Search Results for author: Ang Li

Found 72 papers, 13 papers with code

G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency

no code implementations18 Sep 2021 Yongan Zhang, Haoran You, Yonggan Fu, Tong Geng, Ang Li, Yingyan Lin

While end-to-end jointly optimizing GNNs and their accelerators is promising in boosting GNNs' inference efficiency and expediting the design process, it is still underexplored due to the vast and distinct design spaces of GNNs and their accelerators.

Unit Selection with Causal Diagram

no code implementations15 Sep 2021 Ang Li, Judea Pearl

The unit selection problem aims to identify a set of individuals who are most likely to exhibit a desired mode of behavior, for example, selecting individuals who would respond one way if encouraged and a different way if not encouraged.

ETA Prediction with Graph Neural Networks in Google Maps

no code implementations25 Aug 2021 Austin Derrow-Pinion, Jennifer She, David Wong, Oliver Lange, Todd Hester, Luis Perez, Marc Nunkesser, Seongjae Lee, Xueying Guo, Brett Wiltshire, Peter W. Battaglia, Vishal Gupta, Ang Li, Zhongwen Xu, Alvaro Sanchez-Gonzalez, Yujia Li, Petar Veličković

Travel-time prediction constitutes a task of high importance in transportation networks, with web mapping services like Google Maps regularly serving vast quantities of travel time queries from users and enterprises alike.

Graph Representation Learning

Binary Complex Neural Network Acceleration on FPGA

no code implementations10 Aug 2021 Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding

Deep complex networks (DCN), in contrast, can learn from complex data, but have high computational costs; therefore, they cannot satisfy the instant decision-making requirements of many deployable systems dealing with short observations or short signal bursts.

Decision Making

Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective

no code implementations3 Jul 2021 Binghui Wang, Jiayi Guo, Ang Li, Yiran Chen, Hai Li

Existing representation learning methods on graphs have achieved state-of-the-art performance on various graph-related tasks such as node classification, link prediction, etc.

Link Prediction Node Classification +1

Task-agnostic Continual Learning with Hybrid Probabilistic Models

no code implementations24 Jun 2021 Polina Kirichenko, Mehrdad Farajtabar, Dushyant Rao, Balaji Lakshminarayanan, Nir Levine, Ang Li, Huiyi Hu, Andrew Gordon Wilson, Razvan Pascanu

Learning new tasks continuously without forgetting on a constantly changing data distribution is essential for real-world problems but extremely challenging for modern deep learning.

Anomaly Detection Continual Learning

Bounds on Causal Effects and Application to High Dimensional Data

no code implementations23 Jun 2021 Ang Li, Judea Pearl

This paper addresses the problem of estimating causal effects when adjustment variables in the back-door or front-door criterion are partially observed.

Dimensionality Reduction

Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective

1 code implementation CVPR 2021 Jingwei Sun, Ang Li, Binghui Wang, Huanrui Yang, Hai Li, Yiran Chen

The key idea of our defense is learning to perturb data representation such that the quality of the reconstructed data is severely degraded, while FL performance is maintained.

Federated Learning Inference Attack

Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting

no code implementations3 Jun 2021 Ang Li, Qiuhong Ke, Xingjun Ma, Haiqin Weng, Zhiyuan Zong, Feng Xue, Rui Zhang

A promising countermeasure against such forgeries is deep inpainting detection, which aims to locate the inpainted regions in an image.

Image Inpainting

Causes of Effects: Learning individual responses from population data

no code implementations28 Apr 2021 Scott Mueller, Ang Li, Judea Pearl

The problem of individualization is recognized as crucial in almost every field.

Decision Making

BCNN: Binary Complex Neural Network

no code implementations28 Mar 2021 Yanfei Li, Tong Geng, Ang Li, Huimin Yu

Motivated by the complex neural networks, in this paper we introduce complex representation into the BNNs and propose Binary complex neural network -- a novel network design that processes binary complex inputs and weights through complex convolution, but still can harvest the extraordinary computation efficiency of BNNs.

