Search Results for author: Hao Yu

Found 43 papers, 11 papers with code

Lexicon-Based Graph Convolutional Network for Chinese Word Segmentation

no code implementations Findings (EMNLP) 2021 Kaiyu Huang, Hao Yu, Junpeng Liu, Wei Liu, Jingxiang Cao, Degen Huang

Experimental results on five benchmarks and four cross-domain datasets show the lexicon-based graph convolutional network successfully captures the information of candidate words and helps to improve performance on the benchmarks (Bakeoff-2005 and CTB6) and the cross-domain datasets (SIGHAN-2010).

Chinese Word Segmentation

Online Camera-to-ground Calibration for Autonomous Driving

no code implementations30 Mar 2023 Binbin Li, Xinyu Du, Yao Hu, Hao Yu, Wende Zhang

Online camera-to-ground calibration is to generate a non-rigid body transformation between the camera and the road surface in a real-time manner.

Autonomous Driving

Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration

1 code implementation CVPR 2023 Zheng Qin, Hao Yu, Changjian Wang, Yuxing Peng, Kai Xu

We first design a local spatial consistency measure over the deformation graph of the point cloud, which evaluates the spatial compatibility only between the correspondences in the vicinity of a graph node.

Point Cloud Registration

Rotation-Invariant Transformer for Point Cloud Matching

1 code implementation CVPR 2023 Hao Yu, Zheng Qin, Ji Hou, Mahdi Saleh, Dongsheng Li, Benjamin Busam, Slobodan Ilic

To this end, we introduce RoITr, a Rotation-Invariant Transformer to cope with the pose variations in the point cloud matching task.

Data Augmentation

RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration

no code implementations27 Sep 2022 Hao Yu, Ji Hou, Zheng Qin, Mahdi Saleh, Ivan Shugurov, Kai Wang, Benjamin Busam, Slobodan Ilic

More specifically, 3D structures of the whole frame are first represented by our global PPF signatures, from which structural descriptors are learned to help geometric descriptors sense the 3D world beyond local regions.

Point Cloud Registration

PanGu-Coder: Program Synthesis with Function-Level Language Modeling

no code implementations22 Jul 2022 Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, Guchun Zhang, Yinpeng Guo, Zhongqi Li, Qi Zhang, Meng Xiao, Bo Shen, Lin Li, Hao Yu, Li Yan, Pingyi Zhou, Xin Wang, Yuchi Ma, Ignacio Iacobacci, Yasheng Wang, Guangtai Liang, Jiansheng Wei, Xin Jiang, Qianxiang Wang, Qun Liu

We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i. e. the synthesis of programming language solutions given a natural language problem description.

Code Generation Language Modelling +2

Training Vision Transformers with Only 2040 Images

2 code implementations26 Jan 2022 Yun-Hao Cao, Hao Yu, Jianxin Wu

Vision Transformers (ViTs) is emerging as an alternative to convolutional neural networks (CNNs) for visual recognition.

Inductive Bias

A Unified Pruning Framework for Vision Transformers

1 code implementation30 Nov 2021 Hao Yu, Jianxin Wu

Recently, vision transformer (ViT) and its variants have achieved promising performances in various computer vision tasks.

Model Compression object-detection +1

Mixup Without Hesitation

1 code implementation12 Jan 2021 Hao Yu, Huanyu Wang, Jianxin Wu

In this paper, we find that mixup constantly explores the representation space, and inspired by the exploration-exploitation dilemma in reinforcement learning, we propose mixup Without hesitation (mWh), a concise, effective, and easy-to-use training algorithm.

Data Augmentation Image Classification +2

Robust Attacks on Deep Learning Face Recognition in the Physical World

no code implementations27 Nov 2020 Meng Shen, Hao Yu, Liehuang Zhu, Ke Xu, Qi Li, Xiaojiang Du

Deep neural networks (DNNs) have been increasingly used in face recognition (FR) systems.

Face Recognition

Dynamic Phase Diagram of an Orthogonal Spin Torque device: Topological Category

no code implementations2 Oct 2020 Yuan Hui, Zheng Yang, Hao Yu

The magnetization evolution of the free layer in an orthogonal spin-torque device is studied based on a macrospin model.

Mesoscale and Nanoscale Physics

HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression

no code implementations28 Feb 2020 Rui Lin, Ching-Yun Ko, Zhuolun He, Cong Chen, Yuan Cheng, Hao Yu, Graziano Chesi, Ngai Wong

The emerging edge computing has promoted immense interests in compacting a neural network without sacrificing much accuracy.

Edge-computing Tensor Decomposition

Crude oil price forecasting incorporating news text

no code implementations19 Jan 2020 Yun Bai, Xixi Li, Hao Yu, Suling Jia

Sparse and short news headlines can be arbitrary, noisy, and ambiguous, making it difficult for classic topic model LDA (latent Dirichlet allocation) designed for accommodating long text to discover knowledge from them.

A Communication Efficient Stochastic Multi-Block Alternating Direction Method of Multipliers

no code implementations NeurIPS 2019 Hao Yu

In this paper, we propose a new parallel multi-block stochastic ADMM for distributed stochastic optimization, where each node is only required to perform simple stochastic gradient descent updates.

