b'Ji Liu'

Distributed Learning Systems with First-order Methods

Scalable and efficient distributed learning is one of the main driving f...
04/12/2021 ∙ by Ji Liu, et al. ∙ 0 ∙ share

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Reputation and Pricing Dynamics in Online Markets

We study the economic interactions among sellers and buyers in online ma...
03/30/2021 ∙ by Qian Ma, et al. ∙ 0 ∙ share

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Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond

Deep neural networks have been well-known for their superb performance i...
03/19/2021 ∙ by Xuhong Li, et al. ∙ 0 ∙ share

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1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed

Scalable training of large models (like BERT and GPT-3) requires careful...
02/04/2021 ∙ by Hanlin Tang, et al. ∙ 0 ∙ share

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Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments

Exploration under sparse reward is a long-standing challenge of model-fr...
01/20/2021 ∙ by Daochen Zha, et al. ∙ 6 ∙ share

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C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak

The novel coronavirus disease (COVID-19) has crushed daily routines and ...
12/22/2020 ∙ by Congxi Xiao, et al. ∙ 0 ∙ share

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Relaxed Peephole Optimization: A Novel Compiler Optimization for Quantum Circuits

In this paper, we propose a novel quantum compiler optimization, named r...
12/14/2020 ∙ by Ji Liu, et al. ∙ 0 ∙ share

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Federated Bandit: A Gossiping Approach

In this paper, we study Federated Bandit, a decentralized Multi-Armed Ba...
10/24/2020 ∙ by Zhaowei Zhu, et al. ∙ 0 ∙ share

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Short Video-based Advertisements Evaluation System: Self-Organizing Learning Approach

With the rising of short video apps, such as TikTok, Snapchat and Kwai, ...
10/23/2020 ∙ by Yunjie Zhang, et al. ∙ 0 ∙ share

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Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free

Adversarial training and its many variants substantially improve deep ne...
10/22/2020 ∙ by Haotao Wang, et al. ∙ 0 ∙ share

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Tempura: A General Cost Based Optimizer Framework for Incremental Data Processing (Extended Version)

Incremental processing is widely-adopted in many applications, ranging f...
09/28/2020 ∙ by Zuozhi Wang, et al. ∙ 0 ∙ share

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Themes Informed Audio-visual Correspondence Learning

The applications of short-term user-generated video (UGV), such as Snapc...
09/14/2020 ∙ by Runze Su, et al. ∙ 12 ∙ share

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ServiceNet: A P2P Service Network

Given a large number of online services on the Internet, from time to ti...
09/04/2020 ∙ by Ji Liu, et al. ∙ 0 ∙ share

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Pose-Guided High-Resolution Appearance Transfer via Progressive Training

We propose a novel pose-guided appearance transfer network for transferr...
08/27/2020 ∙ by Ji Liu, et al. ∙ 0 ∙ share

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APMSqueeze: A Communication Efficient Adam-Preconditioned Momentum SGD Algorithm

Adam is the important optimization algorithm to guarantee efficiency and...
08/26/2020 ∙ by Hanlin Tang, et al. ∙ 11 ∙ share

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GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework

Generative adversarial networks (GANs) have gained increasing popularity...
08/25/2020 ∙ by Haotao Wang, et al. ∙ 16 ∙ share

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Streaming Probabilistic Deep Tensor Factorization

Despite the success of existing tensor factorization methods, most of th...
07/14/2020 ∙ by Shikai Fang, et al. ∙ 0 ∙ share

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Lossless CNN Channel Pruning via Gradient Resetting and Convolutional Re-parameterization

Channel pruning (a.k.a. filter pruning) aims to slim down a convolutiona...
07/07/2020 ∙ by Xiaohan Ding, et al. ∙ 0 ∙ share

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On Effective Parallelization of Monte Carlo Tree Search

Despite its groundbreaking success in Go and computer games, Monte Carlo...
06/15/2020 ∙ by Anji Liu, et al. ∙ 0 ∙ share

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Neural Network Activation Quantization with Bitwise Information Bottlenecks

Recent researches on information bottleneck shed new light on the contin...
06/09/2020 ∙ by Xichuan Zhou, et al. ∙ 0 ∙ share

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Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity

In this paper, we introduce proximal gradient temporal difference learni...
06/06/2020 ∙ by Bo Liu, et al. ∙ 0 ∙ share

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Regularized Off-Policy TD-Learning

We present a novel l_1 regularized off-policy convergent TD-learning met...
06/06/2020 ∙ by Bo Liu, et al. ∙ 0 ∙ share

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Data Poisoning Attacks on Federated Machine Learning

Federated machine learning which enables resource constrained node devic...
04/19/2020 ∙ by Gan Sun, et al. ∙ 0 ∙ share

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A Private and Finite-Time Algorithm for Solving a Distributed System of Linear Equations

This paper studies a system of linear equations, denoted as Ax = b, whic...
04/09/2020 ∙ by Shripad Gade, et al. ∙ 0 ∙ share

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Depth Edge Guided CNNs for Sparse Depth Upsampling

Guided sparse depth upsampling aims to upsample an irregularly sampled s...
03/23/2020 ∙ by Yi Guo, et al. ∙ 12 ∙ share

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Stochastic Recursive Momentum for Policy Gradient Methods

