32 citations · 57 across the 9 of their papers we have counts for
9 papers
Efficient and Practical Approximation Algorithms for Advertising in Content Feeds
Guangyi Zhang, Ilie Sarpe, Aristides Gionis
Content feeds provided by platforms such as X (formerly Twitter) and TikTok are consumed by users on a daily basis. In this paper, we revisit the native advertising problem in cont…
Finding Favourite Tuples on Data Streams with Provably Few Comparisons
Guangyi Zhang, Nikolaj Tatti, Aristides Gionis
One of the most fundamental tasks in data science is to assist a user with unknown preferences in finding high-utility tuples within a large database. To accurately elicit the unkn…
Sparse Convolution for Approximate Sparse Instance
Xiaoxiao Li, Zhao Song, Guangyi Zhang
Computing the convolution of two vectors of dimension is one of the most important computational primitives in many fields. For the non-negative convolution scenari…
Ranking with submodular functions on the fly
Guangyi Zhang, Nikolaj Tatti, Aristides Gionis
Maximizing submodular functions have been studied extensively for a wide range of subset-selection problems. However, much less attention has been given to the role of submodularit…
Regularized impurity reduction: Accurate decision trees with complexity guarantees
Guangyi Zhang, Aristides Gionis
Decision trees are popular classification models, providing high accuracy and intuitive explanations. However, as the tree size grows the model interpretability deteriorates. Tradi…
Ranking with submodular functions on a budget
Guangyi Zhang, Nikolaj Tatti, Aristides Gionis
Submodular maximization has been the backbone of many important machine-learning problems, and has applications to viral marketing, diversification, sensor placement, and more. How…
Coresets remembered and items forgotten: submodular maximization with deletions
Guangyi Zhang, Nikolaj Tatti, Aristides Gionis
In recent years we have witnessed an increase on the development of methods for submodular optimization, which have been motivated by the wide applicability of submodular functions…
Diverse Rule Sets
Guangyi Zhang, Aristides Gionis
While machine-learning models are flourishing and transforming many aspects of everyday life, the inability of humans to understand complex models poses difficulties for these mode…
Maximizing diversity over clustered data
Guangyi Zhang, Aristides Gionis
Maximum diversity aims at selecting a diverse set of high-quality objects from a collection, which is a fundamental problem and has a wide range of applications, e.g., in Web searc…