned Data
Chang Wang, Jian Liang, Mingkai Huang +3
We present HDP-VFL, the first hybrid differentially private (DP) framework for vertical federated learning (VFL) to demonstrate that it is possible to jointly learn a generalized l…
A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations
Mingkai Huang, Hao Li, Bing Bai +3
Privacy-preserving recommendations are recently gaining momentum, since the decentralized user data is increasingly harder to collect, by recommendation service providers, due to t…