Search Results for author: Liu Liu

Found 87 papers, 20 papers with code

Boosting Deep Neural Network Efficiency with Dual-Module Inference

no code implementations ICML 2020 Liu Liu, Lei Deng, Zhaodong Chen, yuke wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie

Using Deep Neural Networks (DNNs) in machine learning tasks is promising in delivering high-quality results but challenging to meet stringent latency requirements and energy constraints because of the memory-bound and the compute-bound execution pattern of DNNs.

Deep Streaming Label Learning

1 code implementation ICML 2020 Zhen Wang, Liu Liu, DaCheng Tao

In order to fill in these research gaps, we propose a novel deep neural network (DNN) based framework, Deep Streaming Label Learning (DSLL), to classify instances with newly emerged labels effectively.

Multi-Label Learning

One-shot neural band selection for spectral recovery

no code implementations16 May 2023 Hai-Miao Hu, Zhenbo Xu, Wenshuai Xu, You Song, YiTao Zhang, Liu Liu, Zhilin Han, Ajin Meng

To solve this ill-posed inverse problem, most band selection methods adopt hand-crafted priors or exploit clustering or sparse regularization constraints to find most prominent bands.

Spectral Reconstruction

Reweighted Mixup for Subpopulation Shift

no code implementations9 Apr 2023 Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, QinGhua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao

Subpopulation shift exists widely in many real-world applications, which refers to the training and test distributions that contain the same subpopulation groups but with different subpopulation proportions.

Fairness Generalization Bounds

Deploying Offline Reinforcement Learning with Human Feedback

no code implementations13 Mar 2023 Ziniu Li, Ke Xu, Liu Liu, Lanqing Li, Deheng Ye, Peilin Zhao

To address this issue, we propose an alternative framework that involves a human supervising the RL models and providing additional feedback in the online deployment phase.

Decision Making Model Selection +3

CyberLoc: Towards Accurate Long-term Visual Localization

no code implementations6 Jan 2023 Liu Liu, Yukai Lin, Xiao Liang, Qichao Xu, Miao Jia, Yangdong Liu, Yuxiang Wen, Wei Luo, Jiangwei Li

Second, a single-image-based localization pipeline (retrieval--matching--PnP) is performed to estimate 6-DoF camera poses for each query image, one for each 3D map.

Autonomous Driving Image-Based Localization +3

Event Camera Data Pre-training

no code implementations5 Jan 2023 Yan Yang, Liyuan Pan, Liu Liu

Our model is a self-supervised learning framework, and uses paired event camera data and natural RGB images for training.

Contrastive Learning Self-Supervised Learning +1

K3DN: Disparity-Aware Kernel Estimation for Dual-Pixel Defocus Deblurring

no code implementations CVPR 2023 Yan Yang, Liyuan Pan, Liu Liu, Miaomiao Liu

It estimates a disparity feature map, which is used to query a trainable kernel set to estimate a blur kernel that best describes the spatially-varying blur.

Deblurring Image Restoration

ISG: I can See Your Gene Expression

no code implementations30 Oct 2022 Yan Yang, Liyuan Pan, Liu Liu, Eric A Stone

Instead, we present ISG framework that harnesses interactions among discriminative features from texture-abundant regions by three new modules: 1) a Shannon Selection module, based on the Shannon information content and Solomonoff's theory, to filter out textureless image regions; 2) a Feature Extraction network to extract expressive low-dimensional feature representations for efficient region interactions among a high-resolution image; 3) a Dual Attention network attends to regions with desired gene expression features and aggregates them for the prediction task.

Robust Offline Reinforcement Learning with Gradient Penalty and Constraint Relaxation

no code implementations19 Oct 2022 Chengqian Gao, Ke Xu, Liu Liu, Deheng Ye, Peilin Zhao, Zhiqiang Xu

A promising paradigm for offline reinforcement learning (RL) is to constrain the learned policy to stay close to the dataset behaviors, known as policy constraint offline RL.

D4RL Offline RL +2

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup

1 code implementation19 Sep 2022 Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao

Importance reweighting is a normal way to handle the subpopulation shift issue by imposing constant or adaptive sampling weights on each sample in the training dataset.

