b'Li Shen'

research

∙ 09/20/2023

Are Large Language Models Really Robust to Word-Level Perturbations?

The swift advancement in the scale and capabilities of Large Language Mo...

0 Haoyu Wang, et al. ∙

research

∙ 09/18/2023

FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data

Federated learning is an emerging distributed machine learning method, e...

0 Hao Sun, et al. ∙

research

∙ 08/31/2023

Continual Learning From a Stream of APIs

Continual learning (CL) aims to learn new tasks without forgetting previ...

0 Enneng Yang, et al. ∙

research

∙ 08/30/2023

MerA: Merging Pretrained Adapters For Few-Shot Learning

Adapter tuning, which updates only a few parameters, has become a mainst...

0 Shwai He, et al. ∙

research

∙ 08/24/2023

Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?

The multimedia community has shown a significant interest in perceiving ...

0 Fei Wang, et al. ∙

research

∙ 08/24/2023

Master-slave Deep Architecture for Top-K Multi-armed Bandits with Non-linear Bandit Feedback and Diversity Constraints

We propose a novel master-slave architecture to solve the top-K combinat...

0 Hanchi Huang, et al. ∙

research

∙ 08/18/2023

Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent

Stochastic gradient descent (SGD) performed in an asynchronous manner pl...

0 Xiaoge Deng, et al. ∙

research

∙ 08/16/2023

DFedADMM: Dual Constraints Controlled Model Inconsistency for Decentralized Federated Learning

To address the communication burden issues associated with federated lea...

0 Qinglun Li, et al. ∙

research

∙ 08/01/2023

LGViT: Dynamic Early Exiting for Accelerating Vision Transformer

Recently, the efficient deployment and acceleration of powerful vision t...

0 Guanyu Xu, et al. ∙

research

∙ 07/30/2023

Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup

Adaptive optimization has achieved notable success for distributed learn...

0 Yan Sun, et al. ∙

research

∙ 07/25/2023

High-Resolution Volumetric Reconstruction for Clothed Humans

We present a novel method for reconstructing clothed humans from a spars...

0 Sicong Tang, et al. ∙

research

∙ 07/17/2023

GBT: Two-stage transformer framework for non-stationary time series forecasting

This paper shows that time series forecasting Transformer (TSFT) suffers...

0 Li Shen, 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

∙ 07/14/2023

Boosting Backdoor Attack with A Learnable Poisoning Sample Selection Strategy

Data-poisoning based backdoor attacks aim to insert backdoor into models...

0 Zihao Zhu, et al. ∙

research

∙ 06/30/2023

Systematic Investigation of Sparse Perturbed Sharpness-Aware Minimization Optimizer

Deep neural networks often suffer from poor generalization due to comple...

0 Peng Mi, et al. ∙

research

∙ 06/25/2023

Enhancing Adversarial Training via Reweighting Optimization Trajectory

Despite the fact that adversarial training has become the de facto metho...

0 Tianjin Huang, et al. ∙

research

∙ 06/19/2023

FDNet: Focal Decomposed Network for Efficient, Robust and Practical Time Series Forecasting

This paper presents FDNet: a Focal Decomposed Network for efficient, rob...

0 Li Shen, et al. ∙

research

∙ 06/09/2023

Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization

Federated learning (FL) is a distributed paradigm that coordinates massi...

0 Yan Sun, et al. ∙

research

∙ 06/08/2023

CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification

Although graph neural networks (GNNs) have achieved impressive achieveme...

0 Nan Yin, et al. ∙

research

∙ 06/08/2023

Instructed Diffuser with Temporal Condition Guidance for Offline Reinforcement Learning

Recent works have shown the potential of diffusion models in computer vi...

0 Jifeng Hu, et al. ∙

research

∙ 05/30/2023

Dynamic Sparsity Is Channel-Level Sparsity Learner

Sparse training has received an upsurging interest in machine learning d...

1 Lu Yin, et al. ∙

research

∙ 05/30/2023

Are Large Kernels Better Teachers than Transformers for ConvNets?

This paper reveals a new appeal of the recently emerged large-kernel Con...

4 Tianjin Huang, et al. ∙

research

∙ 05/29/2023

Compact Real-time Radiance Fields with Neural Codebook

Reconstructing neural radiance fields with explicit volumetric represent...

0 Lingzhi Li, et al. ∙

research

∙ 05/28/2023

Learning to Learn from APIs: Black-Box Data-Free Meta-Learning

Data-free meta-learning (DFML) aims to enable efficient learning of new ...

0 Zixuan Hu, 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

∙ 05/25/2023

Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning

Data augmentation (DA) is a crucial technique for enhancing the sample e...

