no code implementations • 19 Apr 2024 • Yang Luo, Zangwei Zheng, Zirui Zhu, Yang You
This effectiveness, however, hinges on the appropriate selection of in-context examples, a process that is currently biased towards visual data, overlooking textual information.
no code implementations • 24 Mar 2024 • JunBo Wang, Wenhai Liu, Qiaojun Yu, Yang You, Liu Liu, Weiming Wang, Cewu Lu
Our primary contribution is a Robust Articulation Network (RoArtNet) that is able to predict both joint parameters and affordable points robustly by local feature learning and point tuple voting.
no code implementations • 20 Mar 2024 • Qiaojun Yu, Ce Hao, JunBo Wang, Wenhai Liu, Liu Liu, Yao Mu, Yang You, Hengxu Yan, Cewu Lu
Robotic manipulation in everyday scenarios, especially in unstructured environments, requires skills in pose-aware object manipulation (POM), which adapts robots' grasping and handling according to an object's 6D pose.
1 code implementation • 18 Mar 2024 • Wangbo Zhao, Jiasheng Tang, Yizeng Han, Yibing Song, Kai Wang, Gao Huang, Fan Wang, Yang You
Existing parameter-efficient fine-tuning (PEFT) methods have achieved significant success on vision transformers (ViTs) adaptation by improving parameter efficiency.
1 code implementation • 15 Mar 2024 • Xuanlei Zhao, Shenggan Cheng, Zangwei Zheng, Zheming Yang, Ziming Liu, Yang You
Scaling large models with long sequences across applications like language generation, video generation and multimodal tasks requires efficient sequence parallelism.
no code implementations • 24 Feb 2024 • Yong liu, Zirui Zhu, Chaoyu Gong, Minhao Cheng, Cho-Jui Hsieh, Yang You
While fine-tuning large language models (LLMs) for specific tasks often yields impressive results, it comes at the cost of memory inefficiency due to back-propagation in gradient-based training.
1 code implementation • 23 Feb 2024 • Zirui Zhu, Yong liu, Zangwei Zheng, Huifeng Guo, Yang You
We explore the typical data characteristics and optimization statistics of CTR prediction, revealing a strong positive correlation between the top hessian eigenvalue and feature frequency.
1 code implementation • 20 Feb 2024 • Kai Wang, Zhaopan Xu, Yukun Zhou, Zelin Zang, Trevor Darrell, Zhuang Liu, Yang You
The autoencoder extracts latent representations of a subset of the trained network parameters.
1 code implementation • 7 Feb 2024 • Yuchen Zhang, Tianle Zhang, Kai Wang, Ziyao Guo, Yuxuan Liang, Xavier Bresson, Wei Jin, Yang You
Specifically, we employ a curriculum learning strategy to train expert trajectories with more diverse supervision signals from the original graph, and then effectively transfer the information into the condensed graph with expanding window matching.
1 code implementation • 7 Feb 2024 • Tianle Zhang, Yuchen Zhang, Kun Wang, Kai Wang, Beining Yang, Kaipeng Zhang, Wenqi Shao, Ping Liu, Joey Tianyi Zhou, Yang You
Training on large-scale graphs has achieved remarkable results in graph representation learning, but its cost and storage have raised growing concerns.
no code implementations • 6 Feb 2024 • Tomoyuki Kagaya, Thong Jing Yuan, Yuxuan Lou, Jayashree Karlekar, Sugiri Pranata, Akira Kinose, Koki Oguri, Felix Wick, Yang You
Owing to recent advancements, Large Language Models (LLMs) can now be deployed as agents for increasingly complex decision-making applications in areas including robotics, gaming, and API integration.
no code implementations • 3 Feb 2024 • Cunxiao Du, Jing Jiang, Xu Yuanchen, Jiawei Wu, Sicheng Yu, Yongqi Li, Shenggui Li, Kai Xu, Liqiang Nie, Zhaopeng Tu, Yang You
Speculative decoding is a relatively new decoding framework that leverages small and efficient draft models to reduce the latency of LLMs.