Stochastic Optimization

On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization

no code implementations10 May 2019 Hao Yu, Rong Jin

We show that for stochastic non-convex optimization under the P-L condition, the classical data-parallel SGD with exponentially increasing batch sizes can achieve the fastest known $O(1/(NT))$ convergence with linear speedup using only $\log(T)$ communication rounds.

Stochastic Optimization

On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization

no code implementations9 May 2019 Hao Yu, Rong Jin, Sen yang

Recent developments on large-scale distributed machine learning applications, e. g., deep neural networks, benefit enormously from the advances in distributed non-convex optimization techniques, e. g., distributed Stochastic Gradient Descent (SGD).

BIG-bench Machine Learning

Solving Non-smooth Constrained Programs with Lower Complexity than \mathcal{O}(1/\varepsilon): A Primal-Dual Homotopy Smoothing Approach

no code implementations NeurIPS 2018 Xiaohan Wei, Hao Yu, Qing Ling, Michael Neely

In this paper, we show that by leveraging a local error bound condition on the dual function, the proposed algorithm can achieve a better primal convergence time of $\mathcal{O}\l(\varepsilon^{-2/(2+\beta)}\log_2(\varepsilon^{-1})\r)$, where $\beta\in(0, 1]$ is a local error bound parameter.

Distributed Optimization

MOHONE: Modeling Higher Order Network Effects in KnowledgeGraphs via Network Infused Embeddings

no code implementations1 Nov 2018 Hao Yu, Vivek Kulkarni, William Wang

First, we introduce methods that learn network representations of entities in the knowledge graph capturing these varied aspects of similarity.

Knowledge Graph Embedding Knowledge Graph Embeddings +2

Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning

no code implementations17 Jul 2018 Hao Yu, Sen yang, Shenghuo Zhu

Ideally, parallel mini-batch SGD can achieve a linear speed-up of the training time (with respect to the number of workers) compared with SGD over a single worker.

Fast K-Means Clustering with Anderson Acceleration

no code implementations27 May 2018 Juyong Zhang, Yuxin Yao, Yue Peng, Hao Yu, Bailin Deng

We propose a novel method to accelerate Lloyd's algorithm for K-Means clustering.

DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization

no code implementations21 May 2018 Yuan Cheng, Guangya Li, Hai-Bao Chen, Sheldon X. -D. Tan, Hao Yu

As it requires a huge number of parameters when exposed to high dimensional inputs in video detection and classification, there is a grand challenge to develop a compact yet accurate video comprehension at terminal devices.

Action Recognition General Classification +5

Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

no code implementations10 Apr 2018 Hao Yu, Zhaoning Zhang, Zheng Qin, Hao Wu, Dongsheng Li, Jun Zhao, Xicheng Lu

LRM is a general method for real-time detectors, as it utilizes the final feature map which exists in all real-time detectors to mine hard examples.

Merging and Evolution: Improving Convolutional Neural Networks for Mobile Applications

2 code implementations24 Mar 2018 Zheng Qin, Zhaoning Zhang, Shiqing Zhang, Hao Yu, Yuxing Peng

Compact neural networks are inclined to exploit "sparsely-connected" convolutions such as depthwise convolution and group convolution for employment in mobile applications.

Online Convex Optimization with Stochastic Constraints

no code implementations NeurIPS 2017 Hao Yu, Michael J. Neely, Xiaohan Wei

This paper considers online convex optimization (OCO) with stochastic constraints, which generalizes Zinkevich's OCO over a known simple fixed set by introducing multiple stochastic functional constraints that are i. i. d.


S-OHEM: Stratified Online Hard Example Mining for Object Detection

no code implementations5 May 2017 Minne Li, Zhaoning Zhang, Hao Yu, Xinyuan Chen, Dongsheng Li

S-OHEM exploits OHEM with stratified sampling, a widely-adopted sampling technique, to choose the training examples according to this influence during hard example mining, and thus enhance the performance of object detectors.

object-detection Object Detection

A GPU-Outperforming FPGA Accelerator Architecture for Binary Convolutional Neural Networks

no code implementations20 Feb 2017 Yixing Li, Zichuan Liu, Kai Xu, Hao Yu, Fengbo Ren

For processing static data in large batch sizes, the proposed solution is on a par with a Titan X GPU in terms of throughput while delivering 9. 5x higher energy efficiency.

A Binary Convolutional Encoder-decoder Network for Real-time Natural Scene Text Processing

no code implementations12 Dec 2016 Zichuan Liu, Yixing Li, Fengbo Ren, Hao Yu

In this paper, we develop a binary convolutional encoder-decoder network (B-CEDNet) for natural scene text processing (NSTP).

A Low Complexity Algorithm with $O(\sqrt{T})$ Regret and $O(1)$ Constraint Violations for Online Convex Optimization with Long Term Constraints

no code implementations8 Apr 2016 Hao Yu, Michael J. Neely

That prior work proposes an algorithm to achieve $O(\sqrt{T})$ regret and $O(T^{3/4})$ constraint violations for general problems and another algorithm to achieve an $O(T^{2/3})$ bound for both regret and constraint violations when the constraint set can be described by a finite number of linear constraints.

Cannot find the paper you are looking for? You can Submit a new open access paper.