Generalization Bounds

Balancing Stability and Plasticity through Advanced Null Space in Continual Learning

no code implementations25 Jul 2022 Yajing Kong, Liu Liu, Zhen Wang, DaCheng Tao

Continual learning is a learning paradigm that learns tasks sequentially with resources constraints, in which the key challenge is stability-plasticity dilemma, i. e., it is uneasy to simultaneously have the stability to prevent catastrophic forgetting of old tasks and the plasticity to learn new tasks well.

Continual Learning

Online Continual Learning with Contrastive Vision Transformer

no code implementations24 Jul 2022 Zhen Wang, Liu Liu, Yajing Kong, Jiaxian Guo, DaCheng Tao

Based on the learnable focuses, we design a focal contrastive loss to rebalance contrastive learning between new and past classes and consolidate previously learned representations.

Continual Learning Contrastive Learning

Learning Object Placement via Dual-path Graph Completion

1 code implementation23 Jul 2022 Siyuan Zhou, Liu Liu, Li Niu, Liqing Zhang

Object placement aims to place a foreground object over a background image with a suitable location and size.

OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interaction

1 code implementation CVPR 2022 Lixin Yang, Kailin Li, Xinyu Zhan, Fei Wu, Anran Xu, Liu Liu, Cewu Lu

We start to collect 1, 800 common household objects and annotate their affordances to construct the first knowledge base: Oak.

Grasp Generation Pose Estimation

Accurate 3-DoF Camera Geo-Localization via Ground-to-Satellite Image Matching

1 code implementation26 Mar 2022 Yujiao Shi, Xin Yu, Liu Liu, Dylan Campbell, Piotr Koniusz, Hongdong Li

We address the problem of ground-to-satellite image geo-localization, that is, estimating the camera latitude, longitude and orientation (azimuth angle) by matching a query image captured at the ground level against a large-scale database with geotagged satellite images.

Image Retrieval Retrieval

Exploring High-Order Structure for Robust Graph Structure Learning

no code implementations22 Mar 2022 Guangqian Yang, Yibing Zhan, Jinlong Li, Baosheng Yu, Liu Liu, Fengxiang He

In this paper, we analyze the adversarial attack on graphs from the perspective of feature smoothness which further contributes to an efficient new adversarial defensive algorithm for GNNs.

Adversarial Attack Graph structure learning +1

Dynamic N:M Fine-grained Structured Sparse Attention Mechanism

no code implementations28 Feb 2022 Zhaodong Chen, Yuying Quan, Zheng Qu, Liu Liu, Yufei Ding, Yuan Xie

We evaluate the 1:2 and 2:4 sparsity under different configurations and achieve 1. 27~ 1. 89x speedups over the full-attention mechanism.

AKB-48: A Real-World Articulated Object Knowledge Base

no code implementations CVPR 2022 Liu Liu, Wenqiang Xu, Haoyuan Fu, Sucheng Qian, Yang Han, Cewu Lu

To bridge the gap, we present AKB-48: a large-scale Articulated object Knowledge Base which consists of 2, 037 real-world 3D articulated object models of 48 categories.

Object Reconstruction Pose Estimation

Robust Imitation Learning from Corrupted Demonstrations

no code implementations29 Jan 2022 Liu Liu, Ziyang Tang, Lanqing Li, Dijun Luo

We consider offline Imitation Learning from corrupted demonstrations where a constant fraction of data can be noise or even arbitrary outliers.

Continuous Control Imitation Learning

Resistance Training using Prior Bias: toward Unbiased Scene Graph Generation

1 code implementation18 Jan 2022 Chao Chen, Yibing Zhan, Baosheng Yu, Liu Liu, Yong Luo, Bo Du

To address this problem, we propose Resistance Training using Prior Bias (RTPB) for the scene graph generation.

Graph Generation Unbiased Scene Graph Generation

Continual Learning With Lifelong Vision Transformer

no code implementations CVPR 2022 Zhen Wang, Liu Liu, Yiqun Duan, Yajing Kong, DaCheng Tao

Continual learning methods aim at training a neural network from sequential data with streaming labels, relieving catastrophic forgetting.