Fluid forces and vortex patterns of an oscillating cylinder pair in still water with both side-by-side and tandem configurations

no code implementations10 Mar 2021 Ang Li, Shengmin Shi, Dixia Fan

In order to reveal the detailed flow physics that result in significant fluid forces alternations, the detailed flow visualization is provided by the numerical simulation: the small gap between two cylinders in a side-by-side configuration will result in a strong gap jet that enhances the energy dissipation and increase the drag, while due to the flow blocking effect for two cylinders in a tandem configuration, the drag coefficient decreases.

Fluid Dynamics

PredCoin: Defense against Query-based Hard-label Attack

no code implementations4 Feb 2021 Junfeng Guo, Yaswanth Yadlapalli, Thiele Lothar, Ang Li, Cong Liu

PredCoin poisons the gradient estimation step, an essential component of most QBHL attacks.

Hard-label Attack

Cramér-Rao Bound Optimization for Joint Radar-Communication Design

no code implementations29 Jan 2021 Fan Liu, Ya-Feng Liu, Ang Li, Christos Masouros, Yonina C. Eldar

We employ the Cram\'er-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios.

On Provable Backdoor Defense in Collaborative Learning

no code implementations19 Jan 2021 Ximing Qiao, Yuhua Bai, Siping Hu, Ang Li, Yiran Chen, Hai Li

The framework shows that the subset selection process, a deciding factor for subset aggregation methods, can be viewed as a code design problem.

GenQu: A Hybrid Framework for Learning Classical Data in Quantum States

no code implementations1 Jan 2021 Samuel A. Stein, Ray Marie Tischio, Betis Baheri, YiWen Chen, Ying Mao, Qiang Guan, Ang Li, Bo Fang

In this paper, we propose GenQu, a hybrid and general-purpose quantum framework for learning classical data through quantum states.

Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective

2 code implementations8 Dec 2020 Jingwei Sun, Ang Li, Binghui Wang, Huanrui Yang, Hai Li, Yiran Chen

In this work, we show our key observation that the data representation leakage from gradients is the essential cause of privacy leakage in FL.

Federated Learning

GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs

no code implementations8 Dec 2020 Binghui Wang, Ang Li, Hai Li, Yiran Chen

However, existing FL methods 1) perform poorly when data across clients are non-IID, 2) cannot handle data with new label domains, and 3) cannot leverage unlabeled data, while all these issues naturally happen in real-world graph-based problems.

Federated Learning General Classification +2

Evasion Attacks to Graph Neural Networks via Influence Function

no code implementations1 Sep 2020 Binghui Wang, Tianxiang Zhou, Minhua Lin, Pan Zhou, Ang Li, Meng Pang, Cai Fu, Hai Li, Yiran Chen

Next, we reformulate the evasion attack against GNNs to be related to calculating label influence on LP, which is applicable to multi-layer GNNs and does not need to know the GNN model.

Node Classification

Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs

no code implementations1 Sep 2020 Houxiang Fan, Binghui Wang, Pan Zhou, Ang Li, Meng Pang, Zichuan Xu, Cai Fu, Hai Li, Yiran Chen

Link prediction in dynamic graphs (LPDG) is an important research problem that has diverse applications such as online recommendations, studies on disease contagion, organizational studies, etc.

Graph Embedding Link Prediction

LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets

1 code implementation7 Aug 2020 Ang Li, Jingwei Sun, Binghui Wang, Lin Duan, Sicheng Li, Yiran Chen, Hai Li

Rather than learning a shared global model in classic federated learning, each client learns a personalized model via LotteryFL; the communication cost can be significantly reduced due to the compact size of lottery networks.

Federated Learning

Accelerating Binarized Neural Networks via Bit-Tensor-Cores in Turing GPUs

1 code implementation30 Jun 2020 Ang Li, Simon Su

Despite foreseeing tremendous speedups over conventional deep neural networks, the performance advantage of binarized neural networks (BNNs) has merely been showcased on general-purpose processors such as CPUs and GPUs.

Accelerated Deep Reinforcement Learning Based Load Shedding for Emergency Voltage Control

no code implementations22 Jun 2020 Renke Huang, Yujiao Chen, Tianzhixi Yin, Xinya Li, Ang Li, Jie Tan, Wenhao Yu, YuAn Liu, Qiuhua Huang

Load shedding has been one of the most widely used and effective emergency control approaches against voltage instability.