1 code implementation • 29 Jan 2024 • Fuzhao Xue, Zian Zheng, Yao Fu, Jinjie Ni, Zangwei Zheng, Wangchunshu Zhou, Yang You
To help the open-source community have a better understanding of Mixture-of-Experts (MoE) based large language models (LLMs), we train and release OpenMoE, a series of fully open-sourced and reproducible decoder-only MoE LLMs, ranging from 650M to 34B parameters and trained on up to over 1T tokens.
no code implementations • 19 Jan 2024 • Xuanlei Zhao, Shenggan Cheng, Guangyang Lu, Jiarui Fang, Haotian Zhou, Bin Jia, Ziming Liu, Yang You
The experiments demonstrate that AutoChunk can reduce over 80\% of activation memory while maintaining speed loss within 10%, extend max sequence length by 3. 2x to 11. 7x, and outperform state-of-the-art methods by a large margin.
no code implementations • 16 Jan 2024 • Kiyohiro Nakayama, Mikaela Angelina Uy, Yang You, Ke Li, Leonidas Guibas
We introduce ProvNeRF, a model that enriches a traditional NeRF representation by incorporating per-point provenance, modeling likely source locations for each point.
1 code implementation • 15 Jan 2024 • Zelin Zang, Liangyu Li, Yongjie Xu, Chenrui Duan, Kai Wang, Yang You, Yi Sun, Stan Z. Li
MuST integrates the multi-modality information contained in the ST data effectively into a uniform latent space to provide a foundation for all the downstream tasks.
1 code implementation • 23 Dec 2023 • Yang You, Kai Xiong, Zhening Yang, Zhengxiang Huang, Junwei Zhou, Ruoxi Shi, Zhou Fang, Adam W. Harley, Leonidas Guibas, Cewu Lu
We introduce PACE (Pose Annotations in Cluttered Environments), a large-scale benchmark designed to advance the development and evaluation of pose estimation methods in cluttered scenarios.
no code implementations • 17 Dec 2023 • SiQi Liu, Yong-Lu Li, Zhou Fang, Xinpeng Liu, Yang You, Cewu Lu
To explore an effective embedding of HAOI for the machine, we build a new benchmark on 3D HAOI consisting of primitives together with their images and propose a task requiring machines to recover 3D HAOI using primitives from images.
1 code implementation • 30 Nov 2023 • Yanqing Liu, Kai Wang, Wenqi Shao, Ping Luo, Yu Qiao, Mike Zheng Shou, Kaipeng Zhang, Yang You
Visual-language pre-training has achieved remarkable success in many multi-modal tasks, largely attributed to the availability of large-scale image-text datasets.
1 code implementation • 27 Nov 2023 • Jianyang Gu, Saeed Vahidian, Vyacheslav Kungurtsev, Haonan Wang, Wei Jiang, Yang You, Yiran Chen
Observing that key factors for constructing an effective surrogate dataset are representativeness and diversity, we design additional minimax criteria in the generative training to enhance these facets for the generated images of diffusion models.
no code implementations • 5 Nov 2023 • Yang You, Bokui Shen, Congyue Deng, Haoran Geng, Songlin Wei, He Wang, Leonidas Guibas
Remarkably, our model demonstrates robust generalization capabilities to novel and previously unencountered complex tasks without any preliminary demonstrations.
no code implementations • 25 Oct 2023 • Qianxu Wang, Haotong Zhang, Congyue Deng, Yang You, Hao Dong, Yixin Zhu, Leonidas Guibas
Central to SparseDFF is a feature refinement network, optimized with a contrastive loss between views and a point-pruning mechanism for feature continuity.
1 code implementation • 23 Oct 2023 • Yanqing Liu, Jianyang Gu, Kai Wang, Zheng Zhu, Kaipeng Zhang, Wei Jiang, Yang You
Dataset distillation plays a crucial role in creating compact datasets with similar training performance compared with original large-scale ones.
no code implementations • 16 Oct 2023 • Haotian Zhou, Tingkai Liu, Qianli Ma, Jianbo Yuan, PengFei Liu, Yang You, Hongxia Yang
In this paper, we introduce a new dimension in SFT data selection: learnability.
no code implementations • 16 Oct 2023 • Qianli Ma, Haotian Zhou, Tingkai Liu, Jianbo Yuan, PengFei Liu, Yang You, Hongxia Yang
Recent years have seen considerable advancements in multi-step reasoning with Large Language Models (LLMs).