0 Guozheng Ma, et al. ∙

research

∙ 05/24/2023

Towards More Suitable Personalization in Federated Learning via Decentralized Partial Model Training

Personalized federated learning (PFL) aims to produce the greatest perso...

0 Yifan Shi, et al. ∙

research

∙ 05/19/2023

Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape

In federated learning (FL), a cluster of local clients are chaired under...

0 Yan Sun, et al. ∙

research

∙ 05/16/2023

Prompt-Tuning Decision Transformer with Preference Ranking

Prompt-tuning has emerged as a promising method for adapting pre-trained...

0 Shengchao Hu, et al. ∙

research

∙ 05/10/2023

DaGAN++: Depth-Aware Generative Adversarial Network for Talking Head Video Generation

Predominant techniques on talking head generation largely depend on 2D i...

3 Fa-Ting Hong, et al. ∙

research

∙ 05/02/2023

Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing

Federated learning (FL) is a collaborative learning paradigm for decentr...

22 Yifan Shi, et al. ∙

research

∙ 05/01/2023

Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy

To defend the inference attacks and mitigate the sensitive information l...

3 Yifan Shi, et al. ∙

research

∙ 04/24/2023

Enhancing Fine-Tuning Based Backdoor Defense with Sharpness-Aware Minimization

Backdoor defense, which aims to detect or mitigate the effect of malicio...

0 Mingli Zhu, et al. ∙

research

∙ 04/10/2023

Evaluate Geometry of Radiance Field with Low-frequency Color Prior

Radiance field is an effective representation of 3D scenes, which has be...

0 Qihang Fang, et al. ∙

research

∙ 04/07/2023

On Efficient Training of Large-Scale Deep Learning Models: A Literature Review

The field of deep learning has witnessed significant progress, particula...

0 Li Shen, et al. ∙

research

∙ 04/04/2023

Quantum Imitation Learning

Despite remarkable successes in solving various complex decision-making ...

0 Zhihao Cheng, et al. ∙

research

∙ 03/24/2023

Towards Making the Most of ChatGPT for Machine Translation

ChatGPT shows remarkable capabilities for machine translation (MT). Seve...

0 Keqin Peng, et al. ∙

research

∙ 03/23/2023

Robust Generalization against Photon-Limited Corruptions via Worst-Case Sharpness Minimization

Robust generalization aims to tackle the most challenging data distribut...

0 Zhuo Huang, et al. ∙

research

∙ 03/20/2023

Make Landscape Flatter in Differentially Private Federated Learning

To defend the inference attacks and mitigate the sensitive information l...

0 Yifan Shi, et al. ∙

research

∙ 03/20/2023

Architecture, Dataset and Model-Scale Agnostic Data-free Meta-Learning

The goal of data-free meta-learning is to learn useful prior knowledge f...

0 Zixuan Hu, et al. ∙

research

∙ 03/15/2023

Visual Prompt Based Personalized Federated Learning

As a popular paradigm of distributed learning, personalized federated le...

0 Guanghao Li, et al. ∙

research

∙ 03/07/2023

Graph Decision Transformer

Offline reinforcement learning (RL) is a challenging task, whose objecti...

0 Shengchao Hu, et al. ∙

research

∙ 03/07/2023

SGDA: Towards 3D Universal Pulmonary Nodule Detection via Slice Grouped Domain Attention

Lung cancer is the leading cause of cancer death worldwide. The best sol...

0 Rui Xu, et al. ∙

research

∙ 03/01/2023

AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks

Sharpness aware minimization (SAM) optimizer has been extensively explor...

0 Hao Sun, et al. ∙

research

∙ 02/24/2023

Subspace based Federated Unlearning

Federated learning (FL) enables multiple clients to train a machine lear...

0 Guanghao Li, et al. ∙

research

∙ 02/21/2023

Fusion of Global and Local Knowledge for Personalized Federated Learning

Personalized federated learning, as a variant of federated learning, tra...

0 Tiansheng Huang, et al. ∙

research

∙ 02/21/2023

FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy

Federated learning is an emerging distributed machine learning framework...

0 Yan Sun, et al. ∙

research

∙ 02/18/2023

Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE

This technical report briefly describes our JDExplore d-team's submissio...

15 Qihuang Zhong, et al. ∙

research

∙ 02/15/2023

FedABC: Targeting Fair Competition in Personalized Federated Learning

Federated learning aims to collaboratively train models without accessin...

0 Dui Wang, et al. ∙

research

∙ 02/08/2023

Improving the Model Consistency of Decentralized Federated Learning

To mitigate the privacy leakages and communication burdens of Federated ...

10 Yifan Shi, et al. ∙

Li Shen

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