Search Results for author: Han Cai

Found 27 papers, 18 papers with code

Condition-Aware Neural Network for Controlled Image Generation

no code implementations1 Apr 2024 Han Cai, Muyang Li, Zhuoyang Zhang, Qinsheng Zhang, Ming-Yu Liu, Song Han

In parallel to prior conditional control methods, CAN controls the image generation process by dynamically manipulating the weight of the neural network.

Conditional Image Generation Text-to-Image Generation

DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models

1 code implementation29 Feb 2024 Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Ming-Yu Liu, Kai Li, Song Han

To overcome this dilemma, we observe the high similarity between the input from adjacent diffusion steps and propose displaced patch parallelism, which takes advantage of the sequential nature of the diffusion process by reusing the pre-computed feature maps from the previous timestep to provide context for the current step.

EfficientViT-SAM: Accelerated Segment Anything Model Without Accuracy Loss

1 code implementation7 Feb 2024 Zhuoyang Zhang, Han Cai, Song Han

For the training, we begin with the knowledge distillation from the SAM-ViT-H image encoder to EfficientViT.

Decoder Knowledge Distillation +1

EfficientViT: Lightweight Multi-Scale Attention for High-Resolution Dense Prediction

no code implementations ICCV 2023 Han Cai, Junyan Li, Muyan Hu, Chuang Gan, Song Han

Without performance loss on Cityscapes, our EfficientViT provides up to 8. 8x and 3. 8x GPU latency reduction over SegFormer and SegNeXt, respectively.

Autonomous Driving Super-Resolution

EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

5 code implementations29 May 2022 Han Cai, Junyan Li, Muyan Hu, Chuang Gan, Song Han

Without performance loss on Cityscapes, our EfficientViT provides up to 13. 9$\times$ and 6. 2$\times$ GPU latency reduction over SegFormer and SegNeXt, respectively.

Autonomous Driving Image Classification +7

Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation

1 code implementation CVPR 2022 Yihan Wang, Muyang Li, Han Cai, Wei-Ming Chen, Song Han

Inspired by this finding, we design LitePose, an efficient single-branch architecture for pose estimation, and introduce two simple approaches to enhance the capacity of LitePose, including Fusion Deconv Head and Large Kernel Convs.

Ranked #5 on Multi-Person Pose Estimation on MS COCO (Validation AP metric)

2D Human Pose Estimation Multi-Person Pose Estimation

Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications

no code implementations25 Apr 2022 Han Cai, Ji Lin, Yujun Lin, Zhijian Liu, Haotian Tang, Hanrui Wang, Ligeng Zhu, Song Han

Deep neural networks (DNNs) have achieved unprecedented success in the field of artificial intelligence (AI), including computer vision, natural language processing and speech recognition.

Model Compression Neural Architecture Search +3

Memory-efficient Patch-based Inference for Tiny Deep Learning

no code implementations NeurIPS 2021 Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han

We further propose receptive field redistribution to shift the receptive field and FLOPs to the later stage and reduce the computation overhead.

Image Classification Neural Architecture Search +3

MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning

1 code implementation28 Oct 2021 Ji Lin, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han

We further propose network redistribution to shift the receptive field and FLOPs to the later stage and reduce the computation overhead.

Image Classification Neural Architecture Search +3

Network Augmentation for Tiny Deep Learning

no code implementations ICLR 2022 Han Cai, Chuang Gan, Ji Lin, Song Han

We introduce Network Augmentation (NetAug), a new training method for improving the performance of tiny neural networks.

Data Augmentation Image Classification +2

TinyTL: Reduce Activations, Not Trainable Parameters for Efficient On-Device Learning

1 code implementation NeurIPS 2020 Han Cai, Chuang Gan, Ligeng Zhu, Song Han

Furthermore, combined with feature extractor adaptation, TinyTL provides 7. 3-12. 9x memory saving without sacrificing accuracy compared to fine-tuning the full Inception-V3.

Transfer Learning

APQ: Joint Search for Network Architecture, Pruning and Quantization Policy

1 code implementation CVPR 2020 Tianzhe Wang, Kuan Wang, Han Cai, Ji Lin, Zhijian Liu, Song Han

However, training this quantization-aware accuracy predictor requires collecting a large number of quantized <model, accuracy> pairs, which involves quantization-aware finetuning and thus is highly time-consuming.

Quantization

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

4 code implementations ACL 2020 Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han

To enable low-latency inference on resource-constrained hardware platforms, we propose to design Hardware-Aware Transformers (HAT) with neural architecture search.