2 code implementations • NeurIPS 2023 • Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, JianXin Li
We validate the proposed SGDD across 9 datasets and achieve state-of-the-art results on all of them: for example, on the YelpChi dataset, our approach maintains 98. 6% test accuracy of training on the original graph dataset with 1, 000 times saving on the scale of the graph.
1 code implementation • 9 Oct 2023 • Ziyao Guo, Kai Wang, George Cazenavette, Hui Li, Kaipeng Zhang, Yang You
The ultimate goal of Dataset Distillation is to synthesize a small synthetic dataset such that a model trained on this synthetic set will perform equally well as a model trained on the full, real dataset.
no code implementations • 6 Oct 2023 • Xinpeng Liu, Yong-Lu Li, Ailing Zeng, Zizheng Zhou, Yang You, Cewu Lu
The goal of motion understanding is to establish a reliable mapping between motion and action semantics, while it is a challenging many-to-many problem.
1 code implementation • 5 Oct 2023 • Yao Lu, Xuguang Chen, Yuchen Zhang, Jianyang Gu, Tianle Zhang, Yifan Zhang, Xiaoniu Yang, Qi Xuan, Kai Wang, Yang You
Dataset Distillation (DD) is a prominent technique that encapsulates knowledge from a large-scale original dataset into a small synthetic dataset for efficient training.
no code implementations • 10 Sep 2023 • Zelin Zang, Hao Luo, Kai Wang, Panpan Zhang, Fan Wang, Stan. Z Li, Yang You
When applied to biological data, DiffAug improves performance by up to 10. 1%, with an average improvement of 5. 8%.
1 code implementation • 21 Aug 2023 • Jianyang Gu, Hao Luo, Kai Wang, Wei Jiang, Yang You, Jian Zhao
In this work, we propose a Color Prompting (CoP) method for data-free continual unsupervised domain adaptive person Re-ID.
Domain Adaptive Person Re-Identification Person Re-Identification +1
1 code implementation • ICCV 2023 • Daquan Zhou, Kai Wang, Jianyang Gu, Xiangyu Peng, Dongze Lian, Yifan Zhang, Yang You, Jiashi Feng
Extensive experiments demonstrate that DQ is able to generate condensed small datasets for training unseen network architectures with state-of-the-art compression ratios for lossless model training.
no code implementations • 19 Aug 2023 • Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Xiaojiang Peng, Yuxuan Liang, Yang Wang
Despite Graph Neural Networks demonstrating considerable promise in graph representation learning tasks, GNNs predominantly face significant issues with over-fitting and over-smoothing as they go deeper as models of computer vision realm.
no code implementations • 4 Aug 2023 • Wangbo Zhao, Kepan Nan, Songyang Zhang, Kai Chen, Dahua Lin, Yang You
Based on this scheme, we develop a novel RVOS method that exploits weak annotations effectively.
2 code implementations • 5 Jul 2023 • Yang Luo, Xiaozhe Ren, Zangwei Zheng, Zhuo Jiang, Xin Jiang, Yang You
Adaptive gradient methods, such as Adam and LAMB, have demonstrated excellent performance in the training of large language models.
2 code implementations • 26 May 2023 • Jianyang Gu, Kai Wang, Wei Jiang, Yang You
Through maintaining the consistency of training gradients and relationship to the past tasks, the summarized samples are more representative for the stream data compared to the original images.
1 code implementation • 22 May 2023 • Chenhui Shen, Liying Cheng, Xuan-Phi Nguyen, Yang You, Lidong Bing
With the recent undeniable advancement in reasoning abilities in large language models (LLMs) like ChatGPT and GPT-4, there is a growing trend for using LLMs on various tasks.
1 code implementation • NeurIPS 2023 • Zangwei Zheng, Xiaozhe Ren, Fuzhao Xue, Yang Luo, Xin Jiang, Yang You
By leveraging this information, we introduce an efficient sequence scheduling technique that groups queries with similar response lengths into micro-batches.
no code implementations • 19 May 2023 • Yang You, Vincent Thomas, Francis Colas, Olivier Buffet
Decentralized partially observable Markov decision processes (Dec-POMDPs) formalize the problem of designing individual controllers for a group of collaborative agents under stochastic dynamics and partial observability.
