Search Results for author: Huazhong Yang

Found 46 papers, 14 papers with code

Evaluating Quantized Large Language Models

1 code implementation28 Feb 2024 Shiyao Li, Xuefei Ning, Luning Wang, Tengxuan Liu, Xiangsheng Shi, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang

Post-training quantization (PTQ) has emerged as a promising technique to reduce the cost of large language models (LLMs).

Quantization

TaskFlex Solver for Multi-Agent Pursuit via Automatic Curriculum Learning

no code implementations19 Dec 2023 Jiayu Chen, Guosheng Li, Chao Yu, Xinyi Yang, Botian Xu, Huazhong Yang, Yu Wang

In this work, we combine RL and curriculum learning to introduce a flexible solver for multiagent pursuit problems, named TaskFlex Solver (TFS), which is capable of solving multi-agent pursuit problems with diverse and dynamically changing task conditions in both 2-dimensional and 3-dimensional scenarios.

Reinforcement Learning (RL)

A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models

no code implementations12 Dec 2023 Enshu Liu, Xuefei Ning, Huazhong Yang, Yu Wang

In this paper, we propose a unified sampling framework (USF) to study the optional strategies for solver.

MASP: Scalable GNN-based Planning for Multi-Agent Navigation

no code implementations5 Dec 2023 Xinyi Yang, Xinting Yang, Chao Yu, Jiayu Chen, Huazhong Yang, Yu Wang

Besides, to enhance generalization capabilities in scenarios with unseen team sizes, we divide agents into multiple groups, each with a previously trained number of agents.

Reinforcement Learning (RL) Zero-shot Generalization

Active Neural Topological Mapping for Multi-Agent Exploration

no code implementations1 Nov 2023 Xinyi Yang, Yuxiang Yang, Chao Yu, Jiayu Chen, Jingchen Yu, Haibing Ren, Huazhong Yang, Yu Wang

In this paper, we propose Multi-Agent Neural Topological Mapping (MANTM) to improve exploration efficiency and generalization for multi-agent exploration tasks.

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation

1 code implementation28 Jul 2023 Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang

This work aims at decreasing the end-to-end generation latency of large language models (LLMs).

Ada3D : Exploiting the Spatial Redundancy with Adaptive Inference for Efficient 3D Object Detection

no code implementations ICCV 2023 Tianchen Zhao, Xuefei Ning, Ke Hong, Zhongyuan Qiu, Pu Lu, Yali Zhao, Linfeng Zhang, Lipu Zhou, Guohao Dai, Huazhong Yang, Yu Wang

One reason for this high resource consumption is the presence of a large number of redundant background points in Lidar point clouds, resulting in spatial redundancy in both 3D voxel and dense BEV map representations.

3D Object Detection Autonomous Driving +1

OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models

1 code implementation15 Jun 2023 Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang

Diffusion probabilistic models (DPMs) are a new class of generative models that have achieved state-of-the-art generation quality in various domains.

Learning Graph-Enhanced Commander-Executor for Multi-Agent Navigation

1 code implementation8 Feb 2023 Xinyi Yang, Shiyu Huang, Yiwen Sun, Yuxiang Yang, Chao Yu, Wei-Wei Tu, Huazhong Yang, Yu Wang

Goal-conditioned hierarchical reinforcement learning (HRL) provides a promising direction to tackle this challenge by introducing a hierarchical structure to decompose the search space, where the low-level policy predicts primitive actions in the guidance of the goals derived from the high-level policy.

Hierarchical Reinforcement Learning Multi-agent Reinforcement Learning +2

Cross-layer Attention Network for Fine-grained Visual Categorization

no code implementations17 Oct 2022 Ranran Huang, Yu Wang, Huazhong Yang

Learning discriminative representations for subtle localized details plays a significant role in Fine-grained Visual Categorization (FGVC).

Fine-Grained Visual Categorization

CLOSE: Curriculum Learning On the Sharing Extent Towards Better One-shot NAS

1 code implementation16 Jul 2022 Zixuan Zhou, Xuefei Ning, Yi Cai, Jiashu Han, Yiping Deng, Yuhan Dong, Huazhong Yang, Yu Wang

Specifically, we train the supernet with a large sharing extent (an easier curriculum) at the beginning and gradually decrease the sharing extent of the supernet (a harder curriculum).

Neural Architecture Search

Multi-Agent Vulnerability Discovery for Autonomous Driving with Hazard Arbitration Reward

no code implementations12 Dec 2021 Weilin Liu, Ye Mu, Chao Yu, Xuefei Ning, Zhong Cao, Yi Wu, Shuang Liang, Huazhong Yang, Yu Wang

These scenarios indeed correspond to the vulnerabilities of the under-test driving policies, thus are meaningful for their further improvements.

