Chang Liu

Recreation of the Periodic Table with an Unsupervised Machine Learning Algorithm

In 1869, the first draft of the periodic table was published by Russian ...
12/23/2019 ∙ by Minoru Kusaba, et al. ∙ 41 ∙ share

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Mixed Reinforcement Learning with Additive Stochastic Uncertainty

Reinforcement learning (RL) methods often rely on massive exploration da...
02/28/2020 ∙ by Yao Mu, et al. ∙ 30 ∙ share

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A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural Network

Data scarcity has refrained deep learning models from making greater pro...
03/29/2019 ∙ by Weiwei Zong, et al. ∙ 26 ∙ share

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Learning to Respond with Stickers: A Framework of Unifying Multi-Modality in Multi-Turn Dialog

Stickers with vivid and engaging expressions are becoming increasingly p...
03/10/2020 ∙ by Shen Gao, et al. ∙ 24 ∙ share

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Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers

Recent emerged quantization technique (i.e., using low bit-width fixed-p...
11/01/2019 ∙ by Xishan Zhang, et al. ∙ 19 ∙ share

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RGB-D Individual Segmentation

Fine-grained recognition task deals with sub-category classification pro...
10/16/2019 ∙ by Wenqiang Xu, et al. ∙ 18 ∙ share

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A Multiscale Image Denoising Algorithm Based On Dilated Residual Convolution Network

Image denoising is a classical problem in low level computer vision. Mod...
12/21/2018 ∙ by Chang Liu, et al. ∙ 16 ∙ share

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Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning

We propose a novel self-supervised method, referred to as Video Cloze Pr...
01/02/2020 ∙ by Dezhao Luo, et al. ∙ 7 ∙ share

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Straight-Through Estimator as Projected Wasserstein Gradient Flow

The Straight-Through (ST) estimator is a widely used technique for back-...
10/05/2019 ∙ by Pengyu Cheng, et al. ∙ 5 ∙ share

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Deep Relational Reasoning Graph Network for Arbitrary Shape Text Detection

Arbitrary shape text detection is a challenging task due to the high var...
03/17/2020 ∙ by Shi-Xue Zhang, et al. ∙ 4 ∙ share

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Multi-task Learning for Macromolecule Classification, Segmentation and Coarse Structural Recovery in Cryo-Tomography

Cellular Electron Cryo-Tomography (CECT) is a powerful 3D imaging tool f...
05/16/2018 ∙ by Chang Liu, et al. ∙ 2 ∙ share

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DWM: A Decomposable Winograd Method for Convolution Acceleration

Winograd's minimal filtering algorithm has been widely used in Convoluti...
02/03/2020 ∙ by Di Huang, et al. ∙ 1 ∙ share

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Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection

The problem of cross-platform binary code similarity detection aims at d...
08/22/2017 ∙ by Xiaojun Xu, et al. ∙ 0 ∙ share

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Analyzing and Improving Stein Variational Gradient Descent for High-dimensional Marginal Inference

Stein variational gradient descent (SVGD) is a nonparametric inference m...
11/13/2017 ∙ by Jingwei Zhuo, et al. ∙ 0 ∙ share

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Can you fool AI with adversarial examples on a visual Turing test?

Deep learning has achieved impressive results in many areas of Computer ...
09/25/2017 ∙ by Xiaojun Xu, et al. ∙ 0 ∙ share

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Pragmatic-Pedagogic Value Alignment

For an autonomous system to provide value (e.g., to customers, designers...
07/20/2017 ∙ by Jaime F. Fisac, et al. ∙ 0 ∙ share

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Feature Analysis and Selection for Training an End-to-End Autonomous Vehicle Controller Using the Deep Learning Approach

Deep learning-based approaches have been widely used for training contro...
03/28/2017 ∙ by Shun Yang, et al. ∙ 0 ∙ share

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Riemannian Stein Variational Gradient Descent for Bayesian Inference

We develop Riemannian Stein Variational Gradient Descent (RSVGD), a Baye...
11/30/2017 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Robust High-Dimensional Linear Regression

The effectiveness of supervised learning techniques has made them ubiqui...
08/07/2016 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Automated Inference on Sociopsychological Impressions of Attractive Female Faces

This article is a sequel to our earlier work [25]. The main objective of...
12/11/2016 ∙ by Xiaolin Wu, et al. ∙ 0 ∙ share

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DeepFood: Deep Learning-Based Food Image Recognition for Computer-Aided Dietary Assessment

Worldwide, in 2014, more than 1.9 billion adults, 18 years and older, we...
06/17/2016 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Latent Feature Based FM Model For Rating Prediction

Rating Prediction is a basic problem in Recommender System, and one of t...
10/29/2014 ∙ by Xudong Liu, et al. ∙ 0 ∙ share

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Latent Attention For If-Then Program Synthesis

Automatic translation from natural language descriptions into programs i...
11/07/2016 ∙ by Xinyun Chen, et al. ∙ 0 ∙ share

