11 accepted papers
In this paper, we study cooperative multi-agent reinforcement learning (MARL) where the joint reward exhibits submodularity, which is a natural property capturing diminishing marginal returns when adding agents to a team. Unlike standard MARL with additive rewards, submodular rewards model realistic…
In the final “Last-Centimeter” phase of manipulation, visual occlusion and calibration errors often make vision unreliable, causing robots to suffer high failure rates due to local pose uncertainty and deviations between simulated and real-world dynamics. To address these challenges, this paper prop
We address the problem of submodular maximization under bandit feedback, where the objective function $f:2^U\to\mathbb{R}_{\geq 0}$ can only be accessed through noisy, i.i.d. sub-Gaussian queries. This problem arises in many applications including influence maximization, diverse recommendation syste
With the rapid growth of data in modern applications, parallel combinatorial algorithms for maximizing non-monotone submodular functions have gained significant attention. In the parallel computation setting, the state-of-the-art approximation ratio of $1/e$ is achieved by a continuous algorithm (En…
Machine learning algorithms are becoming increasing prevalent in the modern world, and as a result there has been significant recent study into algorithmic fairness in order to minimize the possibility of unintentional bias or discrimination in these algorithms. Submodular optimization problems also…
Leveraging the intrinsic structure of submodular functions to design more sample-efficient algorithms for submodular maximization (SM) has gained significant attention in recent studies. In a number of real-world applications such as diversified recommender systems and data summarization, the submod…
Since the goals of both Moment Retrieval (MR) and Highlight Detection (HD) are to quickly obtain the required content from the video according to user needs, several works have attempted to take advantage of the commonality between both tasks to design transformer-based networks for joint MR and HD.…
Effectively modeling the interactions among actors is critical and challenging for Group Activity Recognition (GAR). Previous methods usually divide actors into subgroups based on the similarity of appearance features for modeling multilevel interactions among actors. However, the appearance feature…
Video moment retrieval (MR) and highlight detection (HD) based on natural language queries are two highly related tasks, which aim to obtain relevant moments within videos and highlight scores of each video clip. Recently, several methods have been devoted to building DETR-based networks to solve bo…
In this paper, we consider the optimization problem Submodular Cover (SCP), which is to find a minimum cardinality subset of a finite universe $U$ such that the value of a submodular function $f$ is above an input threshold $\tau$. In particular, we consider several variants of SCP including the gen…
Goal-oriented Reinforcement Learning, where the agent needs to reach the goal state while simultaneously minimizing the cost, has received significant attention in real-world applications. Its theoretical formulation, stochastic shortest path (SSP), has been intensively researched in the online sett…