Continual Learning

Text-to-Image Synthesis Based on Object-Guided Joint-Decoding Transformer

no code implementations CVPR 2022 Fuxiang Wu, Liu Liu, Fusheng Hao, Fengxiang He, Jun Cheng

Object-guided text-to-image synthesis aims to generate images from natural language descriptions built by two-step frameworks, i. e., the model generates the layout and then synthesizes images from the layout and captions.

Image Generation

iSeg3D: An Interactive 3D Shape Segmentation Tool

no code implementations24 Dec 2021 Sucheng Qian, Liu Liu, Wenqiang Xu, Cewu Lu

It can obtain a satisfied segmentation result with minimal human clicks (< 10).

SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks

no code implementations22 Dec 2021 Weigang Lu, Yibing Zhan, Binbin Lin, Ziyu Guan, Liu Liu, Baosheng Yu, Wei Zhao, Yaming Yang, DaCheng Tao

In this paper, we conduct theoretical and experimental analysis to explore the fundamental causes of performance degradation in deep GCNs: over-smoothing and gradient vanishing have a mutually reinforcing effect that causes the performance to deteriorate more quickly in deep GCNs.

Link Prediction Node Classification

Transcribing Natural Languages for The Deaf via Neural Editing Programs

no code implementations17 Dec 2021 Dongxu Li, Chenchen Xu, Liu Liu, Yiran Zhong, Rong Wang, Lars Petersson, Hongdong Li

This work studies the task of glossification, of which the aim is to em transcribe natural spoken language sentences for the Deaf (hard-of-hearing) community to ordered sign language glosses.

OMAD: Object Model with Articulated Deformations for Pose Estimation and Retrieval

no code implementations14 Dec 2021 Han Xue, Liu Liu, Wenqiang Xu, Haoyuan Fu, Cewu Lu

With the full representation of the object shape and joint states, we can address several tasks including category-level object pose estimation and the articulated object retrieval.

Pose Estimation Retrieval

Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels

no code implementations NeurIPS 2021 Sheng Wan, Yibing Zhan, Liu Liu, Baosheng Yu, Shirui Pan, Chen Gong

Essentially, our CGPN can enhance the learning performance of GNNs under extremely limited labels by contrastively propagating the limited labels to the entire graph.

Graph Attention Node Classification +1

Transformer Acceleration with Dynamic Sparse Attention

no code implementations21 Oct 2021 Liu Liu, Zheng Qu, Zhaodong Chen, Yufei Ding, Yuan Xie

We demonstrate that the sparse patterns are dynamic, depending on input sequences.

DFSSATTEN: Dynamic Fine-grained Structured Sparse Attention Mechanism

no code implementations29 Sep 2021 Zhaodong Chen, Liu Liu, Yuying Quan, Zheng Qu, Yufei Ding, Yuan Xie

Transformers are becoming mainstream solutions for various tasks like NLP and Computer vision.

Lagrangian Generative Adversarial Imitation Learning with Safety

no code implementations29 Sep 2021 Zhihao Cheng, Li Shen, Meng Fang, Liu Liu, DaCheng Tao

Imitation Learning (IL) merely concentrates on reproducing expert behaviors and could take dangerous actions, which is unbearable in safety-critical scenarios.

Imitation Learning

Multi-modal Affect Analysis using standardized data within subjects in the Wild

no code implementations7 Jul 2021 Sachihiro Youoku, Takahisa Yamamoto, Junya Saito, Akiyoshi Uchida, Xiaoyu Mi, Ziqiang Shi, Liu Liu, Zhongling Liu, Osafumi Nakayama, Kentaro Murase

Therefore, after learning the common features for each frame, we constructed a facial expression estimation model and valence-arousal model using time-series data after combining the common features and the standardized features for each video.

Time Series Analysis

OPA: Object Placement Assessment Dataset

2 code implementations5 Jul 2021 Liu Liu, Zhenchen Liu, Bo Zhang, Jiangtong Li, Li Niu, Qingyang Liu, Liqing Zhang

Image composition aims to generate realistic composite image by inserting an object from one image into another background image, where the placement (e. g., location, size, occlusion) of inserted object may be unreasonable, which would significantly degrade the quality of the composite image.