Optimization and Generalization of Regularization-Based Continual Learning: a Loss Approximation Viewpoint

no code implementations19 Jun 2020 Dong Yin, Mehrdad Farajtabar, Ang Li, Nir Levine, Alex Mott

This problem is often referred to as catastrophic forgetting, a key challenge in continual learning of neural networks.

Continual Learning

Learning to Incentivize Other Learning Agents

1 code implementation NeurIPS 2020 Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes, Hongyuan Zha

The challenge of developing powerful and general Reinforcement Learning (RL) agents has received increasing attention in recent years.

General Reinforcement Learning

QASMBench: A Low-level QASM Benchmark Suite for NISQ Evaluation and Simulation

3 code implementations26 May 2020 Ang Li, Sriram Krishnamoorthy

The rapid development of quantum computing (QC) in the NISQ era urgently demands a low-level benchmark suite and insightful evaluation metrics for characterizing the properties of prototype NISQ devices, the efficiency of QC programming compilers, schedulers and assemblers, and the capability of quantum simulators in a classical computer.

Quantum Physics

MVStylizer: An Efficient Edge-Assisted Video Photorealistic Style Transfer System for Mobile Phones

no code implementations24 May 2020 Ang Li, Chunpeng Wu, Yiran Chen, Bin Ni

Instead of performing stylization frame by frame, only key frames in the original video are processed by a pre-trained deep neural network (DNN) on edge servers, while the rest of stylized intermediate frames are generated by our designed optical-flow-based frame interpolation algorithm on mobile phones.

Federated Learning Optical Flow Estimation +2

PoliteCamera: Respecting Strangers' Privacy in Mobile Photographing

no code implementations24 May 2020 Ang Li, Wei Du, Qinghua Li

Through the cooperation between a photographer and a stranger, the stranger's face in a photo can be automatically blurred upon his request when the photo is taken.

TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework for Deep Learning with Anonymized Intermediate Representations

no code implementations23 May 2020 Ang Li, Yixiao Duan, Huanrui Yang, Yiran Chen, Jianlei Yang

The goal of this framework is to learn a feature extractor that can hide the privacy information from the intermediate representations; while maximally retaining the original information embedded in the raw data for the data collector to accomplish unknown learning tasks.

Tidal deformability and gravitational-wave phase evolution of magnetised compact-star binaries

no code implementations6 May 2020 Zhenyu Zhu, Ang Li, Luciano Rezzolla

Hence, the measurement of these corrections has the potential of providing important information on the equation of state of nuclear matter.

High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology

Reconfigurable Intelligent Surface (RIS)-Enhanced Two-Way OFDM Communications

no code implementations5 May 2020 Chandan Pradhan, Ang Li, Lingyang Song, Jun Li, Branka Vucetic, Yonghui Li

In this paper, we focus on the reconfigurable intelligent surface (RIS)-enhanced two-way device-to-device (D2D) multi-pair orthogonal-frequency-division-multiplexing (OFDM) communication systems.

The AVA-Kinetics Localized Human Actions Video Dataset

no code implementations1 May 2020 Ang Li, Meghana Thotakuri, David A. Ross, João Carreira, Alexander Vostrikov, Andrew Zisserman

The dataset is collected by annotating videos from the Kinetics-700 dataset using the AVA annotation protocol, and extending the original AVA dataset with these new AVA annotated Kinetics clips.

Action Classification

Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification

1 code implementation20 Apr 2020 Huanrui Yang, Minxue Tang, Wei Wen, Feng Yan, Daniel Hu, Ang Li, Hai Li, Yiran Chen

In this work, we propose SVD training, the first method to explicitly achieve low-rank DNNs during training without applying SVD on every step.

Hybrid Models for Open Set Recognition

no code implementations ECCV 2020 Hongjie Zhang, Ang Li, Jie Guo, Yanwen Guo

We propose the OpenHybrid framework, which is composed of an encoder to encode the input data into a joint embedding space, a classifier to classify samples to inlier classes, and a flow-based density estimator to detect whether a sample belongs to the unknown category.

