Search Results for author: Jialin Li

Found 9 papers, 1 papers with code

FedLPA: Personalized One-shot Federated Learning with Layer-Wise Posterior Aggregation

no code implementations30 Sep 2023 Xiang Liu, Liangxi Liu, Feiyang Ye, Yunheng Shen, Xia Li, Linshan Jiang, Jialin Li

Efficiently aggregating trained neural networks from local clients into a global model on a server is a widely researched topic in federated learning.

Federated Learning

Can the Query-based Object Detector Be Designed with Fewer Stages?

no code implementations28 Sep 2023 Jialin Li, WeiFu Fu, Yuhuan Lin, Qiang Nie, Yong liu

Query-based object detectors have made significant advancements since the publication of DETR.

Semi-supervised Domain Adaptation with Inter and Intra-domain Mixing for Semantic Segmentation

no code implementations30 Aug 2023 WeiFu Fu, Qiang Nie, Jialin Li, Yuhuan Lin, Kai Wu, Yong liu, Chengjie Wang

Instead of solely using the scarce labeled data for supervision, we propose a novel SSDA framework that incorporates both inter-domain mixing and intra-domain mixing, where inter-domain mixing mitigates the source-target domain gap and intra-domain mixing enriches the available target domain information.

Semantic Segmentation Semi-supervised Domain Adaptation +1

A Survey on Personalized Affective Computing in Human-Machine Interaction

no code implementations1 Apr 2023 Jialin Li, Alia Waleed, Hanan Salam

In this paper, we discuss the need for personalization in affective and personality computing (hereinafter referred to as affective computing).

TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation

no code implementations1 Feb 2023 Ziji Shi, Le Jiang, Ang Wang, Jie Zhang, Xianyan Jia, Yong Li, Chencan Wu, Jialin Li, Wei Lin

However, finding a suitable model parallel schedule for an arbitrary neural network is a non-trivial task due to the exploding search space.

MapQA: A Dataset for Question Answering on Choropleth Maps

1 code implementation15 Nov 2022 Shuaichen Chang, David Palzer, Jialin Li, Eric Fosler-Lussier, Ningchuan Xiao

Our experimental results show that V-MODEQA has better overall performance and robustness on MapQA than the state-of-the-art ChartQA and VQA algorithms by capturing the unique properties in map question answering.

Question Answering Visual Question Answering

Harmonia: Near-Linear Scalability for Replicated Storage with In-Network Conflict Detection

no code implementations18 Apr 2019 Hang Zhu, Zhihao Bai, Jialin Li, Ellis Michael, Dan Ports, Ion Stoica, Xin Jin

Experimental results show that Harmonia improves the throughput of these protocols by up to 10X for a replication factor of 10, providing near-linear scalability up to the limit of our testbed.

Distributed, Parallel, and Cluster Computing

Guaranteed Simultaneous Asymmetric Tensor Decomposition via Orthogonalized Alternating Least Squares

no code implementations25 May 2018 Furong Huang, Jialin Li, Xuchen You

We propose a Slicing Initialized Alternating Subspace Iteration (s-ASI) method that is guaranteed to recover top $r$ components ($\epsilon$-close) simultaneously for (a)symmetric tensors almost surely under the noiseless case (with high probability for a bounded noise) using $O(\log(\log \frac{1}{\epsilon}))$ steps of tensor subspace iterations.

Tensor Decomposition

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