1 code implementation • 15 May 2023 • Chenhui Shen, Liying Cheng, Xuan-Phi Nguyen, Yang You, Lidong Bing
Pre-trained language models (PLMs) have achieved outstanding achievements in abstractive single-document summarization (SDS).
1 code implementation • Tiny Papers @ ICLR 2023 • Xiao Liu, Jian Zhang, Heng Zhang, Fuzhao Xue, Yang You
We evaluate our model on various dialogue understanding tasks including dialogue relation extraction, dialogue emotion recognition, and dialogue act classification.
Ranked #1 on Dialog Relation Extraction on DialogRE
1 code implementation • CVPR 2023 • Shuo Yang, Zhaopan Xu, Kai Wang, Yang You, Hongxun Yao, Tongliang Liu, Min Xu
As one of the most fundamental techniques in multimodal learning, cross-modal matching aims to project various sensory modalities into a shared feature space.
1 code implementation • CVPR 2023 • Jianyang Gu, Kai Wang, Hao Luo, Chen Chen, Wei Jiang, Yuqiang Fang, Shanghang Zhang, Yang You, Jian Zhao
Neural Architecture Search (NAS) has been increasingly appealing to the society of object Re-Identification (ReID), for that task-specific architectures significantly improve the retrieval performance.
Ranked #8 on Vehicle Re-Identification on VehicleID Large
1 code implementation • ICCV 2023 • Zangwei Zheng, Mingyuan Ma, Kai Wang, Ziheng Qin, Xiangyu Yue, Yang You
To address this challenge, we propose a novel method ZSCL to prevent zero-shot transfer degradation in the continual learning of vision-language models in both feature and parameter space.
1 code implementation • 8 Mar 2023 • Ziheng Qin, Kai Wang, Zangwei Zheng, Jianyang Gu, Xiangyu Peng, Zhaopan Xu, Daquan Zhou, Lei Shang, Baigui Sun, Xuansong Xie, Yang You
To solve this problem, we propose \textbf{InfoBatch}, a novel framework aiming to achieve lossless training acceleration by unbiased dynamic data pruning.
2 code implementations • 8 Mar 2023 • Kai Wang, Jianyang Gu, Daquan Zhou, Zheng Zhu, Wei Jiang, Yang You
To the best of our knowledge, we are the first to achieve higher accuracy on complex architectures than simple ones, such as 75. 1\% with ResNet-18 and 72. 6\% with ConvNet-3 on ten images per class of CIFAR-10.
1 code implementation • 6 Mar 2023 • Yujing Lou, Zelin Ye, Yang You, Nianjuan Jiang, Jiangbo Lu, Weiming Wang, Lizhuang Ma, Cewu Lu
CRIN directly takes the coordinates of points as input and transforms local points into rotation-invariant representations via centrifugal reference frames.
2 code implementations • ICCV 2023 • Yanqing Liu, Jianyang Gu, Kai Wang, Zheng Zhu, Wei Jiang, Yang You
Although there are various matching objectives, currently the strategy for selecting original images is limited to naive random sampling.
no code implementations • 27 Feb 2023 • Yang You, Vincent Thomas, Francis Colas, Rachid Alami, Olivier Buffet
Based on this, we propose two contributions: 1) an approach to automatically generate an uncertain human behavior (a policy) for each given objective function while accounting for possible robot behaviors; and 2) a robot planning algorithm that is robust to the above-mentioned uncertainties and relies on solving a partially observable Markov decision process (POMDP) obtained by reasoning on a distribution over human behaviors.
1 code implementation • 6 Feb 2023 • Yuliang Liu, Shenggui Li, Jiarui Fang, Yanjun Shao, Boyuan Yao, Yang You
To address these challenges, we introduce a system that can jointly optimize distributed execution and gradient checkpointing plans.
1 code implementation • 30 Jan 2023 • Fuzhao Xue, Valerii Likhosherstov, Anurag Arnab, Neil Houlsby, Mostafa Dehghani, Yang You
However, most standard neural networks have a fixed function type and computation budget regardless of the sample's nature or difficulty.
