b'Heng Huang'

research

∙ 09/18/2023

Deep Prompt Tuning for Graph Transformers

Graph transformers have gained popularity in various graph-based tasks b...

0 Reza Shirkavand, et al. ∙

research

∙ 08/06/2023

Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining

Multi-party collaborative training, such as distributed learning and fed...

0 Xidong Wu, et al. ∙

research

∙ 07/27/2023

Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillation

The success of automated medical image analysis depends on large-scale a...

0 Jianan Fan, et al. ∙

research

∙ 07/17/2023

AlpaGasus: Training A Better Alpaca with Fewer Data

Large language models (LLMs) obtain instruction-following capability thr...

0 Lichang Chen, et al. ∙

research

∙ 07/16/2023

A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning

Forgetting refers to the loss or deterioration of previously acquired in...

0 Zhenyi Wang, et al. ∙

research

∙ 06/05/2023

InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models

Large language models (LLMs) are instruction followers, but it can be ch...

0 Lichang Chen, et al. ∙

research

∙ 06/01/2023

Prediction of Post-Operative Renal and Pulmonary Complication Using Transformers

Postoperative complications pose a significant challenge in the healthca...

0 Reza Shirkavand, et al. ∙

research

∙ 05/25/2023

Incomplete Multimodal Learning for Complex Brain Disorders Prediction

Recent advancements in the acquisition of various brain data sources hav...

0 Reza Shirkavand, et al. ∙

research

∙ 05/23/2023

Prompting Language-Informed Distribution for Compositional Zero-Shot Learning

The compositional zero-shot learning (CZSL) task aims to recognize unsee...

0 Wentao Bao, et al. ∙

research

∙ 05/03/2023

Backdoor Learning on Sequence to Sequence Models

Backdoor learning has become an emerging research area towards building ...

0 Lichang Chen, et al. ∙

research

∙ 05/03/2023

PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer

Recent studies show that prompt tuning can better leverage the power of ...

0 Lichang Chen, et al. ∙

research

∙ 04/12/2023

Dynamic Voxel Grid Optimization for High-Fidelity RGB-D Supervised Surface Reconstruction

Direct optimization of interpolated features on multi-resolution voxel g...

3 Xiangyu Xu, et al. ∙

research

∙ 04/06/2023

When do you need Chain-of-Thought Prompting for ChatGPT?

Chain-of-Thought (CoT) prompting can effectively elicit complex multi-st...

0 Jiuhai Chen, et al. ∙

research

∙ 02/13/2023

Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems

Bilevel Optimization has witnessed notable progress recently with new em...

0 Junyi Li, et al. ∙

research

∙ 02/13/2023

FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging

Federated learning (FL) is an emerging learning paradigm to tackle massi...

0 Junyi Li, et al. ∙

research

∙ 02/08/2023

Decentralized Riemannian Algorithm for Nonconvex Minimax Problems

The minimax optimization over Riemannian manifolds (possibly nonconvex c...

0 Xidong Wu, et al. ∙

research

∙ 01/10/2023

A Newton-CG based barrier-augmented Lagrangian method for general nonconvex conic optimization

In this paper we consider finding an approximate second-order stationary...

0 Chuan He, et al. ∙

research

∙ 12/09/2022

Adversarial Weight Perturbation Improves Generalization in Graph Neural Network

A lot of theoretical and empirical evidence shows that the flatter local...

0 Yihan Wu, et al. ∙

research

∙ 12/02/2022

Faster Adaptive Federated Learning

Federated learning has attracted increasing attention with the emergence...

0 Xidong Wu, et al. ∙

research

∙ 10/27/2022

BI AVAN: Brain inspired Adversarial Visual Attention Network

Visual attention is a fundamental mechanism in the human brain, and it i...

0 Heng Huang, et al. ∙

research

∙ 10/25/2022

FedGRec: Federated Graph Recommender System with Lazy Update of Latent Embeddings

Recommender systems are widely used in industry to improve user experien...

0 Junyi Li, et al. ∙

research

∙ 10/14/2022

Communication-Efficient Adam-Type Algorithms for Distributed Data Mining

Distributed data mining is an emerging research topic to effectively and...

0 Wenhan Xian, et al. ∙

research

∙ 09/07/2022

Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps

Convolutional Neural Networks (CNNs) compression is crucial to deploying...

15 Alireza Ganjdanesh, et al. ∙

research

∙ 08/11/2022

An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification

Sparsity regularized loss minimization problems play an important role i...

0 Runxue Bao, et al. ∙

research

∙ 08/09/2022

Aesthetic Language Guidance Generation of Images Using Attribute Comparison

With the vigorous development of mobile photography technology, major mo...