In this paper, we propose a novel algorithm named STOchastic Recursive M...
03/09/2020 ∙ by Huizhuo Yuan, et al. ∙ 0 ∙ share

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IMRAM: Iterative Matching with Recurrent Attention Memory for Cross-Modal Image-Text Retrieval

Enabling bi-directional retrieval of images and texts is important for u...
03/08/2020 ∙ by Hui Chen, et al. ∙ 8 ∙ share

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End-to-end Robustness for Sensing-Reasoning Machine Learning Pipelines

As machine learning (ML) being applied to many mission-critical scenario...
02/28/2020 ∙ by Zhuolin Yang, et al. ∙ 25 ∙ share

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MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA

OpenCL for FPGA enables developers to design FPGAs using a programming m...
02/05/2020 ∙ by Ji Liu, et al. ∙ 0 ∙ share

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A novel tree-structured point cloud dataset for skeletonization algorithm evaluation

Curve skeleton extraction from unorganized point cloud is a fundamental ...
01/09/2020 ∙ by Yan Lin, et al. ∙ 0 ∙ share

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Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization

Stochastic compositional optimization arises in many important machine l...
12/31/2019 ∙ by Huizhuo Yuan, et al. ∙ 0 ∙ share

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ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries

Zero-shot learning (ZSL) has received extensive attention recently espec...
10/24/2019 ∙ by Xingxing Zhang, et al. ∙ 0 ∙ share

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Hierarchical Prototype Learning for Zero-Shot Recognition

Zero-Shot Learning (ZSL) has received extensive attention and successes ...
10/24/2019 ∙ by Xingxing Zhang, et al. ∙ 0 ∙ share

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Learning Sparsity and Quantization Jointly and Automatically for Neural Network Compression via Constrained Optimization

Deep Neural Networks (DNNs) are widely applied in a wide range of usecas...
10/14/2019 ∙ by Haichuan Yang, et al. ∙ 0 ∙ share

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Central Server Free Federated Learning over Single-sided Trust Social Networks

Federated learning has become increasingly important for modern machine ...
10/11/2019 ∙ by Chaoyang He, et al. ∙ 0 ∙ share

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An Interactive Control Approach to 3D Shape Reconstruction

The ability to accurately reconstruct the 3D facets of a scene is one of...
10/07/2019 ∙ by Bipul Islam, et al. ∙ 9 ∙ share

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Global Sparse Momentum SGD for Pruning Very Deep Neural Networks

Deep Neural Network (DNN) is powerful but computationally expensive and ...
09/27/2019 ∙ by Xiaohan Ding, et al. ∙ 0 ∙ share

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PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions

Graph node embedding aims at learning a vector representation for all no...
09/25/2019 ∙ by Shupeng Gui, et al. ∙ 0 ∙ share

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DeepSqueeze: Decentralization Meets Error-Compensated Compression

Communication is a key bottleneck in distributed training. Recently, an ...
07/17/2019 ∙ by Hanlin Tang, et al. ∙ 0 ∙ share

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DeepSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression

Communication is a key bottleneck in distributed training. Recently, an ...
07/17/2019 ∙ by Hanlin Tang, et al. ∙ 0 ∙ share

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Stochastic Convergence Results for Regularized Actor-Critic Methods

In this paper, we present a stochastic convergence proof, under suitable...
07/13/2019 ∙ by Wesley Suttle, et al. ∙ 0 ∙ share

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A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning

This paper considers a distributed reinforcement learning problem in whi...
07/06/2019 ∙ by Yixuan Lin, et al. ∙ 0 ∙ share

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DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression

A standard approach in large scale machine learning is distributed stoch...
05/15/2019 ∙ by Hanlin Tang, et al. ∙ 0 ∙ share

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A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning

This paper extends off-policy reinforcement learning to the multi-agent ...
03/15/2019 ∙ by Wesley Suttle, et al. ∙ 0 ∙ share

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Optimal Projection Guided Transfer Hashing for Image Retrieval

Recently, learning to hash has been widely studied for image retrieval t...
03/01/2019 ∙ by Ji Liu, et al. ∙ 0 ∙ share

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SCEF: A Support-Confidence-aware Embedding Framework for Knowledge Graph Refinement

Knowledge graph (KG) refinement mainly aims at KG completion and correct...
02/18/2019 ∙ by Yu Zhao, et al. ∙ 0 ∙ share

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Adversarially Trained Model Compression: When Robustness Meets Efficiency

The robustness of deep models to adversarial attacks has gained signific...
02/10/2019 ∙ by Shupeng Gui, et al. ∙ 15 ∙ share

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Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend

Decentralized Online Learning (online learning in decentralized networks...
01/29/2019 ∙ by Yawei Zhao, et al. ∙ 24 ∙ share

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Monocular 3D Pose Recovery via Nonconvex Sparsity with Theoretical Analysis

For recovering 3D object poses from 2D images, a prevalent method is to ...
12/29/2018 ∙ by Jianqiao Wangni, et al. ∙ 24 ∙ share

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Consensus and Disagreement of Heterogeneous Belief Systems in Influence Networks

Recently, an opinion dynamics model has been proposed to describe a netw...
12/12/2018 ∙ by Mengbin Ye, et al. ∙ 0 ∙ share

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Ji Liu

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