Autonomous Driving Multi-agent Reinforcement Learning

Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems

1 code implementation NeurIPS 2021 Jiayu Chen, Yuanxin Zhang, Yuanfan Xu, Huimin Ma, Huazhong Yang, Jiaming Song, Yu Wang, Yi Wu

We motivate our paradigm through a variational perspective, where the learning objective can be decomposed into two terms: task learning on the current task distribution, and curriculum update to a new task distribution.

Multi-agent Reinforcement Learning

Learning Efficient Multi-Agent Cooperative Visual Exploration

no code implementations12 Oct 2021 Chao Yu, Xinyi Yang, Jiaxuan Gao, Huazhong Yang, Yu Wang, Yi Wu

In this paper, we extend the state-of-the-art single-agent visual navigation method, Active Neural SLAM (ANS), to the multi-agent setting by introducing a novel RL-based planning module, Multi-agent Spatial Planner (MSP). MSP leverages a transformer-based architecture, Spatial-TeamFormer, which effectively captures spatial relations and intra-agent interactions via hierarchical spatial self-attentions.

Reinforcement Learning (RL) Visual Navigation

Enabling Lower-Power Charge-Domain Nonvolatile In-Memory Computing with Ferroelectric FETs

no code implementations2 Feb 2021 Guodong Yin, Yi Cai, Juejian Wu, Zhengyang Duan, Zhenhua Zhu, Yongpan Liu, Yu Wang, Huazhong Yang, Xueqing Li

Compute-in-memory (CiM) is a promising approach to alleviating the memory wall problem for domain-specific applications.

Emerging Technologies

Explore the Potential of CNN Low Bit Training

no code implementations1 Jan 2021 Kai Zhong, Xuefei Ning, Tianchen Zhao, Zhenhua Zhu, Shulin Zeng, Guohao Dai, Yu Wang, Huazhong Yang

Through this dynamic precision framework, we can reduce the bit-width of convolution, which is the most computational cost, while keeping the training process close to the full precision floating-point training.

Quantization

Discovering Robust Convolutional Architecture at Targeted Capacity: A Multi-Shot Approach

1 code implementation22 Dec 2020 Xuefei Ning, Junbo Zhao, Wenshuo Li, Tianchen Zhao, Yin Zheng, Huazhong Yang, Yu Wang

In this paper, considering scenarios with capacity budget, we aim to discover adversarially robust architecture at targeted capacities.

Neural Architecture Search

aw_nas: A Modularized and Extensible NAS framework

1 code implementation25 Nov 2020 Xuefei Ning, Changcheng Tang, Wenshuo Li, Songyi Yang, Tianchen Zhao, Niansong Zhang, Tianyi Lu, Shuang Liang, Huazhong Yang, Yu Wang

Neural Architecture Search (NAS) has received extensive attention due to its capability to discover neural network architectures in an automated manner.

Adversarial Robustness Neural Architecture Search

Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic Scenes

no code implementations18 Nov 2020 Feng Gao, Jincheng Yu, Hao Shen, Yu Wang, Huazhong Yang

Learning depth and ego-motion from unlabeled videos via self-supervision from epipolar projection can improve the robustness and accuracy of the 3D perception and localization of vision-based robots.

Evaluating Efficient Performance Estimators of Neural Architectures

1 code implementation NeurIPS 2021 Xuefei Ning, Changcheng Tang, Wenshuo Li, Zixuan Zhou, Shuang Liang, Huazhong Yang, Yu Wang

Conducting efficient performance estimations of neural architectures is a major challenge in neural architecture search (NAS).

Neural Architecture Search

Physical Adversarial Attack on Vehicle Detector in the Carla Simulator

no code implementations31 Jul 2020 Tong Wu, Xuefei Ning, Wenshuo Li, Ranran Huang, Huazhong Yang, Yu Wang

In this paper, we tackle the issue of physical adversarial examples for object detectors in the wild.

Adversarial Attack

GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks

2 code implementations7 Jul 2020 Guyue Huang, Guohao Dai, Yu Wang, Huazhong Yang

GE-SpMM performs SpMM-like operation on sparse matrices represented in the most common Compressed Sparse Row (CSR) format, so it can be embedded in GNN frameworks with no preprocessing overheads and support general GNN algorithms.

Distributed, Parallel, and Cluster Computing

Exploring the Potential of Low-bit Training of Convolutional Neural Networks

no code implementations4 Jun 2020 Kai Zhong, Xuefei Ning, Guohao Dai, Zhenhua Zhu, Tianchen Zhao, Shulin Zeng, Yu Wang, Huazhong Yang

For training a variety of models on CIFAR-10, using 1-bit mantissa and 2-bit exponent is adequate to keep the accuracy loss within $1\%$.