1 code implementation • 1 Jan 2023 • Huaizheng Zhang, Yuanming Li, Wencong Xiao, Yizheng Huang, Xing Di, Jianxiong Yin, Simon See, Yong Luo, Chiew Tong Lau, Yang You
The vision of this paper is to provide a more comprehensive and practical benchmark study for MIG in order to eliminate the need for tedious manual benchmarking and tuning efforts.
1 code implementation • 30 Dec 2022 • Tom Young, Yunan Chen, Yang You
Learning to predict masked tokens in a sequence has been shown to be a helpful pretraining objective for powerful language models such as PaLM2.
no code implementations • 29 Dec 2022 • Xin Hu, Lingling Zhang, Jun Liu, Jinfu Fan, Yang You, Yaqiang Wu
These lead to the fact that traditional data-driven detection model is not suitable for diagrams.
2 code implementations • 10 Dec 2022 • Haichen Huang, Jiarui Fang, Hongxin Liu, Shenggui Li, Yang You
To reduce GPU memory usage, memory partitioning, and memory offloading have been proposed.
2 code implementations • 24 Nov 2022 • Yang You, Wenhao He, Jin Liu, Hongkai Xiong, Weiming Wang, Cewu Lu
We introduce a novel method, CPPF++, designed for sim-to-real pose estimation.
1 code implementation • 24 Nov 2022 • Yang You, Zhuochen Miao, Kai Xiong, Weiming Wang, Cewu Lu
In contrast, our proposed OneLoc algorithm efficiently finds the object center and bounding box size by a special voting scheme.
1 code implementation • 26 Oct 2022 • Chenhui Shen, Liying Cheng, Lidong Bing, Yang You, Luo Si
A wide range of control perspectives have been explored in controllable text generation.
no code implementations • 6 Sep 2022 • Jiangsu Du, Ziming Liu, Jiarui Fang, Shenggui Li, Yongbin Li, Yutong Lu, Yang You
Although the AI community has expanded the model scale to the trillion parameter level, the practical deployment of 10-100 billion parameter models is still uncertain due to the latency, throughput, and memory constraints.
1 code implementation • 18 Aug 2022 • Zangwei Zheng, Xiangyu Yue, Kai Wang, Yang You
In this paper, we propose a novel approach DoPrompt based on prompt learning to embed the knowledge of source domains in domain prompts for target domain prediction.
1 code implementation • 8 Aug 2022 • Jiarui Fang, Geng Zhang, Jiatong Han, Shenggui Li, Zhengda Bian, Yongbin Li, Jin Liu, Yang You
Deep learning recommendation models (DLRMs) have been widely applied in Internet companies.
2 code implementations • 19 Jul 2022 • Yizheng Huang, Huaizheng Zhang, Yuanming Li, Chiew Tong Lau, Yang You
In data-centric AI, active learning (AL) plays a vital role, but current AL tools 1) require users to manually select AL strategies, and 2) can not perform AL tasks efficiently.
1 code implementation • 28 May 2022 • Jianfei Yang, Xiangyu Peng, Kai Wang, Zheng Zhu, Jiashi Feng, Lihua Xie, Yang You
Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an unlabeled target domain supervised by a black-box predictor trained on a source domain.
1 code implementation • 23 May 2022 • Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Jiankang Deng, Xinchao Wang, Hakan Bilen, Yang You
Firstly, randomly masked face images are used to train the reconstruction module in FaceMAE.
no code implementations • 21 May 2022 • Fuzhao Xue, Jianghai Chen, Aixin Sun, Xiaozhe Ren, Zangwei Zheng, Xiaoxin He, Yongming Chen, Xin Jiang, Yang You
In this paper, we revisit these conventional configurations.
Ranked #103 on Image Classification on ImageNet
1 code implementation • 30 Apr 2022 • Kai Wang, Xiangyu Peng, Shuo Yang, Jianfei Yang, Zheng Zhu, Xinchao Wang, Yang You
This paradigm, however, is prone to significant degeneration under heavy label noise, as the number of clean samples is too small for conventional methods to behave well.
1 code implementation • 13 Apr 2022 • Zangwei Zheng, Pengtai Xu, Xuan Zou, Da Tang, Zhen Li, Chenguang Xi, Peng Wu, Leqi Zou, Yijie Zhu, Ming Chen, Xiangzhuo Ding, Fuzhao Xue, Ziheng Qin, Youlong Cheng, Yang You
Our experiments show that previous scaling rules fail in the training of CTR prediction neural networks.
