297 citations · 958 across the 50 of their papers we have counts for
11 papers · 1 filter
Personalized Federated Learning via Amortized Bayesian Meta-Learning
Shiyu Liu, Shaogao Lv, Dun Zeng +3
Federated learning is a decentralized and privacy-preserving technique that enables multiple clients to collaborate with a server to learn a global model without exposing their pri…
PreDiff: Precipitation Nowcasting with Latent Diffusion Models
Zhihan Gao, Xingjian Shi, Boran Han +6
Earth system forecasting has traditionally relied on complex physical models that are computationally expensive and require significant domain expertise. In the past decade, the un…
Adversarial Latent Autoencoder with Self-Attention for Structural Image Synthesis
Jiajie Fan, Laure Vuaille, Hao Wang +1
Generative Engineering Design approaches driven by Deep Generative Models (DGM) have been proposed to facilitate industrial engineering processes. In such processes, designs often…
Energy Optimization for HVAC Systems in Multi-VAV Open Offices: A Deep Reinforcement Learning Approach
Hao Wang, Xiwen Chen, Natan Vital +2
With more than 32% of the global energy used by commercial and residential buildings, there is an urgent need to revisit traditional approaches to Building Energy Management (BEM).…
LLM-based Smart Reply (LSR): Enhancing Collaborative Performance with ChatGPT-mediated Smart Reply System
Ashish Bastola, Hao Wang, Judsen Hembree +5
Interactive user interfaces have increasingly explored AI's role in enhancing communication efficiency and productivity in collaborative tasks. The emergence of Large Language Mode…
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data
Youlong Ding, Xueyang Wu, Hao Wang +1
The Transformer has emerged as a versatile and effective architecture with broad applications. However, it still remains an open problem how to efficiently train a Transformer mode…
Competing for Shareable Arms in Multi-Player Multi-Armed Bandits
Renzhe Xu, Haotian Wang, Xingxuan Zhang +2
Competitions for shareable and limited resources have long been studied with strategic agents. In reality, agents often have to learn and maximize the rewards of the resources at t…
Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation
Guozhen Zhang, Yuhan Zhu, Haonan Wang +3
Effectively extracting inter-frame motion and appearance information is important for video frame interpolation (VFI). Previous works either extract both types of information in a…
Cross-Frequency Time Series Meta-Forecasting
Mike Van Ness, Huibin Shen, Hao Wang +3
Meta-forecasting is a newly emerging field which combines meta-learning and time series forecasting. The goal of meta-forecasting is to train over a collection of source time serie…
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler
Frank Neumann, Aneta Neumann, Chao Qian +7
Submodular functions play a key role in the area of optimization as they allow to model many real-world problems that face diminishing returns. Evolutionary algorithms have been sh…
Quantum Dueling: an Efficient Solution for Combinatorial Optimization
Letian Tang, Haorui Wang, Zhengyang Li +3
In this paper, we present a new algorithm for generic combinatorial optimization, which we term quantum dueling. Traditionally, potential solutions to the given optimization proble…