Making Images Real Again: A Comprehensive Survey on Deep Image Composition

1 code implementation28 Jun 2021 Li Niu, Wenyan Cong, Liu Liu, Yan Hong, Bo Zhang, Jing Liang, Liqing Zhang

We also point out the limitations of existing methods in each sub-task and the problem of the whole image composition task.

Image Harmonization

PluckerNet: Learn To Register 3D Line Reconstructions

no code implementations CVPR 2021 Liu Liu, Hongdong Li, Haodong Yao, Ruyi Zha

Aligning two partially-overlapped 3D line reconstructions in Euclidean space is challenging, as we need to simultaneously solve line correspondences and relative pose between reconstructions.


Towards Real-World Category-level Articulation Pose Estimation

no code implementations7 May 2021 Liu Liu, Han Xue, Wenqiang Xu, Haoyuan Fu, Cewu Lu

This setting allows varied kinematic structures within a semantic category, and multiple instances to co-exist in an observation of real world.

Mixed Reality Pose Estimation

A deep neural network approach on solving the linear transport model under diffusive scaling

no code implementations24 Feb 2021 Liu Liu, Tieyong Zeng, Zecheng Zhang

In our framework, the solution is approximated by a neural network that satisfies both the governing equation and other constraints.

Numerical Analysis Numerical Analysis

Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation

1 code implementation19 Jan 2021 Ye Huang, Di Kang, Wenjing Jia, Xiangjian He, Liu Liu

Spatial and channel attentions, modelling the semantic interdependencies in spatial and channel dimensions respectively, have recently been widely used for semantic segmentation.

Semantic Segmentation

Semantic Inference Network for Few-shot Streaming Label Learning

no code implementations1 Jan 2021 Zhen Wang, Liu Liu, Yiqun Duan, DaCheng Tao

In this work, we formulate and study few-shot streaming label learning (FSLL), which models emerging new labels with only a few annotated examples by utilizing the knowledge learned from past labels.

Meta-Learning Multi-Label Classification

Adaptive Curriculum Learning

no code implementations ICCV 2021 Yajing Kong, Liu Liu, Jun Wang, DaCheng Tao

Therefore, in contrast to recent works using a fixed curriculum, we devise a new curriculum learning method, Adaptive Curriculum Learning (Adaptive CL), adapting the difficulty of examples to the current state of the model.

Binary Classification

PlueckerNet: Learn to Register 3D Line Reconstructions

2 code implementations2 Dec 2020 Liu Liu, Hongdong Li, Haodong Yao, Ruyi Zha

Aligning two partially-overlapped 3D line reconstructions in Euclidean space is challenging, as we need to simultaneously solve correspondences and relative pose between line reconstructions.


On the Guaranteed Almost Equivalence between Imitation Learning from Observation and Demonstration

no code implementations16 Oct 2020 Zhihao Cheng, Liu Liu, Aishan Liu, Hao Sun, Meng Fang, DaCheng Tao

By contrast, this paper proves that LfO is almost equivalent to LfD in the deterministic robot environment, and more generally even in the robot environment with bounded randomness.

Imitation Learning

Weak-shot Fine-grained Classification via Similarity Transfer

1 code implementation NeurIPS 2021 Junjie Chen, Li Niu, Liu Liu, Liqing Zhang

In this setting, we propose a method called SimTrans to transfer pairwise semantic similarity from base categories to novel categories.

Classification General Classification +2

Solving the Blind Perspective-n-Point Problem End-To-End With Robust Differentiable Geometric Optimization

2 code implementations ECCV 2020 Dylan Campbell, Liu Liu, Stephen Gould

We instead propose the first fully end-to-end trainable network for solving the blind PnP problem efficiently and globally, that is, without the need for pose priors.

Robust Compressed Sensing using Generative Models

1 code implementation NeurIPS 2020 Ajil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis

In analogy to classical compressed sensing, here we assume a generative model as a prior, that is, we assume the vector is represented by a deep generative model $G: \mathbb{R}^k \rightarrow \mathbb{R}^n$.

Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution

no code implementations CVPR 2020 Xibin Song, Yuchao Dai, Dingfu Zhou, Liu Liu, Wei Li, Hongdng Li, Ruigang Yang

Second, we propose a new framework for real-world DSR, which consists of four modules : 1) An iterative residual learning module with deep supervision to learn effective high-frequency components of depth maps in a coarse-to-fine manner; 2) A channel attention strategy to enhance channels with abundant high-frequency components; 3) A multi-stage fusion module to effectively re-exploit the results in the coarse-to-fine process; and 4) A depth refinement module to improve the depth map by TGV regularization and input loss.

Benchmarking Depth Map Super-Resolution

Computation on Sparse Neural Networks: an Inspiration for Future Hardware

no code implementations24 Apr 2020 Fei Sun, Minghai Qin, Tianyun Zhang, Liu Liu, Yen-Kuang Chen, Yuan Xie

We show that for practically complicated problems, it is more beneficial to search large and sparse models in the weight dominated region.

Learning 2D-3D Correspondences To Solve The Blind Perspective-n-Point Problem

1 code implementation15 Mar 2020 Liu Liu, Dylan Campbell, Hongdong Li, Dingfu Zhou, Xibin Song, Ruigang Yang

Conventional absolute camera pose via a Perspective-n-Point (PnP) solver often assumes that the correspondences between 2D image pixels and 3D points are given.

Spatial-Aware Feature Aggregation for Image based Cross-View Geo-Localization

1 code implementation NeurIPS 2019 Yujiao Shi, Liu Liu, Xin Yu, Hongdong Li

The first step is to apply a regular polar transform to warp an aerial image such that its domain is closer to that of a ground-view panorama.

DoveNet: Deep Image Harmonization via Domain Verification

1 code implementation CVPR 2020 Wenyan Cong, Jianfu Zhang, Li Niu, Liu Liu, Zhixin Ling, Weiyuan Li, Liqing Zhang

Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image.

Image Harmonization

Stochastically Controlled Compositional Gradient for the Composition problem

no code implementations25 Sep 2019 Liu Liu, Ji Liu, Cho-Jui Hsieh, DaCheng Tao

The strategy is also accompanied by a mini-batch version of the proposed method that improves query complexity with respect to the size of the mini-batch.

Quantum algorithm for finding the negative curvature direction

no code implementations25 Sep 2019 Kaining Zhang, Min-Hsiu Hsieh, Liu Liu, DaCheng Tao

Moreover, we propose an efficient algorithm to achieve the classical read-out of the target state.

Dual-module Inference for Efficient Recurrent Neural Networks

no code implementations25 Sep 2019 Liu Liu, Lei Deng, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie

Using Recurrent Neural Networks (RNNs) in sequence modeling tasks is promising in delivering high-quality results but challenging to meet stringent latency requirements because of the memory-bound execution pattern of RNNs.

Encoding Selection for Solving Hamiltonian Cycle Problems with ASP

no code implementations18 Sep 2019 Liu Liu, Miroslaw Truszczynski

It is common for search and optimization problems to have alternative equivalent encodings in ASP.

Quantum algorithm for finding the negative curvature direction in non-convex optimization

no code implementations17 Sep 2019 Kaining Zhang, Min-Hsiu Hsieh, Liu Liu, DaCheng Tao

Moreover, we propose an efficient quantum algorithm to achieve the classical read-out of the target state.

NODE: Extreme Low Light Raw Image Denoising using a Noise Decomposition Network

no code implementations11 Sep 2019 Hao Guan, Liu Liu, Sean Moran, Fenglong Song, Gregory Slabaugh

In this paper, we propose a multi-task deep neural network called Noise Decomposition (NODE) that explicitly and separately estimates defective pixel noise, in conjunction with Gaussian and Poisson noise, to denoise an extreme low light image.

Image Denoising

Image Harmonization Dataset iHarmony4: HCOCO, HAdobe5k, HFlickr, and Hday2night

1 code implementation28 Aug 2019 Wenyan Cong, Jianfu Zhang, Li Niu, Liu Liu, Zhixin Ling, Weiyuan Li, Liqing Zhang

Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image.

Image Harmonization

Optimal Feature Transport for Cross-View Image Geo-Localization

1 code implementation11 Jul 2019 Yujiao Shi, Xin Yu, Liu Liu, Tong Zhang, Hongdong Li

This paper proposes a novel Cross-View Feature Transport (CVFT) technique to explicitly establish cross-view domain transfer that facilitates feature alignment between ground and aerial images.