1 code implementation • CVPR 2022 • Wangbo Zhao, Kai Wang, Xiangxiang Chu, Fuzhao Xue, Xinchao Wang, Yang You
Text-based video segmentation aims to segment the target object in a video based on a describing sentence.
Ranked #10 on Referring Expression Segmentation on A2D Sentences
Optical Flow Estimation Referring Expression Segmentation +4
1 code implementation • CVPR 2022 • Yang You, Ruoxi Shi, Weiming Wang, Cewu Lu
Drawing inspirations from traditional point pair features (PPFs), in this paper, we design a novel Category-level PPF (CPPF) voting method to achieve accurate, robust and generalizable 9D pose estimation in the wild.
Ranked #8 on 6D Pose Estimation using RGBD on REAL275
2 code implementations • CVPR 2022 • Yong liu, Siqi Mai, Xiangning Chen, Cho-Jui Hsieh, Yang You
Recently, Sharpness-Aware Minimization (SAM), which connects the geometry of the loss landscape and generalization, has demonstrated significant performance boosts on training large-scale models such as vision transformers.
2 code implementations • CVPR 2022 • Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Shuo Yang, Shuo Wang, Guan Huang, Hakan Bilen, Xinchao Wang, Yang You
Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one.
1 code implementation • 2 Mar 2022 • Shenggan Cheng, Xuanlei Zhao, Guangyang Lu, Jiarui Fang, Zhongming Yu, Tian Zheng, Ruidong Wu, Xiwen Zhang, Jian Peng, Yang You
In this work, we present FastFold, an efficient implementation of AlphaFold for both training and inference.
1 code implementation • 24 Feb 2022 • Jie Zhu, Shenggui Li, Yang You
In this paper, we proposed Sky Computing, a load-balanced model parallelism framework to adaptively allocate the weights to devices.
1 code implementation • CVPR 2022 • Xiangyu Peng, Kai Wang, Zheng Zhu, Mang Wang, Yang You
For high performance Siamese representation learning, one of the keys is to design good contrastive pairs.
no code implementations • 26 Jan 2022 • Fuzhao Xue, Xiaoxin He, Xiaozhe Ren, Yuxuan Lou, Yang You
Mixture-of-experts (MoE) is a powerful sparse architecture including multiple experts.
no code implementations • 21 Nov 2021 • Yang You, Chengkun Li, Yujing Lou, Zhoujun Cheng, Liangwei Li, Lizhuang Ma, Weiming Wang, Cewu Lu
Pixel-level 2D object semantic understanding is an important topic in computer vision and could help machine deeply understand objects (e. g. functionality and affordance) in our daily life.
no code implementations • 1 Nov 2021 • Xiaoxin He, Fuzhao Xue, Xiaozhe Ren, Yang You
Deep learning have achieved promising results on a wide spectrum of AI applications.
1 code implementation • 28 Oct 2021 • Shenggui Li, Hongxin Liu, Zhengda Bian, Jiarui Fang, Haichen Huang, Yuliang Liu, Boxiang Wang, Yang You
The success of Transformer models has pushed the deep learning model scale to billions of parameters.
1 code implementation • Findings (ACL) 2022 • Chenhui Shen, Liying Cheng, Ran Zhou, Lidong Bing, Yang You, Luo Si
A more useful text generator should leverage both the input text and the control signal to guide the generation, which can only be built with a deep understanding of the domain knowledge.
no code implementations • 29 Sep 2021 • Yong liu, Siqi Mai, Xiangning Chen, Cho-Jui Hsieh, Yang You
Large-batch training is an important direction for distributed machine learning, which can improve the utilization of large-scale clusters and therefore accelerate the training process.
no code implementations • 17 Sep 2021 • Yang You, Vincent Thomas, Francis Colas, Olivier Buffet
This paper looks at solving collaborative planning problems formalized as Decentralized POMDPs (Dec-POMDPs) by searching for Nash equilibria, i. e., situations where each agent's policy is a best response to the other agents' (fixed) policies.
no code implementations • 5 Sep 2021 • Yuxuan Lou, Fuzhao Xue, Zangwei Zheng, Yang You
Mixture-of-Experts (MoE), a conditional computation architecture, achieved promising performance by scaling local module (i. e. feed-forward network) of transformer.
