Several problems have been extensively studied in the learning-augmented setting, where
the algorithm has access to some, possibly incorrect, predictions. However, it is assumed in …

Paging is a prototypical problem in the area of online algorithms. It has also played a central
role in the development of learning-augmented algorithms. Previous work on learning …

This paper leverages machine-learned predictions to design competitive algorithms for
online conversion problems with the goal of improving the competitive ratio when …

The online knapsack problem is a classic online resource allocation problem in networking
and operations research. Its basic version studies how to pack online arriving items of …

In this paper, we study the online multidimensional knapsack problem (called OMdKP) in
which there is a knapsack whose capacity is represented in m dimensions, each dimension …

The online bin packing problem is a well-known optimization challenge that finds application
in a wide range of real-world scenarios. In the paper, we propose a novel algorithm called …

Many problems, such as online ad display, can be formulated as online bipartite matching.
The crucial challenge lies in the nature of sequentially-revealed online item information …

In online interval scheduling, the input is an online sequence of intervals, and the goal is to
accept a maximum number of non-overlapping intervals. In the more general disjoint path …

A variant of the online knapsack problem is considered in the settings of trusted and
untrusted predictions. In Unit Profit Knapsack, the items have unit profit, and it is easy to find …

This paper develops learning-augmented algorithms for energy trading in volatile electricity
markets. The basic problem is to sell (or buy) k units of energy for the highest revenue …