Image-Based Localization Metric Learning

Lending Orientation to Neural Networks for Cross-view Geo-localization

1 code implementation CVPR 2019 Liu Liu, Hongdong Li

The goal is to predict the spatial location of a ground-level query image by matching it to a large geotagged aerial image database (e. g., satellite imagery).

FurcaNeXt: End-to-end monaural speech separation with dynamic gated dilated temporal convolutional networks

no code implementations12 Feb 2019 Ziqiang Shi, Huibin Lin, Liu Liu, Rujie Liu, Jiqing Han, Anyan Shi

Deep dilated temporal convolutional networks (TCN) have been proved to be very effective in sequence modeling.

Sound Audio and Speech Processing

High Dimensional Robust $M$-Estimation: Arbitrary Corruption and Heavy Tails

no code implementations24 Jan 2019 Liu Liu, Tianyang Li, Constantine Caramanis

We define a natural condition we call the Robust Descent Condition (RDC), and show that if a gradient estimator satisfies the RDC, then Robust Hard Thresholding (IHT using this gradient estimator), is guaranteed to obtain good statistical rates.

regression Vocal Bursts Intensity Prediction

Dynamic Sparse Graph for Efficient Deep Learning

no code implementations ICLR 2019 Liu Liu, Lei Deng, Xing Hu, Maohua Zhu, Guoqi Li, Yufei Ding, Yuan Xie

We propose to execute deep neural networks (DNNs) with dynamic and sparse graph (DSG) structure for compressive memory and accelerative execution during both training and inference.

Dimensionality Reduction

Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient

no code implementations26 Sep 2018 Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, DaCheng Tao

Trust region and cubic regularization methods have demonstrated good performance in small scale non-convex optimization, showing the ability to escape from saddle points.

Second-order methods

Stochastically Controlled Stochastic Gradient for the Convex and Non-convex Composition problem

no code implementations6 Sep 2018 Liu Liu, Ji Liu, Cho-Jui Hsieh, DaCheng Tao

In this paper, we consider the convex and non-convex composition problem with the structure $\frac{1}{n}\sum\nolimits_{i = 1}^n {{F_i}( {G( x )} )}$, where $G( x )=\frac{1}{n}\sum\nolimits_{j = 1}^n {{G_j}( x )} $ is the inner function, and $F_i(\cdot)$ is the outer function.

Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization

5 code implementations ICCV 2019 Liu Liu, Hongdong Li, Yuchao Dai

This paper tackles the problem of large-scale image-based localization (IBL) where the spatial location of a query image is determined by finding out the most similar reference images in a large database.

Image-Based Localization Representation Learning +1

Stochastic Zeroth-order Optimization via Variance Reduction method

no code implementations30 May 2018 Liu Liu, Minhao Cheng, Cho-Jui Hsieh, DaCheng Tao

However, due to the variance in the search direction, the convergence rates and query complexities of existing methods suffer from a factor of $d$, where $d$ is the problem dimension.

High Dimensional Robust Sparse Regression

no code implementations29 May 2018 Liu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis

Our algorithm recovers the true sparse parameters with sub-linear sample complexity, in the presence of a constant fraction of arbitrary corruptions.

regression Vocal Bursts Intensity Prediction

Approximate Newton-based statistical inference using only stochastic gradients

no code implementations23 May 2018 Tianyang Li, Anastasios Kyrillidis, Liu Liu, Constantine Caramanis

We present a novel statistical inference framework for convex empirical risk minimization, using approximate stochastic Newton steps.

Time Series Analysis

Discriminative Cross-View Binary Representation Learning

no code implementations4 Apr 2018 Liu Liu, Hairong Qi

Learning compact representation is vital and challenging for large scale multimedia data.

Image Retrieval Quantization +2

L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks

no code implementations27 Feb 2018 Shuang Wu, Guoqi Li, Lei Deng, Liu Liu, Yuan Xie, Luping Shi

Batch Normalization (BN) has been proven to be quite effective at accelerating and improving the training of deep neural networks (DNNs).