1 code implementation • 12 Aug 2021 • Jiarui Fang, Zilin Zhu, Shenggui Li, Hui Su, Yang Yu, Jie zhou, Yang You
PatrickStar uses the CPU-GPU heterogeneous memory space to store the model data.
no code implementations • 8 Aug 2021 • Zhengda Bian, Shenggui Li, Wei Wang, Yang You
ONES automatically manages the elasticity of each job based on the training batch size, so as to maximize GPU utilization and improve scheduling efficiency.
1 code implementation • 25 Jul 2021 • Fuzhao Xue, Ziji Shi, Futao Wei, Yuxuan Lou, Yong liu, Yang You
To achieve better performance with fewer trainable parameters, recent methods are proposed to go shallower by parameter sharing or model compressing along with the depth.
Ranked #663 on Image Classification on ImageNet
no code implementations • ICLR 2022 • Yong liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You
Current methods usually use extensive data augmentation to increase the batch size, but we found the performance gain with data augmentation decreases as batch size increases, and data augmentation will become insufficient after certain point.
no code implementations • 30 May 2021 • Zhengda Bian, Qifan Xu, Boxiang Wang, Yang You
Our work is the first to introduce a 3-dimensional model parallelism for expediting huge language models.
no code implementations • 30 May 2021 • Boxiang Wang, Qifan Xu, Zhengda Bian, Yang You
It increases efficiency by reducing communication overhead and lowers the memory required for each GPU.
no code implementations • 26 May 2021 • Shenggui Li, Fuzhao Xue, Chaitanya Baranwal, Yongbin Li, Yang You
That is, with sparse attention, our sequence parallelism enables us to train transformer with infinite long sequence.
1 code implementation • CVPR 2022 • Kai Wang, Shuo Wang, Panpan Zhang, Zhipeng Zhou, Zheng Zhu, Xiaobo Wang, Xiaojiang Peng, Baigui Sun, Hao Li, Yang You
This method adopts Dynamic Class Pool (DCP) for storing and updating the identities features dynamically, which could be regarded as a substitute for the FC layer.
Ranked #1 on Face Verification on IJB-C (training dataset metric)
1 code implementation • 12 Apr 2021 • Qifan Xu, Shenggui Li, Chaoyu Gong, Yang You
However, due to memory constraints, model parallelism must be utilized to host large models that would otherwise not fit into the memory of a single device.
1 code implementation • CVPR 2021 • Ruoxi Shi, Zhengrong Xue, Yang You, Cewu Lu
In this paper, we propose an unsupervised aligned keypoint detector, Skeleton Merger, which utilizes skeletons to reconstruct objects.
2 code implementations • 24 Feb 2021 • Yang You, Yujing Lou, Ruoxi Shi, Qi Liu, Yu-Wing Tai, Lizhuang Ma, Weiming Wang, Cewu Lu
Spherical Voxel Convolution and Point Re-sampling are proposed to extract rotation invariant features for each point.
1 code implementation • CVPR 2022 • Yang You, Wenhai Liu, Yanjie Ze, Yong-Lu Li, Weiming Wang, Cewu Lu
Keypoint detection is an essential component for the object registration and alignment.
1 code implementation • CVPR 2022 • Yang You, Zelin Ye, Yujing Lou, Chengkun Li, Yong-Lu Li, Lizhuang Ma, Weiming Wang, Cewu Lu
In the work, we disentangle the direct offset into Local Canonical Coordinates (LCC), box scales and box orientations.
no code implementations • 30 Oct 2020 • Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc Le, Yang You, Sameer Kumar
EfficientNets are a family of state-of-the-art image classification models based on efficiently scaled convolutional neural networks.
no code implementations • 19 Oct 2020 • Yuanhao Xiong, Xuanqing Liu, Li-Cheng Lan, Yang You, Si Si, Cho-Jui Hsieh
For end-to-end efficiency, unlike previous work that assumes random hyperparameter tuning, which over-emphasizes the tuning time, we propose to evaluate with a bandit hyperparameter tuning strategy.
