50 citations · 118 across the 14 of their papers we have counts for
9 papers · 1 filter
Towards Language-guided Visual Recognition via Dynamic Convolutions
Gen Luo, Yiyi Zhou, Xiaoshuai Sun +3
In this paper, we are committed to establishing an unified and end-to-end multi-modal network via exploring the language-guided visual recognition. To approach this target, we firs…
Rethinking Supervised Pre-training for Better Downstream Transferring
Yutong Feng, Jianwen Jiang, Mingqian Tang +2
The pretrain-finetune paradigm has shown outstanding performance on many applications of deep learning, where a model is pre-trained on a upstream large dataset (e.g. ImageNet), an…
Trajectory Design for UAV-Based Internet-of-Things Data Collection: A Deep Reinforcement Learning Approach
Yang Wang, Zhen Gao, Jun Zhang +5
In this paper, we investigate an unmanned aerial vehicle (UAV)-assisted Internet-of-Things (IoT) system in a sophisticated three-dimensional (3D) environment, where the UAV's traje…
Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets
Yue Gao, Kry Yik Chau Lui, Pablo Hernandez-Leal
Trading markets represent a real-world financial application to deploy reinforcement learning agents, however, they carry hard fundamental challenges such as high variance and cost…
Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model
Yue Gao, Garvesh Raskutti
Network estimation from multi-variate point process or time series data is a problem of fundamental importance. Prior work has focused on parametric approaches that require a known…
Relation Modeling in Spatio-Temporal Action Localization
Yutong Feng, Jianwen Jiang, Ziyuan Huang +5
This paper presents our solution to the AVA-Kinetics Crossover Challenge of ActivityNet workshop at CVPR 2021. Our solution utilizes multiple types of relation modeling methods for…
Graph-MLP: Node Classification without Message Passing in Graph
Yang Hu, Haoxuan You, Zhecan Wang +3
Graph Neural Network (GNN) has been demonstrated its effectiveness in dealing with non-Euclidean structural data. Both spatial-based and spectral-based GNNs are relying on adjacenc…
Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai +2
Classical global convergence results for first-order methods rely on uniform smoothness and the Łojasiewicz inequality. Motivated by properties of objective functions that arise in…
Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems
Yue Gao, Ilia Shumailov, Kassem Fawaz
As real-world images come in varying sizes, the machine learning model is part of a larger system that includes an upstream image scaling algorithm. In this paper, we investigate t…