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Regularizing Face Verification Nets For Pain Intensity Regression

Limited labeled data are available for the research of estimating facial...
02/22/2017 ∙ by Feng Wang, et al. ∙ 0 ∙ share

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Learning Neural Programs To Parse Programs

In this work, we study an important problem: learning programs from inpu...
06/05/2017 ∙ by Xinyun Chen, et al. ∙ 0 ∙ share

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Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Deep learning models have achieved high performance on many tasks, and t...
12/15/2017 ∙ by Xinyun Chen, et al. ∙ 0 ∙ share

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Demonstration of Topological Data Analysis on a Quantum Processor

Topological data analysis offers a robust way to extract useful informat...
01/19/2018 ∙ by He-Liang Huang, et al. ∙ 0 ∙ share

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Deep learning based supervised semantic segmentation of Electron Cryo-Subtomograms

Cellular Electron Cryo-Tomography (CECT) is a powerful imaging technique...
02/12/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Learning-Based Dequantization For Image Rsstoration Against Extremely Poor Illumination

All existing image enhancement methods, such as HDR tone mapping, cannot...
03/05/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Attentive Tensor Product Learning for Language Generation and Grammar Parsing

This paper proposes a new architecture - Attentive Tensor Product Learni...
02/20/2018 ∙ by Qiuyuan Huang, et al. ∙ 0 ∙ share

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Generating Plans that Predict Themselves

Collaboration requires coordination, and we coordinate by anticipating o...
02/14/2018 ∙ by Jaime F. Fisac, et al. ∙ 0 ∙ share

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The Secret Sharer: Measuring Unintended Neural Network Memorization & Extracting Secrets

Machine learning models based on neural networks and deep learning are b...
02/22/2018 ∙ by Nicholas Carlini, et al. ∙ 0 ∙ share

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A Machine Learning Approach To Prevent Malicious Calls Over Telephony Networks

Malicious calls, i.e., telephony spams and scams, have been a long-stand...
04/07/2018 ∙ by Huichen Li, et al. ∙ 0 ∙ share

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SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning

Synthesizing SQL queries from natural language is a long-standing open p...
11/13/2017 ∙ by Xiaojun Xu, et al. ∙ 0 ∙ share

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Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration

The study of human-robot interaction is fundamental to the design and us...
02/06/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Performance Analysis for Practical Unmanned Aerial Vehicle Networks with LoS/NLoS Transmissions

In this paper, we provide a performance analysis for practical unmanned ...
04/03/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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A Language for Probabilistically Oblivious Computation

An oblivious computation is one that is free of direct and indirect info...
11/25/2017 ∙ by David Darais, et al. ∙ 0 ∙ share

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Curriculum Adversarial Training

Recently, deep learning has been applied to many security-sensitive appl...
05/13/2018 ∙ by Qi-Zhi Cai, et al. ∙ 0 ∙ share

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Origami Inspired Reconfigurable Antenna for Wireless Communication Systems

This paper presents the design, fabrication, and experimental validation...
05/25/2018 ∙ by Ali Molaei, et al. ∙ 0 ∙ share

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An efficient Moving Morphable Component (MMC)-based approach for multi-resolution topology optimization

In the present work, a highly efficient Moving Morphable Component (MMC)...
05/05/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Accelerated First-order Methods on the Wasserstein Space for Bayesian Inference

We consider doing Bayesian inference by minimizing the KL divergence on ...
07/04/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Linear Span Network for Object Skeleton Detection

Robust object skeleton detection requires to explore rich representative...
07/25/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Tree-to-tree Neural Networks for Program Translation

Program translation is an important tool to migrate legacy code in one l...
02/11/2018 ∙ by Xinyun Chen, et al. ∙ 0 ∙ share

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Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

As machine learning becomes widely used for automated decisions, attacke...
04/01/2018 ∙ by Matthew Jagielski, et al. ∙ 0 ∙ share

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Modified Self-Organized Task Allocation in a Group of Robots

This paper introduces a modified self-organized task allocation algorith...
08/30/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Boosting Model Performance through Differentially Private Model Aggregation

A key factor in developing high performing machine learning models is th...
11/12/2018 ∙ by Sophia Collet, et al. ∙ 0 ∙ share

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Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different d...
11/05/2018 ∙ by Spyridon Bakas, et al. ∙ 0 ∙ share

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Bayesian inference in high-dimensional linear models using an empirical correlation-adaptive prior

In the context of a high-dimensional linear regression model, we propose...
10/01/2018 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs

Recurrent Neural Networks (RNNs) are becoming increasingly important for...
12/12/2018 ∙ by Zhe Li, et al. ∙ 0 ∙ share

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Understanding MCMC Dynamics as Flows on the Wasserstein Space

It is known that the Langevin dynamics used in MCMC is the gradient flow...
02/01/2019 ∙ by Chang Liu, et al. ∙ 0 ∙ share

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Chang Liu

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