0 Xin Jin, et al. ∙

research

∙ 08/09/2022

Aesthetic Attributes Assessment of Images with AMANv2 and DPC-CaptionsV2

Image aesthetic quality assessment is popular during the last decade. Be...

0 Xinghui Zhou, et al. ∙

research

∙ 07/14/2022

Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model

Recently brain networks have been widely adopted to study brain dynamics...

0 Haoteng Tang, et al. ∙

research

∙ 07/08/2022

Balanced Self-Paced Learning for AUC Maximization

Learning to improve AUC performance is an important topic in machine lea...

0 Bin Gu, et al. ∙

research

∙ 06/11/2022

Communication-Efficient Robust Federated Learning with Noisy Labels

Federated learning (FL) is a promising privacy-preserving machine learni...

13 Junyi Li, et al. ∙

research

∙ 05/03/2022

Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction

Bilevel Optimization has witnessed notable progress recently with new em...

7 Junyi Li, et al. ∙

research

∙ 04/23/2022

Distributed Dynamic Safe Screening Algorithms for Sparse Regularization

Distributed optimization has been widely used as one of the most efficie...

0 Runxue Bao, et al. ∙

research

∙ 03/19/2022

Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm

Vertical federated learning (VFL) attracts increasing attention due to t...

0 Qingsong Zhang, et al. ∙

research

∙ 03/18/2022

Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation

Cross-silo federated learning (FL) has attracted much attention in medic...

0 An Xu, et al. ∙

research

∙ 02/10/2022

HNF-Netv2 for Brain Tumor Segmentation using multi-modal MR Imaging

In our previous work, i.e., HNF-Net, high-resolution feature representat...

0 Haozhe Jia, et al. ∙

research

∙ 12/09/2021

A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse

In this paper, we propose a new Hessian inverse free Fully Single Loop A...

3 Junyi Li, et al. ∙

research

∙ 10/29/2021

Adaptive Hierarchical Similarity Metric Learning with Noisy Labels

Deep Metric Learning (DML) plays a critical role in various machine lear...

0 Jiexi Yan, et al. ∙

research

∙ 09/26/2021

AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization

Vertical federated learning (VFL) is an effective paradigm of training t...

0 Qingsong Zhang, et al. ∙

research

∙ 09/18/2021

An Accelerated Variance-Reduced Conditional Gradient Sliding Algorithm for First-order and Zeroth-order Optimization

The conditional gradient algorithm (also known as the Frank-Wolfe algori...

0 Xiyuan Wei, et al. ∙

research

∙ 08/09/2021

PSGR: Pixel-wise Sparse Graph Reasoning for COVID-19 Pneumonia Segmentation in CT Images

Automated and accurate segmentation of the infected regions in computed ...

0 Haozhe Jia, et al. ∙

research

∙ 08/09/2021

Boundary-aware Graph Reasoning for Semantic Segmentation

In this paper, we propose a Boundary-aware Graph Reasoning (BGR) module ...

0 Haoteng Tang, et al. ∙

research

∙ 07/26/2021

Enhanced Bilevel Optimization via Bregman Distance

Bilevel optimization has been widely applied many machine learning probl...

0 Feihu Huang, et al. ∙

research

∙ 07/08/2021

Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform

In this paper, we present Fedlearn-Algo, an open-source privacy preservi...

0 Bo Liu, et al. ∙

research

∙ 06/30/2021

AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization

In the paper, we propose a class of faster adaptive gradient descent asc...

0 Feihu Huang, et al. ∙

research

∙ 06/23/2021

Bregman Gradient Policy Optimization

In this paper, we design a novel Bregman gradient policy optimization fr...

0 Feihu Huang, et al. ∙

research

∙ 06/21/2021

BiAdam: Fast Adaptive Bilevel Optimization Methods

Bilevel optimization recently has attracted increased interest in machin...

0 Feihu Huang, et al. ∙

research

∙ 06/21/2021

Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning

In the paper, we propose an effective and efficient Compositional Federa...

7 Feihu Huang, et al. ∙

research

∙ 06/15/2021

SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients

Adaptive gradient methods have shown excellent performance for solving m...

13 Feihu Huang, et al. ∙

research

∙ 04/09/2021

Learning Sampling Policy for Faster Derivative Free Optimization

Zeroth-order (ZO, also known as derivative-free) methods, which estimate...

0 Zhou Zhai, et al. ∙

research

∙ 03/09/2021

Doubly Contrastive Deep Clustering

Deep clustering successfully provides more effective features than conve...

21 Zhiyuan Dang, et al. ∙

research

∙ 03/04/2021

Data Augmentation for Object Detection via Differentiable Neural Rendering

It is challenging to train a robust object detector when annotated data ...

17 Guanghan Ning, et al. ∙

Heng Huang

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