Decoder Machine Translation +2

Once for All: Train One Network and Specialize it for Efficient Deployment

1 code implementation ICLR 2020 Han Cai, Chuang Gan, Tianzhe Wang, Zhekai Zhang, Song Han

Most of the traditional approaches either manually design or use neural architecture search (NAS) to find a specialized neural network and train it from scratch for each case, which is computationally expensive and unscalable.

Neural Architecture Search

Once-for-All: Train One Network and Specialize it for Efficient Deployment

10 code implementations26 Aug 2019 Han Cai, Chuang Gan, Tianzhe Wang, Zhekai Zhang, Song Han

On diverse edge devices, OFA consistently outperforms state-of-the-art (SOTA) NAS methods (up to 4. 0% ImageNet top1 accuracy improvement over MobileNetV3, or same accuracy but 1. 5x faster than MobileNetV3, 2. 6x faster than EfficientNet w. r. t measured latency) while reducing many orders of magnitude GPU hours and $CO_2$ emission.

Neural Architecture Search

Design Automation for Efficient Deep Learning Computing

no code implementations24 Apr 2019 Song Han, Han Cai, Ligeng Zhu, Ji Lin, Kuan Wang, Zhijian Liu, Yujun Lin

Moreover, we shorten the design cycle by 200x than previous work, so that we can afford to design specialized neural network models for different hardware platforms.

Quantization

ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

23 code implementations ICLR 2019 Han Cai, Ligeng Zhu, Song Han

We address the high memory consumption issue of differentiable NAS and reduce the computational cost (GPU hours and GPU memory) to the same level of regular training while still allowing a large candidate set.

Image Classification Neural Architecture Search

Layout Design for Intelligent Warehouse by Evolution with Fitness Approximation

no code implementations14 Nov 2018 Haifeng Zhang, Zilong Guo, Han Cai, Chris Wang, Wei-Nan Zhang, Yong Yu, Wenxin Li, Jun Wang

With the rapid growth of the express industry, intelligent warehouses that employ autonomous robots for carrying parcels have been widely used to handle the vast express volume.

Layout Design

Large-scale Interactive Recommendation with Tree-structured Policy Gradient

no code implementations14 Nov 2018 Haokun Chen, Xinyi Dai, Han Cai, Wei-Nan Zhang, Xuejian Wang, Ruiming Tang, Yuzhou Zhang, Yong Yu

Reinforcement learning (RL) has recently been introduced to interactive recommender systems (IRS) because of its nature of learning from dynamic interactions and planning for long-run performance.

Clustering Recommendation Systems +1

MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence

3 code implementations2 Dec 2017 Lianmin Zheng, Jiacheng Yang, Han Cai, Wei-Nan Zhang, Jun Wang, Yong Yu

Unlike previous research platforms on single or multi-agent reinforcement learning, MAgent focuses on supporting the tasks and the applications that require hundreds to millions of agents.

Multi-agent Reinforcement Learning reinforcement-learning +1

Long Text Generation via Adversarial Training with Leaked Information

6 code implementations24 Sep 2017 Jiaxian Guo, Sidi Lu, Han Cai, Wei-Nan Zhang, Yong Yu, Jun Wang

Automatically generating coherent and semantically meaningful text has many applications in machine translation, dialogue systems, image captioning, etc.

Sentence Text Generation

Efficient Architecture Search by Network Transformation

3 code implementations16 Jul 2017 Han Cai, Tianyao Chen, Wei-Nan Zhang, Yong Yu, Jun Wang

Techniques for automatically designing deep neural network architectures such as reinforcement learning based approaches have recently shown promising results.

Image Classification Neural Architecture Search +2

Real-Time Bidding by Reinforcement Learning in Display Advertising

1 code implementation10 Jan 2017 Han Cai, Kan Ren, Wei-Nan Zhang, Kleanthis Malialis, Jun Wang, Yong Yu, Defeng Guo

In this paper, we formulate the bid decision process as a reinforcement learning problem, where the state space is represented by the auction information and the campaign's real-time parameters, while an action is the bid price to set.

reinforcement-learning Reinforcement Learning (RL)

Product-based Neural Networks for User Response Prediction

11 code implementations1 Nov 2016 Yanru Qu, Han Cai, Kan Ren, Wei-Nan Zhang, Yong Yu, Ying Wen, Jun Wang

Predicting user responses, such as clicks and conversions, is of great importance and has found its usage in many Web applications including recommender systems, web search and online advertising.

Click-Through Rate Prediction Recommendation Systems

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