4 accepted papers
Previous ad auctions predominantly relied on rule-based mechanisms, which selected winning advertisements (ads) at the ad-level and subsequently combined them into page views (PVs), leading to suboptimal allocations in multi-round auctions. This limitation stems from the significant computational bu…
Binary classification with imbalanced classes is a common and fundamental task, where standard machine learning methods often struggle to provide reliable predictive performance. Although numerous approaches have been proposed to address this issue, classification in low-sample-size and high-dimensi…
This paper introduces a finite smoothing algorithm (FSA), a novel approach to tackle computational challenges in applying support vector machines (SVM) and quantile regression to high-dimensional data. The critical issue with these methods is the non-smooth nature of their loss functions, which trad…
Correlation filters (CFs) have shown excellent performance in unmanned aerial vehicle (UAV) tracking scenarios due to their high computational efficiency. During the UAV tracking process, viewpoint variations are usually accompanied by changes in the object and background appearance, which poses a u…