Open Set Learning Out-of-Distribution Detection

RSnet: An improvement for Darknet

no code implementations16 Jan 2020 Shengquan Wang, Ang Li, Jiying Chen, Baoyu Zheng, Jiaxin Ji, Li Xianglong

Recently, when we used this method to identify aircraft targets in remote sensing images, we found that there are some defects in our own YOLOv2 and Darknet-19 network.

Orthogonal Gradient Descent for Continual Learning

no code implementations15 Oct 2019 Mehrdad Farajtabar, Navid Azizan, Alex Mott, Ang Li

In this paper, we propose to address this issue from a parameter space perspective and study an approach to restrict the direction of the gradient updates to avoid forgetting previously-learned data.

Continual Learning

DeepObfuscator: Obfuscating Intermediate Representations with Privacy-Preserving Adversarial Learning on Smartphones

no code implementations9 Sep 2019 Ang Li, Jiayi Guo, Huanrui Yang, Flora D. Salim, Yiran Chen

Our experiments on CelebA and LFW datasets show that the quality of the reconstructed images from the obfuscated features of the raw image is dramatically decreased from 0. 9458 to 0. 3175 in terms of multi-scale structural similarity.

General Classification Image Classification +2

Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control

1 code implementation ICLR 2020 Nir Levine, Yin-Lam Chow, Rui Shu, Ang Li, Mohammad Ghavamzadeh, Hung Bui

A promising approach is to embed the high-dimensional observations into a lower-dimensional latent representation space, estimate the latent dynamics model, then utilize this model for control in the latent space.

Decision Making Representation Learning

Boosted GAN with Semantically Interpretable Information for Image Inpainting

no code implementations13 Aug 2019 Ang Li, Jianzhong Qi, Rui Zhang, Ramamohanarao Kotagiri

Forexample, given a male image with image region of one eye missing, current models may restore it with a female eye.

Image Inpainting Image Restoration

Generative Image Inpainting with Submanifold Alignment

no code implementations1 Aug 2019 Ang Li, Jianzhong Qi, Rui Zhang, Xingjun Ma, Kotagiri Ramamohanarao

Image inpainting aims at restoring missing regions of corrupted images, which has many applications such as image restoration and object removal.

Image Inpainting Image Restoration

PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving

no code implementations CVPR 2020 Zelun Kong, Junfeng Guo, Ang Li, Cong Liu

We compare PhysGAN with a set of state-of-the-art baseline methods including several of our self-designed ones, which further demonstrate the robustness and efficacy of our approach.

Autonomous Driving Image Classification

Cross-View Policy Learning for Street Navigation

1 code implementation ICCV 2019 Ang Li, Huiyi Hu, Piotr Mirowski, Mehrdad Farajtabar

The ability to navigate from visual observations in unfamiliar environments is a core component of intelligent agents and an ongoing challenge for Deep Reinforcement Learning (RL).

Transfer Learning

Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect

1 code implementation11 Mar 2019 Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan Tallent, Kevin Barker

High performance multi-GPU computing becomes an inevitable trend due to the ever-increasing demand on computation capability in emerging domains such as deep learning, big data and planet-scale simulations.

Hardware Architecture Distributed, Parallel, and Cluster Computing Networking and Internet Architecture Performance

Improved Knowledge Distillation via Teacher Assistant

3 code implementations9 Feb 2019 Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa, Hassan Ghasemzadeh

To alleviate this shortcoming, we introduce multi-step knowledge distillation, which employs an intermediate-sized network (teacher assistant) to bridge the gap between the student and the teacher.

Knowledge Distillation

A Generalized Framework for Population Based Training

no code implementations5 Feb 2019 Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta

Population Based Training (PBT) is a recent approach that jointly optimizes neural network weights and hyperparameters which periodically copies weights of the best performers and mutates hyperparameters during training.

FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters

no code implementations4 Jan 2019 Tong Geng, Tianqi Wang, Ang Li, Xi Jin, Martin Herbordt

Among the issues with this approach is that to make the distributed cluster work with high utilization, the workload distributed to each node must be large, which implies nontrivial growth in the SGD mini-batch size.

Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition

no code implementations23 Oct 2018 Yuanliu Liu, Ang Li, Zejian yuan, Badong Chen, Nanning Zheng

We propose a Consistency-aware Selective Fusion (CSF) to integrate the pairwise orders into a globally consistent order.

Intrinsic Image Decomposition

SymmNet: A Symmetric Convolutional Neural Network for Occlusion Detection

no code implementations3 Jul 2018 Ang Li, Zejian yuan

Detecting the occlusion from stereo images or video frames is important to many computer vision applications.

Optical Flow Estimation

Layout-induced Video Representation for Recognizing Agent-in-Place Actions

no code implementations ICCV 2019 Ruichi Yu, Hongcheng Wang, Ang Li, Jingxiao Zheng, Vlad I. Morariu, Larry S. Davis

We address the recognition of agent-in-place actions, which are associated with agents who perform them and places where they occur, in the context of outdoor home surveillance.

SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks

no code implementations13 Jan 2018 Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu, Ang Li, Shuaiwen Leon Song, Zenglin Xu, Tim Kraska

Given the limited GPU DRAM, SuperNeurons not only provisions the necessary memory for the training, but also dynamically allocates the memory for convolution workspaces to achieve the high performance.

NISP: Pruning Networks using Neuron Importance Score Propagation

no code implementations CVPR 2018 Ruichi Yu, Ang Li, Chun-Fu Chen, Jui-Hsin Lai, Vlad I. Morariu, Xintong Han, Mingfei Gao, Ching-Yung Lin, Larry S. Davis

In contrast, we argue that it is essential to prune neurons in the entire neuron network jointly based on a unified goal: minimizing the reconstruction error of important responses in the "final response layer" (FRL), which is the second-to-last layer before classification, for a pruned network to retrain its predictive power.

Network Pruning

C-WSL: Count-guided Weakly Supervised Localization

no code implementations ECCV 2018 Mingfei Gao, Ang Li, Ruichi Yu, Vlad I. Morariu, Larry S. Davis

We introduce count-guided weakly supervised localization (C-WSL), an approach that uses per-class object count as a new form of supervision to improve weakly supervised localization (WSL).

Dynamic Zoom-in Network for Fast Object Detection in Large Images

no code implementations CVPR 2018 Mingfei Gao, Ruichi Yu, Ang Li, Vlad I. Morariu, Larry S. Davis

We introduce a generic framework that reduces the computational cost of object detection while retaining accuracy for scenarios where objects with varied sizes appear in high resolution images.

Real-Time Object Detection

Generating Holistic 3D Scene Abstractions for Text-based Image Retrieval

no code implementations CVPR 2017 Ang Li, Jin Sun, Joe Yue-Hei Ng, Ruichi Yu, Vlad I. Morariu, Larry S. Davis

Since interactions between objects can be reduced to a limited set of atomic spatial relations in 3D, we study the possibility of inferring 3D structure from a text description rather than an image, applying physical relation models to synthesize holistic 3D abstract object layouts satisfying the spatial constraints present in a textual description.

Image Retrieval Object Detection

ModelHub: Towards Unified Data and Lifecycle Management for Deep Learning

no code implementations18 Nov 2016 Hui Miao, Ang Li, Larry S. Davis, Amol Deshpande

Deep learning modeling lifecycle generates a rich set of data artifacts, such as learned parameters and training logs, and comprises of several frequently conducted tasks, e. g., to understand the model behaviors and to try out new models.

Coordinating Multiple Disparity Proposals for Stereo Computation

no code implementations CVPR 2016 Ang Li, Dapeng Chen, Yuanliu liu, Zejian yuan

While great progress has been made in stereo computation over the last decades, large textureless regions remain challenging.

Sensing Subjective Well-being from Social Media

no code implementations15 Mar 2014 Bibo Hao, Lin Li, Rui Gao, Ang Li, Tingshao Zhu

Nowadays, people are motivated to share their experiences and feelings on social media, so we propose to sense SWB from the vast user generated data on social media.

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