38 citations · 124 across the 14 of their papers we have counts for
15 papers
Understanding Hessian Alignment for Domain Generalization
Sobhan Hemati, Guojun Zhang, Amir Estiri +1
Out-of-distribution (OOD) generalization is a critical ability for deep learning models in many real-world scenarios including healthcare and autonomous vehicles. Recently, differe…
Understanding the Role of Layer Normalization in Label-Skewed Federated Learning
Guojun Zhang, Mahdi Beitollahi, Alex Bie +1
Layer normalization (LN) is a widely adopted deep learning technique especially in the era of foundation models. Recently, LN has been shown to be surprisingly effective in federat…
AnyDoor: Zero-shot Object-level Image Customization
Xi Chen, Lianghua Huang, Yu Liu +3
This work presents AnyDoor, a diffusion-based image generator with the power to teleport target objects to new scenes at user-specified locations in a harmonious way. Instead of tu…
The Future of ChatGPT-enabled Labor Market: A Preliminary Study in China
Lan Chen, Xi Chen, Shiyu Wu +3
As a phenomenal large language model, ChatGPT has achieved unparalleled success in various real-world tasks and increasingly plays an important role in our daily lives and work. Ho…
High-Dimensional Dynamic Pricing under Non-Stationarity: Learning and Earning with Change-Point Detection
Zifeng Zhao, Feiyu Jiang, Yi Yu +1
We consider a high-dimensional dynamic pricing problem under non-stationarity, where a firm sells products to sequentially arriving consumers that behave according to an unknow…
DP-VAE: Differentially Private Pre-trained Variational Autoencoders
Dihong Jiang, Guojun Zhang, Mahdi Karami +3
Modern machine learning systems achieve great success when trained on large datasets. However, these datasets usually contain sensitive information (e.g. medical records, face imag…
Mitigating Data Heterogeneity in Federated Learning with Data Augmentation
Artur Back de Luca, Guojun Zhang, Xi Chen +1
Federated Learning (FL) is a prominent framework that enables training a centralized model while securing user privacy by fusing local, decentralized models. In this setting, one m…
Robust One Round Federated Learning with Predictive Space Bayesian Inference
Mohsin Hasan, Zehao Zhang, Kaiyang Guo +4
Making predictions robust is an important challenge. A separate challenge in federated learning (FL) is to reduce the number of communication rounds, particularly since doing so re…
Federated Bayesian Neural Regression: A Scalable Global Federated Gaussian Process
Haolin Yu, Kaiyang Guo, Mahdi Karami +3
In typical scenarios where the Federated Learning (FL) framework applies, it is common for clients to have insufficient training data to produce an accurate model. Thus, models tha…
Proportional Fairness in Federated Learning
Guojun Zhang, Saber Malekmohammadi, Xi Chen +1
With the increasingly broad deployment of federated learning (FL) systems in the real world, it is critical but challenging to ensure fairness in FL, i.e. reasonably satisfactory p…
No Weighted-Regret Learning in Adversarial Bandits with Delays
Ilai Bistritz, Zhengyuan Zhou, Xi Chen +2
Consider a scenario where a player chooses an action in each round out of rounds and observes the incurred cost after a delay of rounds. The cost functions and the…
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning
Xi Chen, David Simchi-Levi, Yining Wang
The prevalence of e-commerce has made detailed customers' personal information readily accessible to retailers, and this information has been widely used in pricing decisions. When…
UER: An Open-Source Toolkit for Pre-training Models
Zhe Zhao, Hui Chen, Jinbin Zhang +7
Existing works, including ELMO and BERT, have revealed the importance of pre-training for NLP tasks. While there does not exist a single pre-training model that works best in all c…
Learning to Compose over Tree Structures via POS Tags
Gehui Shen, Zhi-Hong Deng, Ting Huang +1
Recursive Neural Network (RecNN), a type of models which compose words or phrases recursively over syntactic tree structures, has been proven to have superior ability to obtain sen…
TMRT Observations of Carbon-chain molecules in Serpens South 1A
Juan Li, Zhi-Qiang Shen, Junzhi Wang +16
We report Shanghai Tian Ma Radio Telescope detections of several long carbon-chain molecules at C and Ku band, including HC3N, HC5N, HC7N, HC9N, C3S, C6H and C8H toward the starles…