Variance Reduced methods for Non-convex Composition Optimization

no code implementations13 Nov 2017 Liu Liu, Ji Liu, DaCheng Tao

In this paper, we apply the variance-reduced technique to derive two variance reduced algorithms that significantly improve the query complexity if the number of inner component functions is large.

Duality-free Methods for Stochastic Composition Optimization

no code implementations26 Oct 2017 Liu Liu, Ji Liu, DaCheng Tao

We consider the composition optimization with two expected-value functions in the form of $\frac{1}{n}\sum\nolimits_{i = 1}^n F_i(\frac{1}{m}\sum\nolimits_{j = 1}^m G_j(x))+R(x)$, { which formulates many important problems in statistical learning and machine learning such as solving Bellman equations in reinforcement learning and nonlinear embedding}.

Efficient Global 2D-3D Matching for Camera Localization in a Large-Scale 3D Map

no code implementations ICCV 2017 Liu Liu, Hongdong Li, Yuchao Dai

In this paper, we introduce a global method which harnesses global contextual information exhibited both within the query image and among all the 3D points in the map.

3D Feature Matching Camera Localization

Person Re-identification Using Visual Attention

no code implementations23 Jul 2017 Alireza Rahimpour, Liu Liu, Ali Taalimi, Yang song, Hairong Qi

Despite recent attempts for solving the person re-identification problem, it remains a challenging task since a person's appearance can vary significantly when large variations in view angle, human pose, and illumination are involved.

Person Re-Identification

Multi-View Task-Driven Recognition in Visual Sensor Networks

no code implementations30 May 2017 Ali Taalimi, Alireza Rahimpour, Liu Liu, Hairong Qi

Nowadays, distributed smart cameras are deployed for a wide set of tasks in several application scenarios, ranging from object recognition, image retrieval, and forensic applications.

Image Retrieval Multi-Task Learning +3

Addressing Ambiguity in Multi-target Tracking by Hierarchical Strategy

no code implementations30 May 2017 Ali Taalimi, Liu Liu, Hairong Qi

We use a network flow approach to link detections in low-level and tracklets in high-level.

Statistical inference using SGD

no code implementations21 May 2017 Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis

We present a novel method for frequentist statistical inference in $M$-estimation problems, based on stochastic gradient descent (SGD) with a fixed step size: we demonstrate that the average of such SGD sequences can be used for statistical inference, after proper scaling.

Multi-view (Joint) Probability Linear Discrimination Analysis for Multi-view Feature Verification

no code implementations20 Apr 2017 Ziqiang Shi, Liu Liu, Mengjiao Wang, Rujie Liu

However, in practical use, when using multi-task learned network as feature extractor, the extracted feature are always attached to several labels.

Decision Making

End-to-end Binary Representation Learning via Direct Binary Embedding

no code implementations15 Mar 2017 Liu Liu, Alireza Rahimpour, Ali Taalimi, Hairong Qi

Furthermore, in the effort of handling multilabel images, we design a joint cross entropy loss that includes both softmax cross entropy and weighted binary cross entropy in consideration of the correlation and independence of labels, respectively.

Image Retrieval Object Recognition +3

CNNLab: a Novel Parallel Framework for Neural Networks using GPU and FPGA-a Practical Study with Trade-off Analysis

no code implementations20 Jun 2016 Maohua Zhu, Liu Liu, Chao Wang, Yuan Xie

To improve the performance and maintain the scalability, we present CNNLab, a novel deep learning framework using GPU and FPGA-based accelerators.


Robust and Efficient Relative Pose with a Multi-camera System for Autonomous Vehicle in Highly Dynamic Environments

no code implementations12 May 2016 Liu Liu, Hongdong Li, Yuchao Dai

When the solver is used in combination with RANSAC, we are able to quickly prune unpromising hypotheses, significantly improve the chance of finding inliers.

Motion Estimation

Compressing Deep Convolutional Networks using Vector Quantization

no code implementations18 Dec 2014 Yunchao Gong, Liu Liu, Ming Yang, Lubomir Bourdev

In this paper, we tackle this model storage issue by investigating information theoretical vector quantization methods for compressing the parameters of CNNs.

Classification General Classification +5

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