no code implementations • 18 Sep 2020 • Le Xiao, Xiaoting Li, Datao Gong, Jinghong Chen, Di Guo, Huiqin He, Suen Hou, Guangming Huang, Chonghan Liu, Tiankuan Liu, Xiangming Sun, Ping-Kun Teng, Bozorgmehr Vosooghi, Annie C. Xiang, Jingbo Ye, Yang You, Zhiheng Zuo
In this paper, we present the design and test results of LOCx2, a transmitter ASIC for the ATLAS Liquid Argon Calorimeter trigger upgrade.
Instrumentation and Detectors
no code implementations • 15 Jun 2020 • Yang You, Yuhui Wang, huan zhang, Zhao Zhang, James Demmel, Cho-Jui Hsieh
For the first time we scale the batch size on ImageNet to at least a magnitude larger than all previous work, and provide detailed studies on the performance of many state-of-the-art optimization schemes under this setting.
1 code implementation • 20 Apr 2020 • Yang You, Chengkun Li, Yujing Lou, Zhoujun Cheng, Lizhuang Ma, Cewu Lu, Weiming Wang
Visual semantic correspondence is an important topic in computer vision and could help machine understand objects in our daily life.
1 code implementation • CVPR 2020 • Yang You, Yujing Lou, Chengkun Li, Zhoujun Cheng, Liangwei Li, Lizhuang Ma, Weiming Wang, Cewu Lu
Detecting 3D objects keypoints is of great interest to the areas of both graphics and computer vision.
1 code implementation • ECCV 2020 • Yujing Lou, Yang You, Chengkun Li, Zhoujun Cheng, Liangwei Li, Lizhuang Ma, Weiming Wang, Cewu Lu
Semantic understanding of 3D objects is crucial in many applications such as object manipulation.
1 code implementation • 20 Nov 2019 • Ruobing Han, James Demmel, Yang You
Our experimental results show that for many applications, APS can train state-of-the-art models by 8-bit gradients with no or only a tiny accuracy loss (<0. 05%).
24 code implementations • ICLR 2020 • Yang You, Jing Li, Sashank Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, Cho-Jui Hsieh
In this paper, we first study a principled layerwise adaptation strategy to accelerate training of deep neural networks using large mini-batches.
Ranked #11 on Question Answering on SQuAD1.1 dev (F1 metric)
1 code implementation • 24 Jan 2019 • Yang You, Liangwei Li, Baisong Guo, Weiming Wang, Cewu Lu
Deep reinforcement learning (DRL) has gained a lot of attention in recent years, and has been proven to be able to play Atari games and Go at or above human levels.
1 code implementation • 24 Jan 2019 • Yang You, Jonathan Hseu, Chris Ying, James Demmel, Kurt Keutzer, Cho-Jui Hsieh
LEGW enables Sqrt Scaling scheme to be useful in practice and as a result we achieve much better results than the Linear Scaling learning rate scheme.
1 code implementation • 23 Nov 2018 • Yang You, Yujing Lou, Qi Liu, Yu-Wing Tai, Lizhuang Ma, Cewu Lu, Weiming Wang
Point cloud analysis without pose priors is very challenging in real applications, as the orientations of point clouds are often unknown.
no code implementations • ICLR 2018 • Boris Ginsburg, Igor Gitman, Yang You
Using LARS, we scaled AlexNet and ResNet-50 to a batch size of 16K.
1 code implementation • 14 Sep 2017 • Yang You, Zhao Zhang, Cho-Jui Hsieh, James Demmel, Kurt Keutzer
If we can make full use of the supercomputer for DNN training, we should be able to finish the 90-epoch ResNet-50 training in one minute.
12 code implementations • 13 Aug 2017 • Yang You, Igor Gitman, Boris Ginsburg
Using LARS, we scaled Alexnet up to a batch size of 8K, and Resnet-50 to a batch size of 32K without loss in accuracy.
no code implementations • NeurIPS 2016 • Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, James Demmel, Cho-Jui Hsieh
n this paper, we propose and study an Asynchronous parallel Greedy Coordinate Descent (Asy-GCD) algorithm for minimizing a smooth function with bounded constraints.