Quantization

DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation

1 code implementation ECCV 2020 Xuefei Ning, Tianchen Zhao, Wenshuo Li, Peng Lei, Yu Wang, Huazhong Yang

In budgeted pruning, how to distribute the resources across layers (i. e., sparsity allocation) is the key problem.

Enabling Efficient and Flexible FPGA Virtualization for Deep Learning in the Cloud

no code implementations26 Mar 2020 Shulin Zeng, Guohao Dai, Hanbo Sun, Kai Zhong, Guangjun Ge, Kaiyuan Guo, Yu Wang, Huazhong Yang

Currently, the majority of FPGA-based DNN accelerators in the cloud run in a time-division multiplexing way for multiple users sharing a single FPGA, and require re-compilation with $\sim$100 s overhead.

FTT-NAS: Discovering Fault-Tolerant Convolutional Neural Architecture

no code implementations20 Mar 2020 Xuefei Ning, Guangjun Ge, Wenshuo Li, Zhenhua Zhu, Yin Zheng, Xiaoming Chen, Zhen Gao, Yu Wang, Huazhong Yang

By inspecting the discovered architectures, we find that the operation primitives, the weight quantization range, the capacity of the model, and the connection pattern have influences on the fault resilience capability of NN models.

Neural Architecture Search Quantization

Nonparametric Topic Modeling with Neural Inference

no code implementations18 Jun 2018 Xuefei Ning, Yin Zheng, Zhuxi Jiang, Yu Wang, Huazhong Yang, Junzhou Huang

Moreover, we also propose HiTM-VAE, where the document-specific topic distributions are generated in a hierarchical manner.

Topic Models

Hu-Fu: Hardware and Software Collaborative Attack Framework against Neural Networks

no code implementations14 May 2018 Wenshuo Li, Jincheng Yu, Xuefei Ning, Pengjun Wang, Qi Wei, Yu Wang, Huazhong Yang

So, in this paper, we propose a hardware-software collaborative attack framework to inject hidden neural network Trojans, which works as a back-door without requiring manipulating input images and is flexible for different scenarios.

Autonomous Driving Cloud Computing +6

Two-Stream Binocular Network: Accurate Near Field Finger Detection Based On Binocular Images

no code implementations26 Apr 2018 Yi Wei, Guijin Wang, Cairong Zhang, Hengkai Guo, Xinghao Chen, Huazhong Yang

Different from previous works, we propose a new framework, named Two-Stream Binocular Network (TSBnet) to detect fingertips from binocular images directly.

Fingertip Detection Hand Pose Estimation

Interactive Hand Pose Estimation: Boosting accuracy in localizing extended finger joints

no code implementations2 Apr 2018 Cairong Zhang, Guijin Wang, Hengkai Guo, Xinghao Chen, Fei Qiao, Huazhong Yang

In the reality of HMI, joints in fingers stretching out, especially corresponding fingertips, are much more important than other joints.

3D Hand Pose Estimation

A Bayesian Nonparametric Topic Model with Variational Auto-Encoders

no code implementations ICLR 2018 Xuefei Ning, Yin Zheng, Zhuxi Jiang, Yu Wang, Huazhong Yang, Junzhou Huang

On the other hand, different with the other BNP topic models, the inference of iTM-VAE is modeled by neural networks, which has rich representation capacity and can be computed in a simple feed-forward manner.

Representation Learning Retrieval +1

A Survey of FPGA Based Neural Network Accelerator

no code implementations24 Dec 2017 Kaiyuan Guo, Shulin Zeng, Jincheng Yu, Yu Wang, Huazhong Yang

Various FPGA based accelerator designs have been proposed with software and hardware optimization techniques to achieve high speed and energy efficiency.

Hardware Architecture

A Deep Learning Approach for Blind Drift Calibration of Sensor Networks

no code implementations16 Jun 2017 Yuzhi Wang, Anqi Yang, Xiaoming Chen, Pengjun Wang, Yu Wang, Huazhong Yang

Temporal drift of sensory data is a severe problem impacting the data quality of wireless sensor networks (WSNs).

ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA

no code implementations1 Dec 2016 Song Han, Junlong Kang, Huizi Mao, Yiming Hu, Xin Li, Yubin Li, Dongliang Xie, Hong Luo, Song Yao, Yu Wang, Huazhong Yang, William J. Dally

Evaluated on the LSTM for speech recognition benchmark, ESE is 43x and 3x faster than Core i7 5930k CPU and Pascal Titan X GPU implementations.

Quantization speech-recognition +1

Physical Computing With No Clock to Implement the Gaussian Pyramid of SIFT Algorithm

no code implementations11 Aug 2014 Yi Li, Qi Wei, Fei Qiao, Huazhong Yang

In this paper, we propose an active circuit network to implement multi-scale Gaussian filter, which is also called Gaussian Pyramid in image preprocessing.

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